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merge into: Dark-Alex-17/coyote:feat/rag-driver-abstraction-v3
Branches Tags
Dark-Alex-17/coyote:main Dark-Alex-17/coyote:feat/rag-phase5-qdrant-write Dark-Alex-17/coyote:feat/rag-driver-abstraction-v3 Dark-Alex-17/coyote:graph-based-rag Dark-Alex-17/coyote:skills Dark-Alex-17/coyote:develop Dark-Alex-17/coyote:graph-agents Dark-Alex-17/coyote:config-refactor Dark-Alex-17/coyote:restful-api-docs Dark-Alex-17/coyote:langchain
Dark-Alex-17/coyote:v0.7.3 Dark-Alex-17/coyote:v0.7.2 Dark-Alex-17/coyote:v0.7.1 Dark-Alex-17/coyote:v0.7.0 Dark-Alex-17/coyote:v0.6.0 Dark-Alex-17/coyote:v0.5.0 Dark-Alex-17/coyote:v0.4.0 Dark-Alex-17/coyote:v0.3.0 Dark-Alex-17/coyote:v0.2.0 Dark-Alex-17/coyote:v0.1.3 Dark-Alex-17/coyote:v0.1.2 Dark-Alex-17/coyote:v0.1.1
..
pull from: Dark-Alex-17/coyote:restful-api-docs
Branches Tags
Dark-Alex-17/coyote:main Dark-Alex-17/coyote:feat/rag-phase5-qdrant-write Dark-Alex-17/coyote:feat/rag-driver-abstraction-v3 Dark-Alex-17/coyote:graph-based-rag Dark-Alex-17/coyote:skills Dark-Alex-17/coyote:develop Dark-Alex-17/coyote:graph-agents Dark-Alex-17/coyote:config-refactor Dark-Alex-17/coyote:restful-api-docs Dark-Alex-17/coyote:langchain
Dark-Alex-17/coyote:v0.7.3 Dark-Alex-17/coyote:v0.7.2 Dark-Alex-17/coyote:v0.7.1 Dark-Alex-17/coyote:v0.7.0 Dark-Alex-17/coyote:v0.6.0 Dark-Alex-17/coyote:v0.5.0 Dark-Alex-17/coyote:v0.4.0 Dark-Alex-17/coyote:v0.3.0 Dark-Alex-17/coyote:v0.2.0 Dark-Alex-17/coyote:v0.1.3 Dark-Alex-17/coyote:v0.1.2 Dark-Alex-17/coyote:v0.1.1
1 Commits
feat/rag-driver-abstraction-v3 .. restful-api-docs
Author SHA1 Message Date
Dark-Alex-17 1ee6b4d7c7 docs: Documentation for the RESTful API POC 2026-05-01 14:45:13 -06:00
385 changed files with 28229 additions and 52583 deletions
Expand all files Collapse all files
.github/ISSUE_TEMPLATE/bug_report.yaml
+13 -13
View File
@@ -21,25 +21,25 @@ body:
value: |
I tried this:
1. `coyote`
1. `loki`
I expected this to happen:
Instead, this happened:
- type: textarea
id: coyote-log
id: loki-log
attributes:
label: Coyote log
description: Include the Coyote log file to help diagnose the issue. (`coyote --info` to see the log_path)
label: Loki log
description: Include the Loki log file to help diagnose the issue. (`loki --info` to see the log_path)
value: |
| OS | Log file location |
| ------- | ----------------------------------------------------- |
| Linux | `~/.cache/coyote/coyote.log` |
| Mac | `~/Library/Logs/coyote/coyote.log` |
| Windows | `C:\Users\<User>\AppData\Local\coyote\coyote.log` |
| Linux | `~/.cache/loki/loki.log` |
| Mac | `~/Library/Logs/loki/loki.log` |
| Windows | `C:\Users\<User>\AppData\Local\loki\loki.log` |
```
please provide a copy of your coyote log file here if possible; you may need to redact some of the lines
please provide a copy of your loki log file here if possible; you may need to redact some of the lines
```
- type: input
@@ -57,13 +57,13 @@ body:
validations:
required: true
- type: input
id: coyote-version
id: loki-version
attributes:
label: Coyote Version
label: Loki Version
description: >
Coyote version (`coyote --version` if using a release, `git describe` if building
Loki version (`loki --version` if using a release, `git describe` if building
from main).
**Make sure that you are using the [latest coyote release](https://github.com/Dark-Alex-17/coyote/releases) or a newer main build**
placeholder: "coyote 0.1.0"
**Make sure that you are using the [latest loki release](https://github.com/Dark-Alex-17/loki/releases) or a newer main build**
placeholder: "loki 0.1.0"
validations:
required: true
.github/workflows/ci.yaml
-11
View File
@@ -36,17 +36,6 @@ jobs:
- uses: Swatinem/rust-cache@v2
- name: Cache DuckDB Extensions
id: duckdb-extensions
uses: actions/cache@v4
with:
path: ~/.duckdb/extensions
key: duckdb-ext-${{ matrix.os }}-${{ hashFiles('Cargo.lock') }}
- name: Install DuckDB Extensions
if: steps.duckdb-extensions.outputs.cache-hit != 'true'
run: cargo test --all duckdb
- name: Test
run: cargo test --all
.github/workflows/release.yaml
+29 -91
View File
@@ -8,9 +8,9 @@ on:
workflow_dispatch:
inputs:
bump_type:
description: 'Specify the type of version bump'
description: "Specify the type of version bump"
required: true
default: 'patch'
default: "patch"
type: choice
options:
- patch
@@ -46,7 +46,7 @@ jobs:
- name: Set up Python
uses: actions/setup-python@v4
with:
python-version: '3.10'
python-version: "3.10"
- name: Install Commitizen
run: |
@@ -98,9 +98,9 @@ jobs:
# Ignore Act's local artifact dir noise
echo artifacts/ >> .git/info/exclude || true
# Edit the version line right after name="coyote"
# Edit the version line right after name="loki"
sed -E -i '
/^[[:space:]]*name[[:space:]]*=[[:space:]]*"coyote"[[:space:]]*$/ {
/^[[:space:]]*name[[:space:]]*=[[:space:]]*"loki"[[:space:]]*$/ {
n
s|^[[:space:]]*version[[:space:]]*=[[:space:]]*"[^"]*"|version = "'"$VERSION"'"|
}
@@ -108,19 +108,17 @@ jobs:
cargo update || true
sed -i "s|image: 'darkalex17/coyote:v[^']*'|image: 'darkalex17/coyote:v${VERSION}'|" assets/sbx-kit/spec.yaml
# Git config that helps in Act
git config user.name "github-actions[bot]"
git config user.email "github-actions[bot]@users.noreply.github.com"
git config --global --add safe.directory "$GITHUB_WORKSPACE"
git status --porcelain
git diff --name-only -- Cargo.toml Cargo.lock assets/sbx-kit/spec.yaml || true
git diff --name-only -- Cargo.toml Cargo.lock || true
if ! git diff --quiet -- Cargo.toml Cargo.lock assets/sbx-kit/spec.yaml; then
git add -u -- Cargo.toml Cargo.lock assets/sbx-kit/spec.yaml
git commit -m "chore: bump Cargo.toml and sandbox image to $VERSION"
if ! git diff --quiet -- Cargo.toml Cargo.lock; then
git add -u -- Cargo.toml Cargo.lock
git commit -m "chore: bump Cargo.toml to $VERSION"
else
echo "No changes to commit (already at $VERSION)"
fi
@@ -165,28 +163,28 @@ jobs:
- target: aarch64-unknown-linux-musl
os: ubuntu-latest
use-cross: true
cargo-flags: ''
cargo-flags: ""
- target: aarch64-apple-darwin
os: macos-latest
use-cross: true
cargo-flags: ''
cargo-flags: ""
- target: aarch64-pc-windows-msvc
os: windows-latest
use-cross: true
cargo-flags: ''
cargo-flags: ""
- target: x86_64-apple-darwin
os: macos-latest
cargo-flags: ''
cargo-flags: ""
- target: x86_64-pc-windows-msvc
os: windows-latest
cargo-flags: ''
cargo-flags: ""
- target: x86_64-unknown-linux-musl
os: ubuntu-latest
use-cross: true
cargo-flags: ''
cargo-flags: ""
- target: x86_64-unknown-linux-gnu
os: ubuntu-latest
cargo-flags: ''
cargo-flags: ""
steps:
- name: Check if actor is repository owner
@@ -280,7 +278,7 @@ jobs:
- name: Verify file
shell: bash
run: |
file target/${{ matrix.target }}/release/coyote
file target/${{ matrix.target }}/release/loki
- name: Test
if: matrix.target != 'aarch64-apple-darwin' && matrix.target != 'aarch64-pc-windows-msvc'
@@ -340,7 +338,7 @@ jobs:
${{ steps.package.outputs.archive }}
${{ steps.package.outputs.sha }}
tag_name: v${{ env.RELEASE_VERSION }}
name: 'v${{ env.RELEASE_VERSION }}'
name: "v${{ env.RELEASE_VERSION }}"
body_path: artifacts/changelog.md
prerelease: false
@@ -384,11 +382,11 @@ jobs:
shell: bash
run: |
# Set environment variables
macos_sha="$(cat ./artifacts/coyote-x86_64-apple-darwin.sha256 | awk '{print $1}')"
macos_sha="$(cat ./artifacts/loki-x86_64-apple-darwin.sha256 | awk '{print $1}')"
echo "MACOS_SHA=$macos_sha" >> $GITHUB_ENV
macos_sha_arm="$(cat ./artifacts/coyote-aarch64-apple-darwin.sha256 | awk '{print $1}')"
macos_sha_arm="$(cat ./artifacts/loki-aarch64-apple-darwin.sha256 | awk '{print $1}')"
echo "MACOS_SHA_ARM=$macos_sha_arm" >> $GITHUB_ENV
linux_sha="$(cat ./artifacts/coyote-x86_64-unknown-linux-musl.sha256 | awk '{print $1}')"
linux_sha="$(cat ./artifacts/loki-x86_64-unknown-linux-musl.sha256 | awk '{print $1}')"
echo "LINUX_SHA=$linux_sha" >> $GITHUB_ENV
release_version="$(cat ./artifacts/release-version)"
echo "RELEASE_VERSION=$release_version" >> $GITHUB_ENV
@@ -404,23 +402,23 @@ jobs:
if: env.ACT != 'true'
run: |
# run packaging script
python "./deployment/homebrew/packager.py" ${{ env.RELEASE_VERSION }} "./deployment/homebrew/coyote.rb.template" "./coyote.rb" ${{ env.MACOS_SHA }} ${{ env.MACOS_SHA_ARM }} ${{ env.LINUX_SHA }}
python "./deployment/homebrew/packager.py" ${{ env.RELEASE_VERSION }} "./deployment/homebrew/loki.rb.template" "./loki.rb" ${{ env.MACOS_SHA }} ${{ env.MACOS_SHA_ARM }} ${{ env.LINUX_SHA }}
- name: Push changes to Homebrew tap
if: env.ACT != 'true'
env:
TOKEN: ${{ secrets.COYOTE_GITHUB_TOKEN }}
TOKEN: ${{ secrets.LOKI_GITHUB_TOKEN }}
run: |
# push to Git
git config --global user.name "Dark-Alex-17"
git config --global user.email "alex.j.tusa@gmail.com"
git clone https://Dark-Alex-17:${{ secrets.COYOTE_GITHUB_TOKEN }}@github.com/Dark-Alex-17/homebrew-coyote.git
rm homebrew-coyote/Formula/coyote.rb
cp coyote.rb homebrew-coyote/Formula
cd homebrew-coyote
git clone https://Dark-Alex-17:${{ secrets.LOKI_GITHUB_TOKEN }}@github.com/Dark-Alex-17/homebrew-loki.git
rm homebrew-loki/Formula/loki.rb
cp loki.rb homebrew-loki/Formula
cd homebrew-loki
git add .
git diff-index --quiet HEAD || git commit -am "Update formula for Coyote release ${{ env.RELEASE_VERSION }}"
git push https://$TOKEN@github.com/Dark-Alex-17/homebrew-coyote.git
git diff-index --quiet HEAD || git commit -am "Update formula for Loki release ${{ env.RELEASE_VERSION }}"
git push https://$TOKEN@github.com/Dark-Alex-17/homebrew-loki.git
publish-crate:
needs: publish-github-release
@@ -458,63 +456,3 @@ jobs:
if: env.ACT != 'true'
with:
registry-token: ${{ secrets.CARGO_REGISTRY_TOKEN }}
publish-sandbox-image:
needs: [publish-github-release]
name: Publish Sandbox Docker Image
runs-on: ubuntu-latest
steps:
- name: Check if actor is repository owner
if: ${{ github.actor != github.repository_owner && env.ACT != 'true' }}
run: |
echo "You are not authorized to run this workflow."
exit 1
- name: Checkout repository
uses: actions/checkout@v4
with:
fetch-depth: 1
- name: Ensure repository is up-to-date
if: env.ACT != 'true'
run: |
git fetch --all
git pull
- name: Get release artifacts
uses: actions/download-artifact@v4
with:
path: artifacts
merge-multiple: true
- name: Set version variable
run: |
version="$(cat artifacts/release-version)"
echo "version=$version" >> $GITHUB_ENV
- name: Validate release environment variables
run: |
echo "Release version: ${{ env.version }}"
- name: Set up QEMU
uses: docker/setup-qemu-action@v3
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Login to Docker Hub
if: env.ACT != 'true'
uses: docker/login-action@v3
with:
username: ${{ secrets.DOCKER_USERNAME }}
password: ${{ secrets.DOCKER_PASSWORD }}
- name: Push to Docker Hub
uses: docker/build-push-action@v5
with:
context: .
file: Dockerfile
platforms: linux/amd64,linux/arm64
push: ${{ env.ACT != 'true' }}
tags: darkalex17/coyote:latest, darkalex17/coyote:v${{ env.version }}
build-args: COYOTE_VERSION=${{ env.version }}
.gitignore
+1 -1
View File
@@ -3,5 +3,5 @@
/.env
!cli/**
.idea/
/coyote.iml
/loki.iml
/.idea/
.loki-project.json
+1
View File
@@ -0,0 +1 @@
{"type":"rust","build":"cargo build","test":"cargo test","check":"cargo check","_detected_by":"heuristic","_cached_at":"2026-04-13T13:36:33-06:00"}
CHANGELOG.md
+4 -469
View File
@@ -1,468 +1,3 @@
## v0.8.3 (2026-08-03)
### Fix
- infinite loop bug when attempting to interrupt a prompt exchange right before a session compression
- ctrl-c inside of an auto-continue loop created an infinite loop
## v0.8.2 (2026-07-31)
### Fix
- sbx update doesn't allow undefined fields in sbx spec
## v0.8.1 (2026-07-30)
### Feat
- ctrl-c interrupts ongoing prompt in a session, but lets the user inject more instructions mid-stream
- improved function calling performance by allowing parallel tool calling
- created the architect and gatekeeper agents for dramatically improved coding performance
- Improved readability of session message exchange replays
- apply --agent/--role/--rag/--model flags in --acp-server mode
- add headless profile to sbx-kit spec
- implement ACP user-interaction to request_permission bridge
- implement ACP session/load and session/cancel
- implement ACP session/prompt
- add ACP server skeleton with stdout-purity test
- add --headless flag for unattended operation
### Fix
- ctrl-c interruption doesn't discard session messages when throbber is showing
- improper handling of fd-style globbing for directories in fs_glob
- properly templated architect design doc path in starter commands
- .copy works when sessions are resumed
- ACP session/prompt now drives the full tool-execution loop
- ACP spec conformance — ContentBlock prompt params and protocolVersion type
- restore stdout output for standalone --headless mode
- suppress tool-call display in headless mode; initialize session on session/new
- skip stdin drain and set silent render mode when --acp-server is active
- include graph-agent descriptions in .agent <TAB> completions
### Refactor
- move ACP server dispatch into run() for shared flag setup
## v0.8.0 (2026-07-25)
### Feat
- Dynamically detect if a selected client in the sandbox first run wizard supports oauth
- Add support for the --fresh flag again with host environment configuration injection
- force overwrite global sbx secrets
- add sbx secrets globally
- only create secrets local to a sandbox
- Improved credentials management for docker sandboxes
- renamed --contents arg for fs_write/patch to --content since most models attempt that first and error otherwise
- Used improved theme selections for tool call highlighting colors
- Improved theme-derived syntax highlighting for LLM tool call logging
- Improved coloring of LLM tool invocation outputs to make LLM output more readable and cohesive
- renamed the user__ask to user__select and improved descriptions to improve model usage
- Improved coloring/highlighting of tool calls to make LLM invocation logs easier to read
- long-running session improvements
- Made sisyphus suite of agents all auto-approved for tool usage
- added ast_grep tool to Sisyphus suite agents
- created the adversay agent and adversarial-review skill
- new spawnable_agents field in agents to let users restrict what agents can be spawned by a parent agent
- replay pre-compressed messages as well when resuming sessions for users to see
- created a new builtin function for agents who can spawn other agents to list available agents via agent__list_available
- **render**: hanging-indent line wrapping for lists and blockquotes
- **render**: wire table state machine and finalize hook
- **render**: render markdown tables with comfy-table
- **render**: parse table cells and column alignments
- **render**: detect markdown table rows and separators
- **render**: add comfy-table dependency and table border style
- **render**: activate rich markdown renderer as default
- **render**: rich block-level markdown rendering (headings, quotes, lists, hr)
- **render**: rich inline markdown rendering (bold, italic, code, links)
- **render**: detect markdown block-level line types
- **render**: precompute markdown scope styles for rich rendering
- Created the raw_markdown configuration flag
- added a .fork command to fork a new session from a running conversation
- **oauth**: enable browser-paste PKCE flow for OpenAI-compatible providers
- copy host OAuth tokens into sandbox at launch
- implement OAuth 2.0 Device Authorization Grant (RFC 8628)
- hint that browser 'paste code' pages can be ignored during callback capture
- openai-compatible wizard offers OAuth when provider has bundled oauth defaults
- validate unique client names at config load
- bundle xAI OAuth defaults in models.yaml
- OAuth branch in openai_compatible prepare_* fns
- get_oauth_provider_for_client dispatcher + client_config_info update
- OpenAICompatibleOAuthProvider (config-driven OAuthProvider impl)
- add auth + oauth fields to OpenAICompatibleConfig
- add oauth field to ProviderModels
- add client_credentials support to prepare_oauth_access_token
- add OAuthConfig + OAuthFlow types to oauth.rs
- Added reasoning effort to the right prompt
- Improved support for Anthropic's extended thinking
- Also support GEMINI.md workspace instructions
- Improved workspace instructions support
- also detect .mcp.json configurations at workspace roots
- Created new .tool enable/disable and .mcp enable/disable aliases to make REPL usage more egonomic
- Created a new .list <kind> REPL command to make discoveribility easier in the REPL
- Support claude-style hidden workspace MCP configuration files via .mcp.json
- Allow users to customize the workspace-specific configuration directory name so they can use Coyote with other CLI clients like .claude
- Add reasoning_effort validation for the main configuration file
- Add validation for reasoning_effort settings to prevent users from specifying erroneous values
- Added support for modifying the reasoning effort of reasoning models
- Explicitly Prevent .undo usage in graph agents
- Added an .undo command to the REPL to let users have more control over the conversation
- Improve sandbox startup time by using the prebuilt Coyote image
- Make coyote available as a docker image
- Made fs_patch more flexible for different model preferences of patch formats
- Installed nano into the sandbox so that users can edit config files in the sandbox directly
- Support workspace-local skill definitions and MCP configurations
- fully functional graph-based RAG
- Implemented graph-based RAG
- Added a --dangerously-skip-permissions flag to skip permission prompts for tool invocations
- Remove the temperature hyperparameter from the diagnose role
- Added a new oauth.redirectHost field to make it possible to further extend MCP support
- Updated the REPL mcp auth path to use the prettified error messaging
- Improved error messaging for failed MCP starts because of auth issues
- Added support for specifying the oauth port and client ID in MCP server configs
- Implemented OAuth support for OpenAI models via Codex endpoints
- merge MCP config when installing bundled mcp config
- Implemented durable state for sisyphus
- Installed ast-grep for the explore agent to use for better code exploration
- Created the step-runner graph agent for more deterministic coding workflows to produce even more reliable and higher-quality results
- Improved oracle and sisyphus agents with skill integrations for the new skills
- Created new sisyphus family skills to improve performance
- Created new diagnostic role and skill for use in other contexts
- Added new memory functions for deleting and renaming memory files, as well as new lints for memory expiration dates and staleness of memories to improve the memory system
- Created a new iwe skill and installed the iwe MCP server for utilizing large knowledgebases
- Session-specific, file-backed history in the REPL
- Replay session output when a user re-enters a session so all output can be seen again
- Added confirmation message after MCP Oauth succeeds when invoked from --auth-mcp
- Created the --auth-mcp CLI flag to let users auth with remote MCP servers without needing to be in the REPL
- add OAuth authentication support for remote MCP servers
- Added mixin for sisyphus so the ddg MCP server can search arbitrary domains
- added improved error messaging on MCP server initialization
- prefer musl versions for linux when running --update/.update
### Fix
- fresh wizard openai-compatible support
- config existence check for --fresh sandboxes
- Improve coyote sandbox startup time
- bypass forgotten sandbox mode check for MCP secret interpolation
- properly wrap sub-style changes in markdown rendering
- removed accidental duplicate ast_grep tool in explore agent
- npm and npx need the /usr/local/share/npm-global/lib directory to exist to run properly so I've added it to the dockerfile
- added executable bit to adversary agent tools script
- fetch descriptions from graph agent configs as well when listing agents
- **render**: suppress blank lines above rendered table
- chown the full sandbox cache dir, not just the coyote subdir
- chown the whole coyote cache dir not just the oauth dir in the sandbox
- fix typo in Gemini's generation_config property to use camelCase exclusively
- **oauth**: treat missing expires_in as non-expiring device_code token
- **oauth**: send Accept: application/json in device flow requests
- OAuth callback listener skips speculative/malformed browser connections
- resolve reasoning effort for the prompt for global defaults as well
- Account for default model reasoning_effort when supplying that value for the REPL prompts
- model narration included in history and between tool calls to prevent repetition
- Don't terminate agent loops early for null tool output
- reduce code duplication by reusing the new concrete_tool_names function in .list tools
- Agent tools can only be modified via .tool enable/disable using tools in the allowed whitelist in the agent
- re-render agent sessions when entering agents with either pre-configured agent_session or when entering an agent directly into a session
- Per RFC 9728, enable dynamic discovery of OAuth endpoints in MCP using path-aware discovery
- hot-attach to MCP servers that require auth after running .mcp auth <name>
- Correctly inherit graph-global model for extractor model if none is defined
- no cursor timeout when user scrolls away from ongoing streaming output
- default to the nano or notepad when a configured editor is not found
- When EDITOR, VISUAL, or config.editor is defined, don't verify via which
- Added a loop exit condition for the diagnostics skill
- Added directness clause to the diganose role to improve prompt
- fs tools now output better error handling to guide the model more effectively
- Make fs_read more tolerant of various arg invocation formats.
- todo functions are injected properly to roles when roles have auto_continue: true and the REPL is started directly into the role
- updated the redirect URI for OAuth MCP to use localhost since that's what is whitelisted, not 127.0.0.1
- allow MCP OAuth refresh_token to be absent from initial token exchanges
- Overrode the default JSON content-type for MCP OAuth so its properly application/x-www-form-urlencoded
- typo in mcp file name
- Added uvx wrapper for macos-based sandboxes
### Refactor
- Standardized paths module function names to not use 'path' in the name and to just always be either 'dir' or 'file'
- main.rs resolve_oauth_client uses new dispatcher
- split run_oauth_flow into pkce + client_credentials dispatchers
### Perf
- updated the memory injection warning so it only logs once, rather than after each keystroke
## v0.7.4 (2026-07-02)
### Feat
- Pin specific usql version to sbx kit
- recursively take ownership over the copied in coyote config for the sbx
- explicitly specify the COYOTE_CONFIG_DIR in the sbx kit
- --tail-logs can track log rollovers and incoporates a sleep timer to minimize idle CPU cycles
- Added support for log rolling so log files don't just blow up over time
### Fix
- Added back in --kit specification for the running of the sbx
- sbx isn't copying base files in their respective directories
- Update deprecated sbx kit config
- Properly chown the coyote config recursively and password file in the sbx
## v0.7.3 (2026-06-24)
### Fix
- apply bootstrapping of functions at startup to fix edge case
## v0.7.2 (2026-06-19)
### Fix
- usql version upgrade
## v0.7.1 (2026-06-19)
### Fix
- sbx mixins must be passed in directories, not as files and the files must be named spec.yaml per new sbx version
## v0.7.0 (2026-06-18)
### Feat
- added configurable cache path via the COYOTE_CACHE_PATH environment variable
- added a memory option to .set tab completions
- Added a diagnostic .info tools subcommand to make it easier to see what tools are enabled in all contexts
- Added additional info outputs for enabled skills and sbx directories
- directly execute shell commands from within the REPL
- created mixin kit for built-in functions and MCP servers
- Added sbx mixins for the secrets providers so users can also bootstrap those as well.
- added support for loading sbx mixins that are dynamically discovered in the users workspace and config directory
- Added a --fresh flag to let users create a truly bare bones sandbox without bootstrapping their config
- initial built-in sandboxing support powered by Docker sbx
- Added the ability to auto-bootstrap workspace memory when in git repos
- Added explicit guardrail handling for pending agents
- auto-append memory to memory index and don't necessarily require the LLM to remember to do it after a write
- Added an --init-memory [global|workspace] flag to easily and quickly enable memory
- added memory global configuration settings to the output of --info and .info
- added .set memory REPL commands to control memory injection and applied formatting
- Create the built-in memory management tools
- Append the memory system prompts (readonly or r/w) to the system prompt when applicable
- Created the --no-memory CLI flag to disable memory for this invocation
- Added the memory configuration properties and storage to the main app config, roles, sessions, and agents.
- initial scaffolding of a memory system
### Fix
- rebuild the tool scope after dynamically updating the skills_enabled value in the REPL
- properly resolve Windows-based local vault password file locations and bootstrap them into the sandbox when possible
- auto-translation of user-prefixed Mac and Linux paths for the vault password file when running inside a sandbox
- don't attempt to auto complete .vault list in the REPL; that's the end of the command
- buffer tool stdout as well as stderr so that any tools that error to stdout are captured and included in the response to the model, enabling the model to see what went wrong and to reason about how to fix it.
- auto-bootstrapped memory was accidentally putting the MEMORY.md directly in the repo root rather than .coyote/memory/MEMORY.md
- improved the fs_patch script description and added improved error handling to it.
- added in forgotten require_max_tokens to the fable model
- append memory functions to non-graph based agents on init
- when auto_continue is disabled via the .set auto_continue false command, it should strip the todo functions from the list of functions
- use rawPredict for non-streaming Claude requests
### Refactor
- Migrated the .skills command completion to use StateFlags and updated the help messages
## v0.6.0 (2026-06-05)
### Feat
- added skill hint prompt injection and configuration
- Fallthrough on missing secrets during mcp.json merging
- validate visible_skills field at config load time
- implemented reflexion (sorta) in sisyphus for significant code changes to delegate to the code-reviewer agent
- improved explore agent
- removed conditional fallback of LLM_*_RAW_JSON from built-ins
- updated enabled_skills handling to support both list and comma-separated strings
- added new REPL set commands for toggling skills and changing what skills are enabled
- upgraded to the latest version of mcp-remote
- fs_grep now works with both files and directories
- improved code reviewer agents with skills
- added round trip validation for vault providers to ensure permissions and authentication
- created new first-time run wizard for secrets provider
- vault_password_file or nothing at all is shorthand for just using the local gman provider for secret management
- refactored gman usage to be generic and work with various vault providers and use the SupportedProvider enum directly for configurations
- created initial parity gman generalization for vault provider
- Refactored the sisyhpus agent system to utilize the new skills system to improve performance and reliability
- llm graph nodes support skills
- updated sisyphus and coder tools
- removed potentially confusing tab completions for .skill
- .edit skill <name> support from within the REPL
- Added skills_dir to the info output of Coyote
- Created a few auto built-in skills
- Added support for auto_unload skills during chat
- cleaned up skill implementation
- support multiple skill flags to load multiple skills at CLI startup
- Modified --skill CLI to allow users to specify skills to start the REPL or CLI with.
- added CLI --skill flag for modifying skills easily
- REPL integration with skills
- dynamic loading/unloading of skill tools and MCP servers whenever load_skill/unload_skill are invoked
- created built-in functions for listing, loading, and unloading skills
- implemented the skills policy to track available skills per context
- added remote install and install support for skills
- created the skill registry
- decided to make skills persist to disk like agents and not in-memory like built-in roles
- scaffold skill module
### Fix
- disable skills for specific built-in roles
- redirect stderr into user's /dev/tty for guards
- azure doesn't support underscores in key vault
- accidental regression on enabled_skills being empty = all
- greedy secrets regex caused multiple secrets on one line to fail
- add agent context check to skill visibility validation
- enforced global visible_skills in llm node validation and improved skill loading error handling across the project
- restore agent skill policy on error during effective policy calculation
- apply the same validation for skill filenames on list_skills as happens everywhere else
- the vault's init_bare should try to load the provisioned secret_provider from the config file without also interpolating any of the rest of the configuration file. It should only fail if the user has not yet created a configuration file; i.e. done a first-time run.
- the vault roundtrip test used characters that are unsupported by some major secrets providers
- fixed tool filtering logic for skills and user functions in agents
- privilege leak when unloading skills and leaving tool scope untouched
- When bootstrapping an app config to interpolate secrets, clone the secrets provider configuration as well so config secrets stored in remote vaults can be used properly
- forgot to move back up the vault probe value error to be before the delete
- don't silently fail on skill role composition extraction in llm nodes
- set -euo pipefail for the temp script in execute_command.sh tool
- added forgotten skill name validation to has_skill to prevent side-channel attacks
- use unique values for the secrets round trip verification
- stop interpolating a line if any errors occur
- added path validation for skill names
- effective_policy unconditionally overwrote skill values for role-like structs
- updated execute_command to not mangle heredocs and also added explicit instructions to the coder and sisyphus agents to use fs_write and fs_patch over execute_command when writing files
- llm nodes accidentally skipped skill_registry::effective_role because I was passing an inline role instead
- updated temperature values for all agents and roles
- added back in require_max_tokens for new Claude models
- skill support also requires function calling to be enabled
- non_tty tests break on some TTY terminals
- skill loading on agents
- forgot to bootstrap skills on REPL startup
- remove now deprecated .skill edit command
### Refactor
- removed redundant skill name validation from has_skill function
- support both CSV and list formats for enabled_tools
- Support both CSV and list formats for enabled_mcp_servers
## v0.5.0 (2026-05-27)
### Feat
- rename Loki to Coyote
### Fix
- bash-based user interactions in agents accidentally regressed in graph implementation
- Claude function calling in agent contexts
- Claude code rate limit error per new Claude changes
## v0.4.0 (2026-05-23)
### Feat
- LLM node failures propgate up
- Added .install remote tab completions to the REPL
- feature complete install remote with category selection
- Support to interactively add secrets to Coyote that are missing from MCP configs when merging
- Added MCP config merging support for remote asset installations
- install remote now writes files to disk
- Created basic install_remote functions
- Created a more comprehensive and immediately useful default config for first runs
- Created an example graph-based agent called deep-research
- Improved coder agent that is now a graph-based agent
- Removed indicatif spinners. The UX just won't stop clobbering for parallel graph nodes
- Added agent variables support for graph agents and improved script executor to use the same environment variables as normal agent tool calling for further flexibility
- Improved UX with colored spinners for parallel graph agents and no clobbering outputs for sub-agents
- created new graph-based deep-research agent
- improved UX for parallel graph execution
- added branch progress tracker for better visualization of parallel graph super-steps
- Removed the jira-helper agent and replaced it with the atlassian role
- created the RenderMode enum to suppress stdout streaming during parallel graph super-steps
- Full support for map node types
- implemented the frontier-based scheduling for the graph executor with simplified state management (gotta love .clone)
- validation support for parallel graph execution; restricted map nodes to only run for nodes without next targets and not supporting chained map nodes
- created the staging area for state merges per super-step and created the built-in reducers (and their application) for the state merge phase of a super step
- scaffolding work for fan-out nodes for parallel branch execution support and stubbed out Map node types
- Coyote can now update itself via .update and --update commands
- added a .edit command for editing the MCP configuration file
- Created a new .install command to install bundled assets on-demand
- migrated llm node validation to graph loading time instead of graph runtime
- ripped out user input timeout scaffolding for approval and input node types; implementation can't be done cleanly
- added additional support for all RAG-configuration fields in RAG nodes
- initial support for RAG nodes in the graph execution system
- implemented structured logging for graph execution
- merged normal agent config and graph agent configs into one file (either/or)
- added structured-output extraction for llm and agent nodes
- created full llm node runtime implementation
- scaffolded together the initial llm node type and its executor
- wired together graph execution and agent graph dispatch
- implemented support for the graph executor
- created the approval node executor and the input node executor for user interaction
- Added initial support for native Coyote agent nodes in the graph-based agent system
- Added direct script invocation support for graph-based agents
- Added graph validation
- Implemented state management for agent graphs
- initial agent graph scaffolding
- add auto-continue support to all contexts
- dynamic tab completions now show the sessions for a given agent instead of only listing global sessions
- legacy SSE support for MCP server configurations
- support http/sse transport types for MCP server configurations so it fully supports claude desktop-style MCP configs
- 99% complete migration to new state structs to get away from God-Config struct; i.e. AppConfig, AppState, and RequestContext
- Automatic runtime customization using shebangs
- Created a demo TypeScript tool and a get_current_weather function in TypeScript
- Updated the Python demo tool to show all possible parameter types and variations
- Added TypeScript tool support using the refactored common ScriptedLanguage trait
### Fix
- Generified the functions usage of script detection for an executable bit on unix systems
- merge required claude code system prompt into instructions
- updated argc argument passing in run-tool and run-agent scripts
- Added additional graph validation for parallel reads and writes with dependencies between nodes states
- bug in next_single method and improved outcome handling for LLM node execution
- inline RAG bug when globbing files by extension without subdirectory globbing
- update the estimate_token_length function to use the standard word count method
- removed unnecessary regenerate logic for sessions and use the same logic for all contexts; prevents a panic on empty message list
- error when users try to start a session on a graph agent
- added on_other field for approval nodes so users can specify an alternative free-text target when none of the options match what they want
- accidentally added back in full agent tools on LLM nodes
- Improve the coder agent's usage of tools
- make the agent__collect escalation-aware so it doesn't freeze on sub-agent escalations
- check for an existing session before starting up MCP servers when switching to a role
- do not switch to agent if a session is active.
- Do not append todo instructions when function calling is disabled
- a bug in the dynamic completions because the crate name is coyote-ai but the binary is named coyote
- bug found by copilot that would create a lock on the PollSender for sse-based MCP servers
- Accidental shadow of temp_file function for Windows function calling
- upgraded to newer rmcp version to get native-tls support
- RagCache was not being used for agent and sub-agent instantiation
- TypeScript function args were being passed as objects rather than direct parameters
- Added in forgotten wrapper scripts for TypeScript tools
- don't shadow variables in binary path handling for Windows
- Tool call improvements for Windows systems
### Refactor
- migrated llm nodes to use Roles to simplify instructions handling and to function like inline roles
- migrated the next_node and apply_state_updates logic for LLM nodes into the LlmExecutor
- fully complete state re-architecting
- Fully ripped out the god Config struct
- Deprecated old Config struct initialization logic
- migrate functions and MCP servers to AppConfig
- Migrate the vault/bare_init logic
- created a single install_builtins free function to remove from Config::init
- partial migration to init in AppConfig
- Extracted common Python parser logic into a common.rs module
- python tools now use tree-sitter queries instead of AST
## v0.3.0 (2026-04-02)
### Feat
@@ -486,7 +21,7 @@
- Created a CodeRabbit-style code-reviewer agent
- Added configuration option in agents to indicate the timeout for user input before proceeding (defaults to 5 minutes)
- Added support for sub-agents to escalate user interaction requests from any depth to the parent agents for user interactions
- built-in user interaction tools to remove the need for the list/confirm/etc prompts in prompt tools and to enhance user interactions in Coyote
- built-in user interaction tools to remove the need for the list/confirm/etc prompts in prompt tools and to enhance user interactions in Loki
- Experimental update to sisyphus to use the new parallel agent spawning system
- Added an agent configuration property that allows auto-injecting sub-agent spawning instructions (when using the built-in sub-agent spawning system)
- Auto-dispatch support of sub-agents and support for the teammate pattern between subagents
@@ -540,7 +75,7 @@
- Simplified sisyphus prompt to improve functionality
- Supported the injection of RAG sources into the prompt, not just via the `.sources rag` command in the REPL so models can directly reference the documents that supported their responses
- Created the Sisyphus agent to make Coyote function like Claude Code, Gemini, Codex, etc.
- Created the Sisyphus agent to make Loki function like Claude Code, Gemini, Codex, etc.
- Created the Oracle agent to handle high-level architectural decisions and design questions about a given codebase
- Updated the coder agent to be much more task-focused and to be delegated to by Sisyphus
- Created the explore agent for exploring codebases to help answer questions
@@ -600,8 +135,8 @@
- Support for secret injection into the global config file (API keys, for example)
- Improved MCP handling toggle handling
- Secret injection into the MCP configuration
- added REPL support for interacting with the Coyote vault
- Integrated gman with Coyote to create a vault and added flags to configure the Coyote vault
- added REPL support for interacting with the Loki vault
- Integrated gman with Loki to create a vault and added flags to configure the Loki vault
- Added a default session to the jira helper to make interaction more natural
- Created the repo-analyzer role
- Created the coder and sql agents
CONTRIBUTING.md
+2 -2
View File
@@ -2,7 +2,7 @@
Contributors are very welcome! **No contribution is too small and all contributions are valued.**
## Rust
You'll need to have the stable Rust toolchain installed in order to develop Coyote.
You'll need to have the stable Rust toolchain installed in order to develop Loki.
The Rust toolchain (stable) can be installed via rustup using the following command:
@@ -84,5 +84,5 @@ Claude, etc.) is not permitted unless explicitly disclosed and approved.
Submissions must certify that the contributor understands and can maintain the code they submit.
## Questions? Reach out to me!
If you encounter any questions while developing Coyote, please don't hesitate to reach out to me at
If you encounter any questions while developing Loki, please don't hesitate to reach out to me at
alex.j.tusa@gmail.com. I'm happy to help contributors in any way I can, regardless of if they're new or experienced!
CREDITS.md
+7 -16
View File
@@ -1,19 +1,19 @@
# Credits
## AIChat
Coyote originally started as a fork of the fantastic
Loki originally started as a fork of the fantastic
[AIChat CLI](https://github.com/sigoden/aichat). The initial goal was simply
to fix a bug in how MCP servers worked with AIChat, allowing different MCP
servers to be specified per agent. Since then, Coyote has evolved far beyond
servers to be specified per agent. Since then, Loki has evolved far beyond
its original scope and grown into a passion project with a life of its own.
Today, Coyote includes first-class MCP server support (for both local and remote
Today, Loki includes first-class MCP server support (for both local and remote
servers), a built-in vault for interpolating secrets in configuration files,
built-in agents and macros, dynamic tab completions, integrated custom
functions (no external `argc` dependency), improved documentation, and much
more with many more ideas planned for the future.
Coyote is now developed and maintained as an independent project. Full credit
Loki is now developed and maintained as an independent project. Full credit
for the original foundation goes to the developers of the wonderful
AIChat project.
@@ -21,20 +21,11 @@ This project is not affiliated with or endorsed by the AIChat maintainers.
## AIChat
Coyote originally began as a fork of [AIChat CLI](https://github.com/sigoden/aichat),
Loki originally began as a fork of [AIChat CLI](https://github.com/sigoden/aichat),
created and maintained by the AIChat contributors.
While Coyote has since diverged significantly and is now developed as an
While Loki has since diverged significantly and is now developed as an
independent project, its early foundation and inspiration came from the
AIChat project.
AIChat is licensed under the MIT License. The MIT license text and its
copyright notice are preserved in the [LICENSE-MIT](./LICENSE-MIT) file.
## Licensing
Coyote as a whole is licensed under the GNU Affero General Public License
v3.0 only (AGPL-3.0-only); see [LICENSE](./LICENSE). Substantial portions
derived from AIChat remain under the MIT License (Copyright (c) sigoden),
preserved in [LICENSE-MIT](./LICENSE-MIT). See [NOTICE](./NOTICE) for the
combined-licensing summary.
AIChat is licensed under the MIT License.
Cargo.lock
Generated
+1041 -1888
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File diff suppressed because it is too large Load Diff
Cargo.toml
+25 -29
View File
@@ -1,30 +1,28 @@
[package]
name = "coyote-ai"
version = "0.8.3"
name = "loki-ai"
version = "0.3.0"
edition = "2024"
authors = ["Alex Clarke <alex.j.tusa@gmail.com>"]
description = "An all-in-one, batteries included LLM CLI Tool"
keywords = ["chatgpt", "llm", "cli", "ai", "repl"]
homepage = "https://github.com/Dark-Alex-17/coyote"
repository = "https://github.com/Dark-Alex-17/coyote"
homepage = "https://github.com/Dark-Alex-17/loki"
repository = "https://github.com/Dark-Alex-17/loki"
categories = ["command-line-utilities"]
readme = "README.md"
license = "AGPL-3.0-only"
rust-version = "1.95.0"
license = "MIT"
rust-version = "1.89.0"
exclude = [".github", "CONTRIBUTING.md"]
[dependencies]
anyhow = "1.0.69"
bytes = "1.4.0"
clap = { version = "4.5.40", features = ["cargo", "derive", "wrap_help"] }
comfy-table = { version = "7.1.4", features = ["custom_styling"] }
dirs = "6.0.0"
duckdb = { version = "1.10505.0", features = ["bundled"] }
dunce = "1.0.5"
futures-util = "0.3.29"
inquire = "0.9.4"
is-terminal = "0.4.9"
reedline = "0.47.0"
reedline = "0.46.0"
serde = { version = "1.0.152", features = ["derive"] }
serde_json = { version = "1.0.93", features = ["preserve_order"] }
serde_yaml = "0.9.17"
@@ -36,6 +34,10 @@ tokio = { version = "1.34.0", features = [
"rt-multi-thread",
"full",
] }
tokio-graceful = "0.2.2"
tokio-stream = { version = "0.1.15", default-features = false, features = [
"sync",
] }
crossterm = "0.29.0"
chrono = "0.4.23"
bincode = { version = "2.0.0", features = [
@@ -49,24 +51,28 @@ nu-ansi-term = "0.50.0"
async-trait = "0.1.74"
textwrap = "0.16.0"
ansi_colours = "1.2.2"
eventsource-stream = "0.2.3"
reqwest-eventsource = "0.6.0"
log = "0.4.28"
log4rs = { version = "1.4.0", features = ["file_appender", "rolling_file_appender", "compound_policy", "fixed_window_roller", "size_trigger"] }
log4rs = { version = "1.4.0", features = ["file_appender"] }
shell-words = "1.1.0"
sha2 = "0.10.8"
unicode-width = "0.2.0"
async-recursion = "1.1.1"
http = "1.1.0"
http-body-util = "0.1"
hyper = { version = "1.0", features = ["full"] }
hyper-util = { version = "0.1", features = ["server-auto", "client-legacy"] }
time = { version = "0.3.36", features = ["macros"] }
indexmap = { version = "2.2.6", features = ["serde"] }
hmac = "0.12.1"
aws-smithy-eventstream = "0.60.4"
aws-smithy-types = "=1.4.9"
time = "=0.3.47"
urlencoding = "2.1.3"
unicode-segmentation = "1.11.0"
json-patch = { version = "4.0.0", default-features = false }
bitflags = "2.5.0"
path-absolutize = "3.1.1"
hnsw_rs = "0.3.0"
rayon = "1.10.0"
uuid = { version = "1.9.1", features = ["v4"] }
scraper = { version = "0.23.1", default-features = false, features = [
"deterministic",
@@ -76,7 +82,6 @@ html_to_markdown = "0.1.0"
rust-embed = "8.5.0"
os_info = { version = "3.8.2", default-features = false }
bm25 = { version = "2.0.1", features = ["parallelism"] }
petgraph = { version = "0.7", features = ["serde-1"] }
which = "8.0.0"
fuzzy-matcher = "0.3.7"
terminal-colorsaurus = "0.4.8"
@@ -92,34 +97,25 @@ rmcp = { version = "1.5.0", features = [
] }
num_cpus = "1.17.0"
tree-sitter = "0.26.8"
tree-sitter-language = "0.1"
tree-sitter-python = "0.25.0"
tree-sitter-typescript = "0.23"
colored = "3.0.0"
clap_complete = { version = "4.5.58", features = ["unstable-dynamic"] }
gman = "0.5.0"
gman = "0.4.1"
clap_complete_nushell = "4.5.9"
open = "5"
rand = { version = "0.10.0", features = ["default"] }
url = "2.5.8"
self_update = { version = "0.44", default-features = false, features = [
"reqwest",
"rustls",
"archive-tar",
"compression-flate2",
"archive-zip",
"compression-zip-deflate",
] }
qrcode = "0.14"
[dependencies.reqwest]
version = "0.13.3"
version = "0.12.0"
features = [
"json",
"multipart",
"stream",
"form",
"socks",
"rustls",
"rustls-tls",
"rustls-tls-native-roots",
]
default-features = false
@@ -144,7 +140,7 @@ pretty_assertions = "1.4.0"
serial_test = "3"
[[bin]]
name = "coyote"
name = "loki"
path = "src/main.rs"
[profile.release]
Dockerfile
-95
View File
@@ -1,95 +0,0 @@
ARG COYOTE_VERSION
FROM docker/sandbox-templates:shell-docker AS build
ARG COYOTE_VERSION
ARG TARGETARCH
ENV PATH="/home/agent/.cargo/bin:/home/agent/.local/bin:${PATH}"
USER root
RUN apt-get update && \
apt-get install -y --no-install-recommends \
jq curl git \
build-essential pkg-config \
cmake \
clang libclang-dev \
musl-tools \
libssl-dev \
pandoc \
bzip2 \
nano && \
rm -rf /var/lib/apt/lists/*
RUN set -euo pipefail; \
USQL_VERSION=0.21.4; \
case "${TARGETARCH}" in \
amd64) USQL_ARCH=amd64 ;; \
arm64) USQL_ARCH=arm64 ;; \
*) echo "Unsupported TARGETARCH: ${TARGETARCH}" >&2; exit 1 ;; \
esac; \
TMPDIR=$(mktemp -d); \
curl -fsSL --retry 3 \
"https://github.com/xo/usql/releases/download/v${USQL_VERSION}/usql_static-${USQL_VERSION}-linux-${USQL_ARCH}.tar.bz2" \
-o "$TMPDIR/usql.tar.bz2"; \
tar -xjf "$TMPDIR/usql.tar.bz2" -C "$TMPDIR"; \
install -m 0755 "$TMPDIR/usql_static" /usr/local/bin/usql; \
rm -rf "$TMPDIR"
USER 1000
RUN curl -LsSf https://astral.sh/uv/install.sh | sh && \
printf '#!/bin/sh\nexec uv tool run "$@"\n' > "$HOME/.local/bin/uvx" && \
chmod +x "$HOME/.local/bin/uvx"
RUN mkdir -p /usr/local/share/npm-global/lib
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | \
sh -s -- -y --default-toolchain stable --profile minimal && \
. "$HOME/.cargo/env" && \
cargo install --locked iwec && \
cargo install --locked ast-grep
USER root
RUN set -euo pipefail; \
case "${TARGETARCH}" in \
amd64) MUSL_TARGET=x86_64-unknown-linux-musl ;; \
arm64) MUSL_TARGET=aarch64-unknown-linux-musl ;; \
*) echo "Unsupported TARGETARCH: ${TARGETARCH}" >&2; exit 1 ;; \
esac; \
TMPDIR=$(mktemp -d); \
curl -fsSL --retry 3 \
"https://github.com/Dark-Alex-17/coyote/releases/download/v${COYOTE_VERSION}/coyote-${MUSL_TARGET}.tar.gz" \
-o "$TMPDIR/coyote.tar.gz"; \
tar -xzf "$TMPDIR/coyote.tar.gz" -C "$TMPDIR"; \
install -m 0755 "$TMPDIR/coyote" /home/agent/.cargo/bin/coyote; \
chown 1000:1000 /home/agent/.cargo/bin/coyote; \
rm -rf "$TMPDIR"
FROM scratch
ARG COYOTE_VERSION
COPY --from=build / /
ENV PATH="/home/agent/.cargo/bin:/home/agent/.local/bin:/usr/local/share/npm-global/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin" \
NPM_CONFIG_PREFIX="/usr/local/share/npm-global" \
NO_PROXY="localhost,127.0.0.1,::1,172.17.0.0/16" \
no_proxy="localhost,127.0.0.1,::1,172.17.0.0/16" \
BASH_ENV="/etc/sandbox-persistent.sh"
LABEL com.docker.sandboxes="templates" \
com.docker.sandboxes.base="ubuntu:questing" \
com.docker.sandboxes.flavor="shell-docker" \
com.docker.sandboxes.start-docker="true" \
org.opencontainers.image.title="coyote" \
org.opencontainers.image.description="An all-in-one, batteries-included LLM CLI tool: Shell Assistant, CLI & REPL mode, RAG, AI tools & agents, MCP servers, skills, and macros." \
org.opencontainers.image.source="https://github.com/Dark-Alex-17/coyote" \
org.opencontainers.image.version="${COYOTE_VERSION}"
WORKDIR /home/agent/workspace
USER 1000
ENTRYPOINT ["coyote"]
LICENSE
+22 -661
View File
@@ -1,661 +1,22 @@
GNU AFFERO GENERAL PUBLIC LICENSE
Version 3, 19 November 2007
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
Everyone is permitted to copy and distribute verbatim copies
of this license document, but changing it is not allowed.
Preamble
The GNU Affero General Public License is a free, copyleft license for
software and other kinds of works, specifically designed to ensure
cooperation with the community in the case of network server software.
The licenses for most software and other practical works are designed
to take away your freedom to share and change the works. By contrast,
our General Public Licenses are intended to guarantee your freedom to
share and change all versions of a program--to make sure it remains free
software for all its users.
When we speak of free software, we are referring to freedom, not
price. Our General Public Licenses are designed to make sure that you
have the freedom to distribute copies of free software (and charge for
them if you wish), that you receive source code or can get it if you
want it, that you can change the software or use pieces of it in new
free programs, and that you know you can do these things.
Developers that use our General Public Licenses protect your rights
with two steps: (1) assert copyright on the software, and (2) offer
you this License which gives you legal permission to copy, distribute
and/or modify the software.
A secondary benefit of defending all users' freedom is that
improvements made in alternate versions of the program, if they
receive widespread use, become available for other developers to
incorporate. Many developers of free software are heartened and
encouraged by the resulting cooperation. However, in the case of
software used on network servers, this result may fail to come about.
The GNU General Public License permits making a modified version and
letting the public access it on a server without ever releasing its
source code to the public.
The GNU Affero General Public License is designed specifically to
ensure that, in such cases, the modified source code becomes available
to the community. It requires the operator of a network server to
provide the source code of the modified version running there to the
users of that server. Therefore, public use of a modified version, on
a publicly accessible server, gives the public access to the source
code of the modified version.
An older license, called the Affero General Public License and
published by Affero, was designed to accomplish similar goals. This is
a different license, not a version of the Affero GPL, but Affero has
released a new version of the Affero GPL which permits relicensing under
this license.
The precise terms and conditions for copying, distribution and
modification follow.
TERMS AND CONDITIONS
0. Definitions.
"This License" refers to version 3 of the GNU Affero General Public License.
"Copyright" also means copyright-like laws that apply to other kinds of
works, such as semiconductor masks.
"The Program" refers to any copyrightable work licensed under this
License. Each licensee is addressed as "you". "Licensees" and
"recipients" may be individuals or organizations.
To "modify" a work means to copy from or adapt all or part of the work
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exact copy. The resulting work is called a "modified version" of the
earlier work or a work "based on" the earlier work.
A "covered work" means either the unmodified Program or a work based
on the Program.
To "propagate" a work means to do anything with it that, without
permission, would make you directly or secondarily liable for
infringement under applicable copyright law, except executing it on a
computer or modifying a private copy. Propagation includes copying,
distribution (with or without modification), making available to the
public, and in some countries other activities as well.
To "convey" a work means any kind of propagation that enables other
parties to make or receive copies. Mere interaction with a user through
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An interactive user interface displays "Appropriate Legal Notices"
to the extent that it includes a convenient and prominently visible
feature that (1) displays an appropriate copyright notice, and (2)
tells the user that there is no warranty for the work (except to the
extent that warranties are provided), that licensees may convey the
work under this License, and how to view a copy of this License. If
the interface presents a list of user commands or options, such as a
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1. Source Code.
The "source code" for a work means the preferred form of the work
for making modifications to it. "Object code" means any non-source
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A "Standard Interface" means an interface that either is an official
standard defined by a recognized standards body, or, in the case of
interfaces specified for a particular programming language, one that
is widely used among developers working in that language.
The "System Libraries" of an executable work include anything, other
than the work as a whole, that (a) is included in the normal form of
packaging a Major Component, but which is not part of that Major
Component, and (b) serves only to enable use of the work with that
Major Component, or to implement a Standard Interface for which an
implementation is available to the public in source code form. A
"Major Component", in this context, means a major essential component
(kernel, window system, and so on) of the specific operating system
(if any) on which the executable work runs, or a compiler used to
produce the work, or an object code interpreter used to run it.
The "Corresponding Source" for a work in object code form means all
the source code needed to generate, install, and (for an executable
work) run the object code and to modify the work, including scripts to
control those activities. However, it does not include the work's
System Libraries, or general-purpose tools or generally available free
programs which are used unmodified in performing those activities but
which are not part of the work. For example, Corresponding Source
includes interface definition files associated with source files for
the work, and the source code for shared libraries and dynamically
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such as by intimate data communication or control flow between those
subprograms and other parts of the work.
The Corresponding Source need not include anything that users
can regenerate automatically from other parts of the Corresponding
Source.
The Corresponding Source for a work in source code form is that
same work.
2. Basic Permissions.
All rights granted under this License are granted for the term of
copyright on the Program, and are irrevocable provided the stated
conditions are met. This License explicitly affirms your unlimited
permission to run the unmodified Program. The output from running a
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content, constitutes a covered work. This License acknowledges your
rights of fair use or other equivalent, as provided by copyright law.
You may make, run and propagate covered works that you do not
convey, without conditions so long as your license otherwise remains
in force. You may convey covered works to others for the sole purpose
of having them make modifications exclusively for you, or provide you
with facilities for running those works, provided that you comply with
the terms of this License in conveying all material for which you do
not control copyright. Those thus making or running the covered works
for you must do so exclusively on your behalf, under your direction
and control, on terms that prohibit them from making any copies of
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Conveying under any other circumstances is permitted solely under
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3. Protecting Users' Legal Rights From Anti-Circumvention Law.
No covered work shall be deemed part of an effective technological
measure under any applicable law fulfilling obligations under article
11 of the WIPO copyright treaty adopted on 20 December 1996, or
similar laws prohibiting or restricting circumvention of such
measures.
When you convey a covered work, you waive any legal power to forbid
circumvention of technological measures to the extent such circumvention
is effected by exercising rights under this License with respect to
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modification of the work as a means of enforcing, against the work's
users, your or third parties' legal rights to forbid circumvention of
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4. Conveying Verbatim Copies.
You may convey verbatim copies of the Program's source code as you
receive it, in any medium, provided that you conspicuously and
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keep intact all notices of the absence of any warranty; and give all
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You may charge any price or no price for each copy that you convey,
and you may offer support or warranty protection for a fee.
5. Conveying Modified Source Versions.
You may convey a work based on the Program, or the modifications to
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terms of section 4, provided that you also meet all of these conditions:
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it, and giving a relevant date.
b) The work must carry prominent notices stating that it is
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7. This requirement modifies the requirement in section 4 to
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License to anyone who comes into possession of a copy. This
License will therefore apply, along with any applicable section 7
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work need not make them do so.
A compilation of a covered work with other separate and independent
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in or on a volume of a storage or distribution medium, is called an
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used to limit the access or legal rights of the compilation's users
beyond what the individual works permit. Inclusion of a covered work
in an aggregate does not cause this License to apply to the other
parts of the aggregate.
6. Conveying Non-Source Forms.
You may convey a covered work in object code form under the terms
of sections 4 and 5, provided that you also convey the
machine-readable Corresponding Source under the terms of this License,
in one of these ways:
a) Convey the object code in, or embodied in, a physical product
(including a physical distribution medium), accompanied by the
Corresponding Source fixed on a durable physical medium
customarily used for software interchange.
b) Convey the object code in, or embodied in, a physical product
(including a physical distribution medium), accompanied by a
written offer, valid for at least three years and valid for as
long as you offer spare parts or customer support for that product
model, to give anyone who possesses the object code either (1) a
copy of the Corresponding Source for all the software in the
product that is covered by this License, on a durable physical
medium customarily used for software interchange, for a price no
more than your reasonable cost of physically performing this
conveying of source, or (2) access to copy the
Corresponding Source from a network server at no charge.
c) Convey individual copies of the object code with a copy of the
written offer to provide the Corresponding Source. This
alternative is allowed only occasionally and noncommercially, and
only if you received the object code with such an offer, in accord
with subsection 6b.
d) Convey the object code by offering access from a designated
place (gratis or for a charge), and offer equivalent access to the
Corresponding Source in the same way through the same place at no
further charge. You need not require recipients to copy the
Corresponding Source along with the object code. If the place to
copy the object code is a network server, the Corresponding Source
may be on a different server (operated by you or a third party)
that supports equivalent copying facilities, provided you maintain
clear directions next to the object code saying where to find the
Corresponding Source. Regardless of what server hosts the
Corresponding Source, you remain obligated to ensure that it is
available for as long as needed to satisfy these requirements.
e) Convey the object code using peer-to-peer transmission, provided
you inform other peers where the object code and Corresponding
Source of the work are being offered to the general public at no
charge under subsection 6d.
A separable portion of the object code, whose source code is excluded
from the Corresponding Source as a System Library, need not be
included in conveying the object code work.
A "User Product" is either (1) a "consumer product", which means any
tangible personal property which is normally used for personal, family,
or household purposes, or (2) anything designed or sold for incorporation
into a dwelling. In determining whether a product is a consumer product,
doubtful cases shall be resolved in favor of coverage. For a particular
product received by a particular user, "normally used" refers to a
typical or common use of that class of product, regardless of the status
of the particular user or of the way in which the particular user
actually uses, or expects or is expected to use, the product. A product
is a consumer product regardless of whether the product has substantial
commercial, industrial or non-consumer uses, unless such uses represent
the only significant mode of use of the product.
"Installation Information" for a User Product means any methods,
procedures, authorization keys, or other information required to install
and execute modified versions of a covered work in that User Product from
a modified version of its Corresponding Source. The information must
suffice to ensure that the continued functioning of the modified object
code is in no case prevented or interfered with solely because
modification has been made.
If you convey an object code work under this section in, or with, or
specifically for use in, a User Product, and the conveying occurs as
part of a transaction in which the right of possession and use of the
User Product is transferred to the recipient in perpetuity or for a
fixed term (regardless of how the transaction is characterized), the
Corresponding Source conveyed under this section must be accompanied
by the Installation Information. But this requirement does not apply
if neither you nor any third party retains the ability to install
modified object code on the User Product (for example, the work has
been installed in ROM).
The requirement to provide Installation Information does not include a
requirement to continue to provide support service, warranty, or updates
for a work that has been modified or installed by the recipient, or for
the User Product in which it has been modified or installed. Access to a
network may be denied when the modification itself materially and
adversely affects the operation of the network or violates the rules and
protocols for communication across the network.
Corresponding Source conveyed, and Installation Information provided,
in accord with this section must be in a format that is publicly
documented (and with an implementation available to the public in
source code form), and must require no special password or key for
unpacking, reading or copying.
7. Additional Terms.
"Additional permissions" are terms that supplement the terms of this
License by making exceptions from one or more of its conditions.
Additional permissions that are applicable to the entire Program shall
be treated as though they were included in this License, to the extent
that they are valid under applicable law. If additional permissions
apply only to part of the Program, that part may be used separately
under those permissions, but the entire Program remains governed by
this License without regard to the additional permissions.
When you convey a copy of a covered work, you may at your option
remove any additional permissions from that copy, or from any part of
it. (Additional permissions may be written to require their own
removal in certain cases when you modify the work.) You may place
additional permissions on material, added by you to a covered work,
for which you have or can give appropriate copyright permission.
Notwithstanding any other provision of this License, for material you
add to a covered work, you may (if authorized by the copyright holders of
that material) supplement the terms of this License with terms:
a) Disclaiming warranty or limiting liability differently from the
terms of sections 15 and 16 of this License; or
b) Requiring preservation of specified reasonable legal notices or
author attributions in that material or in the Appropriate Legal
Notices displayed by works containing it; or
c) Prohibiting misrepresentation of the origin of that material, or
requiring that modified versions of such material be marked in
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trade names, trademarks, or service marks; or
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it) with contractual assumptions of liability to the recipient, for
any liability that these contractual assumptions directly impose on
those licensors and authors.
All other non-permissive additional terms are considered "further
restrictions" within the meaning of section 10. If the Program as you
received it, or any part of it, contains a notice stating that it is
governed by this License along with a term that is a further
restriction, you may remove that term. If a license document contains
a further restriction but permits relicensing or conveying under this
License, you may add to a covered work material governed by the terms
of that license document, provided that the further restriction does
not survive such relicensing or conveying.
If you add terms to a covered work in accord with this section, you
must place, in the relevant source files, a statement of the
additional terms that apply to those files, or a notice indicating
where to find the applicable terms.
Additional terms, permissive or non-permissive, may be stated in the
form of a separately written license, or stated as exceptions;
the above requirements apply either way.
8. Termination.
You may not propagate or modify a covered work except as expressly
provided under this License. Any attempt otherwise to propagate or
modify it is void, and will automatically terminate your rights under
this License (including any patent licenses granted under the third
paragraph of section 11).
However, if you cease all violation of this License, then your
license from a particular copyright holder is reinstated (a)
provisionally, unless and until the copyright holder explicitly and
finally terminates your license, and (b) permanently, if the copyright
holder fails to notify you of the violation by some reasonable means
prior to 60 days after the cessation.
Moreover, your license from a particular copyright holder is
reinstated permanently if the copyright holder notifies you of the
violation by some reasonable means, this is the first time you have
received notice of violation of this License (for any work) from that
copyright holder, and you cure the violation prior to 30 days after
your receipt of the notice.
Termination of your rights under this section does not terminate the
licenses of parties who have received copies or rights from you under
this License. If your rights have been terminated and not permanently
reinstated, you do not qualify to receive new licenses for the same
material under section 10.
9. Acceptance Not Required for Having Copies.
You are not required to accept this License in order to receive or
run a copy of the Program. Ancillary propagation of a covered work
occurring solely as a consequence of using peer-to-peer transmission
to receive a copy likewise does not require acceptance. However,
nothing other than this License grants you permission to propagate or
modify any covered work. These actions infringe copyright if you do
not accept this License. Therefore, by modifying or propagating a
covered work, you indicate your acceptance of this License to do so.
10. Automatic Licensing of Downstream Recipients.
Each time you convey a covered work, the recipient automatically
receives a license from the original licensors, to run, modify and
propagate that work, subject to this License. You are not responsible
for enforcing compliance by third parties with this License.
An "entity transaction" is a transaction transferring control of an
organization, or substantially all assets of one, or subdividing an
organization, or merging organizations. If propagation of a covered
work results from an entity transaction, each party to that
transaction who receives a copy of the work also receives whatever
licenses to the work the party's predecessor in interest had or could
give under the previous paragraph, plus a right to possession of the
Corresponding Source of the work from the predecessor in interest, if
the predecessor has it or can get it with reasonable efforts.
You may not impose any further restrictions on the exercise of the
rights granted or affirmed under this License. For example, you may
not impose a license fee, royalty, or other charge for exercise of
rights granted under this License, and you may not initiate litigation
(including a cross-claim or counterclaim in a lawsuit) alleging that
any patent claim is infringed by making, using, selling, offering for
sale, or importing the Program or any portion of it.
11. Patents.
A "contributor" is a copyright holder who authorizes use under this
License of the Program or a work on which the Program is based. The
work thus licensed is called the contributor's "contributor version".
A contributor's "essential patent claims" are all patent claims
owned or controlled by the contributor, whether already acquired or
hereafter acquired, that would be infringed by some manner, permitted
by this License, of making, using, or selling its contributor version,
but do not include claims that would be infringed only as a
consequence of further modification of the contributor version. For
purposes of this definition, "control" includes the right to grant
patent sublicenses in a manner consistent with the requirements of
this License.
Each contributor grants you a non-exclusive, worldwide, royalty-free
patent license under the contributor's essential patent claims, to
make, use, sell, offer for sale, import and otherwise run, modify and
propagate the contents of its contributor version.
In the following three paragraphs, a "patent license" is any express
agreement or commitment, however denominated, not to enforce a patent
(such as an express permission to practice a patent or covenant not to
sue for patent infringement). To "grant" such a patent license to a
party means to make such an agreement or commitment not to enforce a
patent against the party.
If you convey a covered work, knowingly relying on a patent license,
and the Corresponding Source of the work is not available for anyone
to copy, free of charge and under the terms of this License, through a
publicly available network server or other readily accessible means,
then you must either (1) cause the Corresponding Source to be so
available, or (2) arrange to deprive yourself of the benefit of the
patent license for this particular work, or (3) arrange, in a manner
consistent with the requirements of this License, to extend the patent
license to downstream recipients. "Knowingly relying" means you have
actual knowledge that, but for the patent license, your conveying the
covered work in a country, or your recipient's use of the covered work
in a country, would infringe one or more identifiable patents in that
country that you have reason to believe are valid.
If, pursuant to or in connection with a single transaction or
arrangement, you convey, or propagate by procuring conveyance of, a
covered work, and grant a patent license to some of the parties
receiving the covered work authorizing them to use, propagate, modify
or convey a specific copy of the covered work, then the patent license
you grant is automatically extended to all recipients of the covered
work and works based on it.
A patent license is "discriminatory" if it does not include within
the scope of its coverage, prohibits the exercise of, or is
conditioned on the non-exercise of one or more of the rights that are
specifically granted under this License. You may not convey a covered
work if you are a party to an arrangement with a third party that is
in the business of distributing software, under which you make payment
to the third party based on the extent of your activity of conveying
the work, and under which the third party grants, to any of the
parties who would receive the covered work from you, a discriminatory
patent license (a) in connection with copies of the covered work
conveyed by you (or copies made from those copies), or (b) primarily
for and in connection with specific products or compilations that
contain the covered work, unless you entered into that arrangement,
or that patent license was granted, prior to 28 March 2007.
Nothing in this License shall be construed as excluding or limiting
any implied license or other defenses to infringement that may
otherwise be available to you under applicable patent law.
12. No Surrender of Others' Freedom.
If conditions are imposed on you (whether by court order, agreement or
otherwise) that contradict the conditions of this License, they do not
excuse you from the conditions of this License. If you cannot convey a
covered work so as to satisfy simultaneously your obligations under this
License and any other pertinent obligations, then as a consequence you may
not convey it at all. For example, if you agree to terms that obligate you
to collect a royalty for further conveying from those to whom you convey
the Program, the only way you could satisfy both those terms and this
License would be to refrain entirely from conveying the Program.
13. Remote Network Interaction; Use with the GNU General Public License.
Notwithstanding any other provision of this License, if you modify the
Program, your modified version must prominently offer all users
interacting with it remotely through a computer network (if your version
supports such interaction) an opportunity to receive the Corresponding
Source of your version by providing access to the Corresponding Source
from a network server at no charge, through some standard or customary
means of facilitating copying of software. This Corresponding Source
shall include the Corresponding Source for any work covered by version 3
of the GNU General Public License that is incorporated pursuant to the
following paragraph.
Notwithstanding any other provision of this License, you have
permission to link or combine any covered work with a work licensed
under version 3 of the GNU General Public License into a single
combined work, and to convey the resulting work. The terms of this
License will continue to apply to the part which is the covered work,
but the work with which it is combined will remain governed by version
3 of the GNU General Public License.
14. Revised Versions of this License.
The Free Software Foundation may publish revised and/or new versions of
the GNU Affero General Public License from time to time. Such new versions
will be similar in spirit to the present version, but may differ in detail to
address new problems or concerns.
Each version is given a distinguishing version number. If the
Program specifies that a certain numbered version of the GNU Affero General
Public License "or any later version" applies to it, you have the
option of following the terms and conditions either of that numbered
version or of any later version published by the Free Software
Foundation. If the Program does not specify a version number of the
GNU Affero General Public License, you may choose any version ever published
by the Free Software Foundation.
If the Program specifies that a proxy can decide which future
versions of the GNU Affero General Public License can be used, that proxy's
public statement of acceptance of a version permanently authorizes you
to choose that version for the Program.
Later license versions may give you additional or different
permissions. However, no additional obligations are imposed on any
author or copyright holder as a result of your choosing to follow a
later version.
15. Disclaimer of Warranty.
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
16. Limitation of Liability.
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
SUCH DAMAGES.
17. Interpretation of Sections 15 and 16.
If the disclaimer of warranty and limitation of liability provided
above cannot be given local legal effect according to their terms,
reviewing courts shall apply local law that most closely approximates
an absolute waiver of all civil liability in connection with the
Program, unless a warranty or assumption of liability accompanies a
copy of the Program in return for a fee.
END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
state the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU Affero General Public License for more details.
You should have received a copy of the GNU Affero General Public License
along with this program. If not, see <https://www.gnu.org/licenses/>.
Also add information on how to contact you by electronic and paper mail.
If your software can interact with users remotely through a computer
network, you should also make sure that it provides a way for users to
get its source. For example, if your program is a web application, its
interface could display a "Source" link that leads users to an archive
of the code. There are many ways you could offer source, and different
solutions will be better for different programs; see section 13 for the
specific requirements.
You should also get your employer (if you work as a programmer) or school,
if any, to sign a "copyright disclaimer" for the program, if necessary.
For more information on this, and how to apply and follow the GNU AGPL, see
<https://www.gnu.org/licenses/>.
The MIT License (MIT)
Copyright (c) 2025 sigoden
Copyright (c) 2025 Alexander J. Clarke
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
LICENSE-MIT
-22
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@@ -1,22 +0,0 @@
The MIT License (MIT)
Copyright (c) 2025 sigoden
Copyright (c) 2025 Alexander J. Clarke
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
NOTICE
-24
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Coyote
Copyright (c) 2025 Alexander J. Clarke
This project as a whole is licensed under the GNU Affero General Public
License, version 3.0 only (AGPL-3.0-only). The full text of that license is
provided in the LICENSE file.
--------------------------------------------------------------------------------
Upstream / third-party notices
--------------------------------------------------------------------------------
Coyote began as a fork of AIChat (https://github.com/sigoden/aichat),
Copyright (c) sigoden, which is distributed under the MIT License. Substantial
portions of Coyote are derived from AIChat and remain available under the terms
of the MIT License. The MIT License text and its required copyright and
permission notices are preserved in the LICENSE-MIT file.
As permitted by the MIT License, these portions have been incorporated into a
larger work that is distributed under the AGPL-3.0-only license. When you
receive Coyote as a combined work, your rights and obligations for the work as
a whole are governed by the AGPL-3.0-only license; the MIT notice is retained
to satisfy the attribution requirements of the MIT-licensed portions.
See CREDITS.md for additional background and attribution.
README.md
+95 -163
View File
@@ -1,153 +1,121 @@
# Coyote: All-in-one, batteries-included LLM CLI Tool
# Loki: All-in-one, batteries-included LLM CLI Tool
![Test](https://github.com/Dark-Alex-17/coyote/actions/workflows/ci.yaml/badge.svg)
[![crates.io link](https://img.shields.io/crates/v/coyote-ai.svg)](https://crates.io/crates/coyote-ai)
![Release](https://img.shields.io/github/v/release/Dark-Alex-17/coyote?color=%23c694ff)
![Crate.io downloads](https://img.shields.io/crates/d/coyote-ai?label=Crate%20downloads)
[![GitHub Downloads](https://img.shields.io/github/downloads/Dark-Alex-17/coyote/total.svg?label=GitHub%20downloads)](https://github.com/Dark-Alex-17/coyote/releases)
![Docker pulls](https://img.shields.io/docker/pulls/darkalex17/coyote?label=Docker%20downloads)
[![License: AGPL v3](https://img.shields.io/badge/License-AGPL_v3-blue.svg)](./LICENSE)
![Test](https://github.com/Dark-Alex-17/loki/actions/workflows/ci.yaml/badge.svg)
![LOC](https://tokei.rs/b1/github/Dark-Alex-17/loki?category=code)
[![crates.io link](https://img.shields.io/crates/v/loki-ai.svg)](https://crates.io/crates/loki-ai)
![Release](https://img.shields.io/github/v/release/Dark-Alex-17/loki?color=%23c694ff)
![Crate.io downloads](https://img.shields.io/crates/d/loki-ai?label=Crate%20downloads)
[![GitHub Downloads](https://img.shields.io/github/downloads/Dark-Alex-17/loki/total.svg?label=GitHub%20downloads)](https://github.com/Dark-Alex-17/loki/releases)
Coyote is an all-in-one, batteries-included, LLM CLI tool featuring Shell Assistant, CLI & REPL Mode, RAG, AI Tools &
Loki is an all-in-one, batteries-included, LLM CLI tool featuring Shell Assistant, CLI & REPL Mode, RAG, AI Tools &
Agents, and More.
It is designed to include a number of useful agents, roles, macros, and more so users can get up and running with Coyote
in as little time as possible. You can also install entire bundles of agents, roles, macros, tools, and MCP servers from
any git repository. See [Sharing Configurations](https://github.com/Dark-Alex-17/coyote/wiki/Sharing-Configurations) for more information.
It is designed to include a number of useful agents, roles, macros, and more so users can get up and running with Loki
in as little time as possible.
![Agent example](https://raw.githubusercontent.com/wiki/Dark-Alex-17/coyote/images/agents/sql.gif)
![Agent example](./docs/images/agents/sql.gif)
Coming from [AIChat](https://github.com/sigoden/aichat)? Follow the [migration guide](https://github.com/Dark-Alex-17/coyote/wiki/AIChat-Migration) to get started.
Coming from [AIChat](https://github.com/sigoden/aichat)? Follow the [migration guide](./docs/AICHAT-MIGRATION.md) to get started.
## Quick Links
* [AIChat Migration Guide](https://github.com/Dark-Alex-17/coyote/wiki/AIChat-Migration): Coming from AIChat? Follow the migration guide to get started.
* [Installation](#install): Install Coyote
* [Getting Started](#getting-started): Get started with Coyote by doing first-run setup steps.
* [Sharing Configurations](https://github.com/Dark-Alex-17/coyote/wiki/Sharing-Configurations): Install bundles of agents, roles, macros, tools, and MCP servers from any git repo, and share your own.
* [REPL](https://github.com/Dark-Alex-17/coyote/wiki/REPL): Interactive Read-Eval-Print Loop for conversational interactions with LLMs and Coyote.
* [Custom REPL Prompt](https://github.com/Dark-Alex-17/coyote/wiki/REPL-Prompt): Customize the REPL prompt to provide useful contextual information.
* [Vault](https://github.com/Dark-Alex-17/coyote/wiki/Vault): Securely store and manage sensitive information such as API keys and credentials.
* [Sandboxes](https://github.com/Dark-Alex-17/coyote/wiki/Sandboxes): Launch Coyote inside an isolated [Docker Sandbox](https://docs.docker.com/ai/sandboxes/) with one command. Host config and vault credentials are projected in automatically; everything else is delegated to the `sbx` CLI.
* [Shell Integrations](https://github.com/Dark-Alex-17/coyote/wiki/Shell-Integrations): Seamlessly integrate Coyote with your shell environment for enhanced command-line assistance.
* [Function Calling](https://github.com/Dark-Alex-17/coyote/wiki/Tools): Leverage function calling capabilities to extend Coyote's functionality with custom tools
* [Creating Custom Tools](https://github.com/Dark-Alex-17/coyote/wiki/Custom-Tools): You can create your own custom tools to enhance Coyote's capabilities.
* [Create Custom Python Tools](https://github.com/Dark-Alex-17/coyote/wiki/Custom-Tools#custom-python-based-tools)
* [Create Custom TypeScript Tools](https://github.com/Dark-Alex-17/coyote/wiki/Custom-Tools#custom-typescript-based-tools)
* [Create Custom Bash Tools](https://github.com/Dark-Alex-17/coyote/wiki/Custom-Bash-Tools)
* [Bash Prompt Utilities](https://github.com/Dark-Alex-17/coyote/wiki/Bash-Prompt-Helpers)
* [First-Class MCP Server Support](https://github.com/Dark-Alex-17/coyote/wiki/MCP-Servers): Easily connect and interact with MCP servers for advanced functionality.
* [Macros](https://github.com/Dark-Alex-17/coyote/wiki/Macros): Automate repetitive tasks and workflows with Coyote "scripts" (macros).
* [RAG](https://github.com/Dark-Alex-17/coyote/wiki/RAG): Retrieval-Augmented Generation for enhanced information retrieval and generation.
* [Sessions](https://github.com/Dark-Alex-17/coyote/wiki/Sessions): Manage and persist conversational contexts and settings across multiple interactions.
* [Memory](https://github.com/Dark-Alex-17/coyote/wiki/Memory): Persistent file-based memory that survives across sessions. Bootstrap with `coyote --init-memory [global|workspace]`.
* [Workspace Instructions](https://github.com/Dark-Alex-17/coyote/wiki/Workspace-Instructions): Human-curated project instructions (`COYOTE.md`) injected into every prompt, with `AGENTS.md`/`CLAUDE.md`/`GEMINI.md` fallbacks for cross-tool compatibility. Scaffold with `coyote --init-instructions`.
* [Roles](https://github.com/Dark-Alex-17/coyote/wiki/Roles): Customize model behavior for specific tasks or domains.
* [Skills](https://github.com/Dark-Alex-17/coyote/wiki/Skills): Modular knowledge or capability packs the LLM can load and unload mid-conversation. Multiple skills compose; instructions stack, tools and MCPs union.
* [Agents](https://github.com/Dark-Alex-17/coyote/wiki/Agents): Leverage AI agents to perform complex tasks and workflows, including sub-agent spawning, teammate messaging, and user interaction tools.
* [Graph Agents](https://github.com/Dark-Alex-17/coyote/wiki/Graph-Agents): Define an agent as a declarative, YAML-driven workflow. A directed graph of typed nodes (LLM calls, scripts, approvals, user input, RAG retrieval, sub-agent spawns).
* [Todo System](https://github.com/Dark-Alex-17/coyote/wiki/TODO-System): Built-in task tracking for improved LLM reliability with smaller models.
* [Environment Variables](https://github.com/Dark-Alex-17/coyote/wiki/Environment-Variables): Override and customize your Coyote configuration at runtime with environment variables.
* [Client Configurations](https://github.com/Dark-Alex-17/coyote/wiki/Clients): Configuration instructions for various LLM providers.
* [Authentication (API Key & OAuth)](https://github.com/Dark-Alex-17/coyote/wiki/Clients#authentication): Authenticate with API keys or OAuth for subscription-based access.
* [Patching API Requests](https://github.com/Dark-Alex-17/coyote/wiki/Patches): Learn how to patch API requests for advanced customization.
* [Custom Themes](https://github.com/Dark-Alex-17/coyote/wiki/Themes): Change the look and feel of Coyote to your preferences with custom themes.
* [History](#history): A history of how Coyote came to be.
* [AIChat Migration Guide](./docs/AICHAT-MIGRATION.md): Coming from AIChat? Follow the migration guide to get started.
* [Installation](#install): Install Loki
* [Getting Started](#getting-started): Get started with Loki by doing first-run setup steps.
* [REPL](./docs/REPL.md): Interactive Read-Eval-Print Loop for conversational interactions with LLMs and Loki.
* [Custom REPL Prompt](./docs/REPL-PROMPT.md): Customize the REPL prompt to provide useful contextual information.
* [Vault](./docs/VAULT.md): Securely store and manage sensitive information such as API keys and credentials.
* [Shell Integrations](./docs/SHELL-INTEGRATIONS.md): Seamlessly integrate Loki with your shell environment for enhanced command-line assistance.
* [Function Calling](./docs/function-calling/TOOLS.md#Tools): Leverage function calling capabilities to extend Loki's functionality with custom tools
* [Creating Custom Tools](./docs/function-calling/CUSTOM-TOOLS.md): You can create your own custom tools to enhance Loki's capabilities.
* [Create Custom Python Tools](./docs/function-calling/CUSTOM-TOOLS.md#custom-python-based-tools)
* [Create Custom TypeScript Tools](./docs/function-calling/CUSTOM-TOOLS.md#custom-typescript-based-tools)
* [Create Custom Bash Tools](./docs/function-calling/CUSTOM-BASH-TOOLS.md)
* [Bash Prompt Utilities](./docs/function-calling/BASH-PROMPT-HELPERS.md)
* [First-Class MCP Server Support](./docs/function-calling/MCP-SERVERS.md): Easily connect and interact with MCP servers for advanced functionality.
* [Macros](./docs/MACROS.md): Automate repetitive tasks and workflows with Loki "scripts" (macros).
* [RAG](./docs/RAG.md): Retrieval-Augmented Generation for enhanced information retrieval and generation.
* [Sessions](/docs/SESSIONS.md): Manage and persist conversational contexts and settings across multiple interactions.
* [Roles](./docs/ROLES.md): Customize model behavior for specific tasks or domains.
* [Agents](/docs/AGENTS.md): Leverage AI agents to perform complex tasks and workflows, including sub-agent spawning, teammate messaging, and user interaction tools.
* [Todo System](./docs/TODO-SYSTEM.md): Built-in task tracking for improved agent reliability with smaller models.
* [Environment Variables](./docs/ENVIRONMENT-VARIABLES.md): Override and customize your Loki configuration at runtime with environment variables.
* [Client Configurations](./docs/clients/CLIENTS.md): Configuration instructions for various LLM providers.
* [Authentication (API Key & OAuth)](./docs/clients/CLIENTS.md#authentication): Authenticate with API keys or OAuth for subscription-based access.
* [Patching API Requests](./docs/clients/PATCHES.md): Learn how to patch API requests for advanced customization.
* [Custom Themes](./docs/THEMES.md): Change the look and feel of Loki to your preferences with custom themes.
* [History](#history): A history of how Loki came to be.
## Prerequisites
Coyote requires the following tools to be installed on your system:
Loki requires the following tools to be installed on your system:
* [jq](https://github.com/jqlang/jq)
* `brew install jq`
* [jira (optional)](https://github.com/ankitpokhrel/jira-cli/wiki/Installation) (For the `query_jira_issues` tool)
* `brew tap ankitpokhrel/jira-cli && brew install jira-cli`
* You'll need to [create a JIRA API token](https://id.atlassian.com/manage-profile/security/api-tokens) for authentication
* Then, save it as an environment variable to your shell profile:
```sh
# ~/.bashrc or ~/.zshrc
export JIRA_API_TOKEN="your_jira_api_token_here"
```
* Then run `jira init`, select installation type as `cloud`, and provide the required details to generate a config
file for the Jira CLI.
* [usql](https://github.com/xo/usql) (For the `sql` agent)
* `brew install xo/xo/usql`
* [docker](https://docs.docker.com/engine/install/)
* [uv](https://docs.astral.sh/uv/getting-started/installation/)
* `curl -LsSf https://astral.sh/uv/install.sh | sh`
* [iwe](https://github.com/iwe-org/iwe) (`iwec`, for the built-in `iwe` MCP server that navigates large markdown knowledgebases)
* **Homebrew:** `brew tap iwe-org/iwe && brew trust --formula iwe-org/iwe/iwe && brew install iwe`
* **Cargo:** `cargo install iwec`
* [ast-grep](https://ast-grep.github.io/) (for the built-in `ast_grep` structural code search tool, used by the `explore` agent)
* **Homebrew:** `brew install ast-grep`
* **Cargo:** `cargo install ast-grep --locked`
* **npm:** `npm i -g @ast-grep/cli`
* Optional: if `ast-grep` is not installed, the `ast_grep` tool reports it and agents fall back to `fs_grep`
These tools are used to provide various functionalities within Coyote, such as document processing, JSON manipulation,
etc., and they are used within agents and tools.
These tools are used to provide various functionalities within Loki, such as document processing, JSON manipulation,
interaction with Jira, and they are used within agents and tools.
## Install
### Cargo
If you have Cargo installed, then you can install `coyote` from Crates.io:
If you have Cargo installed, then you can install `loki` from Crates.io:
```shell
cargo install coyote-ai # Binary name is `coyote`
cargo install loki-ai # Binary name is `loki`
# If you encounter issues installing, try installing with '--locked'
cargo install --locked coyote-ai
cargo install --locked loki-ai
```
### Homebrew (Mac/Linux)
To install Coyote from Homebrew, install the `coyote` tap. Then you'll be able to install `coyote`:
To install Loki from Homebrew, install the `loki` tap. Then you'll be able to install `loki`:
```shell
brew tap Dark-Alex-17/coyote
brew install coyote
brew tap Dark-Alex-17/loki
brew install loki
# If you need to be more specific, use:
brew install Dark-Alex-17/coyote/coyote
brew install Dark-Alex-17/loki/loki
```
To upgrade `coyote` using Homebrew:
To upgrade `loki` using Homebrew:
```shell
brew upgrade coyote
```
### Docker
Coyote is available as a Docker image on Docker Hub (`darkalex17/coyote`) for Linux amd64 and arm64.
Useful for CI, ephemeral environments, or anywhere you prefer not to install it natively.
```bash
docker pull darkalex17/coyote
docker run --rm -it darkalex17/coyote
```
To persist your configuration across container runs, mount your existing config directory:
```bash
docker run --rm -it \
-v ~/.config/coyote:/home/agent/.config/coyote \
darkalex17/coyote
```
If you use the local vault provider and want your vault credentials available in the container, also mount the password file:
```bash
docker run --rm -it \
-v ~/.config/coyote:/home/agent/.config/coyote \
-v ~/.coyote_password:/home/agent/.coyote_password:ro \
darkalex17/coyote
brew upgrade loki
```
### Scripts
#### Linux/MacOS (`bash`)
You can use the following command to run a bash script that downloads and installs the latest version of `coyote` for your
You can use the following command to run a bash script that downloads and installs the latest version of `loki` for your
OS (Linux/MacOS) and architecture (x86_64/arm64):
```shell
curl -fsSL https://raw.githubusercontent.com/Dark-Alex-17/coyote/refs/heads/main/scripts/install_coyote.sh | bash
curl -fsSL https://raw.githubusercontent.com/Dark-Alex-17/loki/main/install_loki.sh | bash
```
#### Windows/Linux/MacOS (`PowerShell`)
You can use the following command to run a PowerShell script that downloads and installs the latest version of `coyote`
You can use the following command to run a PowerShell script that downloads and installs the latest version of `loki`
for your OS (Windows/Linux/MacOS) and architecture (x86_64/arm64):
```powershell
powershell -NoProfile -ExecutionPolicy Bypass -Command "iwr -useb https://raw.githubusercontent.com/Dark-Alex-17/coyote/refs/heads/main/scripts/install_coyote.ps1 | iex"
powershell -NoProfile -ExecutionPolicy Bypass -Command "iwr -useb https://raw.githubusercontent.com/Dark-Alex-17/loki/main/scripts/install_loki.ps1 | iex"
```
### Manual
Binaries are available on the [releases](https://github.com/Dark-Alex-17/coyote/releases) page for the following platforms:
Binaries are available on the [releases](https://github.com/Dark-Alex-17/loki/releases) page for the following platforms:
| Platform | Architecture(s) |
|----------------|-----------------|
@@ -158,58 +126,35 @@ Binaries are available on the [releases](https://github.com/Dark-Alex-17/coyote/
#### Windows Instructions
To use a binary from the releases page on Windows, do the following:
1. Download the latest [binary](https://github.com/Dark-Alex-17/coyote/releases) for your OS.
1. Download the latest [binary](https://github.com/Dark-Alex-17/loki/releases) for your OS.
2. Use 7-Zip or TarTool to unpack the Tar file.
3. Run the executable `coyote.exe`!
3. Run the executable `loki.exe`!
#### Linux/MacOS Instructions
To use a binary from the releases page on Linux/MacOS, do the following:
1. Download the latest [binary](https://github.com/Dark-Alex-17/coyote/releases) for your OS.
1. Download the latest [binary](https://github.com/Dark-Alex-17/loki/releases) for your OS.
2. `cd` to the directory where you downloaded the binary.
3. Extract the binary with `tar -C /usr/local/bin -xzf coyote-<arch>.tar.gz` (Note: This may require `sudo`)
4. Now you can run `coyote`!
## Updating
Coyote can update itself in place to the latest GitHub release. Run `coyote --update`
for the newest release, or `coyote --update v0.4.0` for a specific version:
```shell
coyote --update
coyote --update v0.4.0
```
The same is available from within the REPL via `.update` and `.update v0.4.0`.
If Coyote was installed with a package manager, prefer that package manager so its
records stay in sync with the binary on disk; i.e. `brew upgrade coyote` for Homebrew,
or `cargo install --locked coyote-ai` for Cargo.
When Coyote detects a package-manager install it prints a warning and asks for
confirmation. In a non-interactive shell (no TTY), pass `--force` to update
anyway:
```shell
coyote --update --force
```
3. Extract the binary with `tar -C /usr/local/bin -xzf loki-<arch>.tar.gz` (Note: This may require `sudo`)
4. Now you can run `loki`!
## Getting Started
After installation, you can generate the configuration files and directories by simply running:
```sh
coyote --info
loki --info
```
Then, you need to set up the Coyote vault by creating a vault password file. Coyote will do this for you automatically and
Then, you need to set up the Loki vault by creating a vault password file. Loki will do this for you automatically and
guide you through the process when you first attempt to access the vault. So, to get started, you can run:
```sh
coyote --list-secrets
loki --list-secrets
```
### Authentication
Each client in your configuration needs authentication (with a few exceptions; e.g. ollama). Most clients use an API key
(set via `api_key` in the config or through the [vault](https://github.com/Dark-Alex-17/coyote/wiki/Vault)). For providers that support OAuth (e.g. Claude Pro/Max
(set via `api_key` in the config or through the [vault](./docs/VAULT.md)). For providers that support OAuth (e.g. Claude Pro/Max
subscribers, Google Gemini), you can authenticate with your existing subscription instead:
```yaml
@@ -221,40 +166,40 @@ clients:
```
```sh
coyote --authenticate my-claude-oauth
loki --authenticate my-claude-oauth
# Or via the REPL: .authenticate
```
For full details, see the [authentication documentation](https://github.com/Dark-Alex-17/coyote/wiki/Clients#authentication).
For full details, see the [authentication documentation](./docs/clients/CLIENTS.md#authentication).
### Tab-Completions
You can also enable tab completions to make using Coyote easier. To do so, add the following to your shell profile:
You can also enable tab completions to make using Loki easier. To do so, add the following to your shell profile:
```shell
# Bash
# (add to: `~/.bashrc`)
source <(COMPLETE=bash coyote)
source <(COMPLETE=bash loki)
# Zsh
# (add to: `~/.zshrc`)
source <(COMPLETE=zsh coyote)
source <(COMPLETE=zsh loki)
# Fish
# (add to: `~/.config/fish/config.fish`)
source <(COMPLETE=fish coyote | psub)
source <(COMPLETE=fish loki | psub)
# Elvish
# (add to: `~/.elvish/rc.elv`)
eval (E:COMPLETE=elvish coyote | slurp)
eval (E:COMPLETE=elvish loki | slurp)
# PowerShell
# (add to: `$PROFILE`)
$env:COMPLETE = "powershell"
coyote | Out-String | Invoke-Expression
loki | Out-String | Invoke-Expression
```
### Shell Integration
You can integrate Coyote's Shell Assistant into your shell for enhanced command-line assistance. Add the code in the
corresponding [shell integration script](./scripts/shell-integration) to your shell. Then, you can invoke Coyote to convert natural language to
You can integrate Loki's Shell Assistant into your shell for enhanced command-line assistance. Add the code in the
corresponding [shell integration script](./scripts/shell-integration) to your shell. Then, you can invoke Loki to convert natural language to
shell commands by pressing `Alt-e`. For example:
```shell
@@ -264,18 +209,18 @@ find . -name "*.md"
```
## Configuration
The location of the global Coyote configuration varies between systems, so you can use the following command to find your
The location of the global Loki configuration varies between systems, so you can use the following command to find your
`config.yaml` file:
```shell
coyote --info | grep 'config_file' | awk '{print $2}'
loki --info | grep 'config_file' | awk '{print $2}'
```
The configuration file consists of a number of settings. To see a full example configuration file with every setting
defined, refer to the [example configuration file](./config.example.yaml).
### Default LLM
The following settings are available to configure the default LLM that is used when you start Coyote, and its
The following settings are available to configure the default LLM that is used when you start Loki, and its
hyperparameters:
| Setting | Description |
@@ -285,34 +230,34 @@ hyperparameters:
| `top_p` | The default `top_p` hyperparameter value to use for all models, with a range of (0,1) (or (0,2) for some models); <br>Used unless explicitly overridden |
### CLI Behavior
You can use the following settings to modify the behavior of Coyote:
You can use the following settings to modify the behavior of Loki:
| Setting | Default Value | Description |
|---------------|---------------|-------------------------------------------------------------------------------------------------------------------------------------|
| `stream` | `true` | Controls whether to use stream-style APIs when querying for completions from LLM providers |
| `save` | `true` | Controls whether to save each query/response to every model to `messages.md` for posterity; Useful for debugging |
| `keybindings` | `emacs` | Specifies which keybinding schema to use; can either be `emacs` or `vi` |
| `editor` | `null` | What text editor Coyote should use to edit the input buffer or session (e.g. `vim`, `emacs`, `nano`, `hx`); <br>Defaults to `$EDITOR` |
| `editor` | `null` | What text editor Loki should use to edit the input buffer or session (e.g. `vim`, `emacs`, `nano`, `hx`); <br>Defaults to `$EDITOR` |
| `wrap` | `no` | Controls whether text is wrapped (can be `no`, `auto`, or some `<max_width>` |
| `wrap_code` | `false` | Enables or disables the wrapping of code blocks |
### Preludes
Preludes let you define the default behavior for the different operating modes of Coyote. The available settings are
Preludes let you define the default behavior for the different operating modes of Loki. The available settings are
shown below:
| Setting | Description |
|-----------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| `repl_prelude` | This setting lets you specify a default `session` or `role` to use when starting Coyote in [REPL](https://github.com/Dark-Alex-17/coyote/wiki/REPL) mode. <br>Values can be <ul><li>`role:<name>` to define a role</li><li>`session:<name>` to define a session</li><li>`<session>:<role>` to define both a session and a role to use</li></ul> |
| `cmd_prelude` | This setting lets you specify a default `session` or `role` to use when running one-off queries in Coyote via the CLI. <br>Values can be <ul><li>`role:<name>` to define a role</li><li>`session:<name>` to define a session</li><li>`<session>:<role>` to define both a session and a role to use</li></ul> |
| `repl_prelude` | This setting lets you specify a default `session` or `role` to use when starting Loki in [REPL](./docs/REPL.md) mode. <br>Values can be <ul><li>`role:<name>` to define a role</li><li>`session:<name>` to define a session</li><li>`<session>:<role>` to define both a session and a role to use</li></ul> |
| `cmd_prelude` | This setting lets you specify a default `session` or `role` to use when running one-off queries in Loki via the CLI. <br>Values can be <ul><li>`role:<name>` to define a role</li><li>`session:<name>` to define a session</li><li>`<session>:<role>` to define both a session and a role to use</li></ul> |
| `agent_session` | This setting is used to specify a default session that all agents should start into, unless otherwise specified in the agent configuration. (e.g. `temp`, `default`) |
### Appearance
The appearance of Coyote can be modified using the following settings:
The appearance of Loki can be modified using the following settings:
| Setting | Default Value | Description |
|---------------|---------------|------------------------------------------------------|
| `highlight` | `true` | This setting enables or disables syntax highlighting |
| `light_theme` | `false` | This setting toggles light mode in Coyote |
| `light_theme` | `false` | This setting toggles light mode in Loki |
### Miscellaneous Settings
| Setting | Default Value | Description |
@@ -324,7 +269,7 @@ The appearance of Coyote can be modified using the following settings:
## History
Coyote began as a fork of [AIChat CLI](https://github.com/sigoden/aichat) and has since evolved into an independent project.
Loki began as a fork of [AIChat CLI](https://github.com/sigoden/aichat) and has since evolved into an independent project.
See [CREDITS.md](./CREDITS.md) for full attribution and background.
@@ -332,16 +277,3 @@ See [CREDITS.md](./CREDITS.md) for full attribution and background.
## Creator
* [Alex Clarke](https://github.com/Dark-Alex-17)
---
## License
Coyote is licensed under the [GNU Affero General Public License v3.0](./LICENSE)
(AGPL-3.0-only).
Coyote began as a fork of [AIChat](https://github.com/sigoden/aichat)
(Copyright (c) sigoden), which is licensed under the MIT License. Substantial
portions of Coyote are derived from AIChat and remain available under the MIT
License, preserved in [LICENSE-MIT](./LICENSE-MIT). See [NOTICE](./NOTICE) and
[CREDITS.md](./CREDITS.md) for details.
assets/agents/.shared/utils.sh
+25 -101
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@@ -7,14 +7,14 @@ set -euo pipefail
#######################
# Cache file name for detected project info
_COYOTE_PROJECT_CACHE=".coyote-project.json"
_LOKI_PROJECT_CACHE=".loki-project.json"
# Read cached project detection if valid
# Usage: _read_project_cache "/path/to/project"
# Returns: cached JSON on stdout (exit 0) or nothing (exit 1)
_read_project_cache() {
local dir="$1"
local cache_file="${dir}/${_COYOTE_PROJECT_CACHE}"
local cache_file="${dir}/${_LOKI_PROJECT_CACHE}"
if [[ -f "${cache_file}" ]]; then
local cached
@@ -32,7 +32,7 @@ _read_project_cache() {
_write_project_cache() {
local dir="$1"
local json="$2"
local cache_file="${dir}/${_COYOTE_PROJECT_CACHE}"
local cache_file="${dir}/${_LOKI_PROJECT_CACHE}"
echo "${json}" > "${cache_file}" 2>/dev/null || true
}
@@ -40,57 +40,15 @@ _write_project_cache() {
_detect_heuristic() {
local dir="$1"
local runner="" runner_type="" runner_targets=""
if [[ -f "${dir}/Taskfile.yml" || -f "${dir}/Taskfile.yaml" || -f "${dir}/taskfile.yml" || -f "${dir}/taskfile.yaml" ]]; then
runner="task" runner_type="taskfile"
runner_targets=$( (cd "${dir}" && task --list-all 2>/dev/null | sed -n 's/^\* \([^:[:space:]]*\):.*/\1/p') || true)
elif [[ -f "${dir}/justfile" || -f "${dir}/Justfile" ]]; then
runner="just" runner_type="just"
runner_targets=$( (cd "${dir}" && just --summary 2>/dev/null | tr ' ' '\n') || true)
elif [[ -f "${dir}/Makefile" || -f "${dir}/makefile" || -f "${dir}/GNUmakefile" ]]; then
runner="make" runner_type="make"
local mk mkfiles=()
for mk in Makefile makefile GNUmakefile; do
[[ -f "${dir}/${mk}" ]] && mkfiles+=("${dir}/${mk}")
done
runner_targets=$(sed -n 's/^\([A-Za-z0-9_][A-Za-z0-9_.-]*\):\([^=].*\|\)$/\1/p' "${mkfiles[@]}" 2>/dev/null | sort -u || true)
fi
if [[ -n "${runner}" && -n "${runner_targets}" ]]; then
_pick_target() {
local c
for c in "$@"; do
if grep -qx "${c}" <<<"${runner_targets}"; then
echo "${runner} ${c}"
return 0
fi
done
echo ""
}
local r_build r_test r_check r_lint r_fmt
r_build=$(_pick_target build compile)
r_test=$(_pick_target test tests unit)
r_check=$(_pick_target check vet typecheck build)
r_lint=$(_pick_target lint fmt-check)
r_fmt=$(_pick_target fmt format)
if [[ -n "${r_build}${r_test}${r_check}${r_lint}${r_fmt}" ]]; then
echo "{\"type\":\"${runner_type}\",\"build\":\"${r_build}\",\"test\":\"${r_test}\",\"check\":\"${r_check}\",\"lint\":\"${r_lint}\",\"fmt\":\"${r_fmt}\"}"
return 0
fi
fi
# Rust
if [[ -f "${dir}/Cargo.toml" ]]; then
echo '{"type":"rust","build":"cargo build","test":"cargo test","check":"cargo check","lint":"cargo clippy --no-deps -- -D warnings","fmt":"cargo fmt"}'
echo '{"type":"rust","build":"cargo build","test":"cargo test","check":"cargo check"}'
return 0
fi
# Go
if [[ -f "${dir}/go.mod" ]]; then
local go_lint=""
if compgen -G "${dir}/.golangci.*" &>/dev/null && command -v golangci-lint &>/dev/null; then
go_lint="golangci-lint run"
fi
echo "{\"type\":\"go\",\"build\":\"go build ./...\",\"test\":\"go test ./...\",\"check\":\"go vet ./...\",\"lint\":\"${go_lint}\",\"fmt\":\"gofmt -w .\"}"
echo '{"type":"go","build":"go build ./...","test":"go test ./...","check":"go vet ./..."}'
return 0
fi
@@ -107,25 +65,7 @@ _detect_heuristic() {
[[ -f "${dir}/pnpm-lock.yaml" ]] && pm="pnpm"
[[ -f "${dir}/yarn.lock" ]] && pm="yarn"
# Emit only scripts the manifest actually declares (same introspection
# contract as the runner tier: never guess a target into existence).
_pkg_script() {
local s
for s in "$@"; do
if jq -e --arg s "$s" '.scripts[$s] // empty' "${dir}/package.json" &>/dev/null; then
echo "${pm} run ${s}"
return 0
fi
done
echo ""
}
local p_build p_test p_check p_lint p_fmt
p_build=$(_pkg_script build compile)
p_test=$(_pkg_script test)
p_check=$(_pkg_script check typecheck tsc)
p_lint=$(_pkg_script lint)
p_fmt=$(_pkg_script fmt format prettier)
echo "{\"type\":\"nodejs\",\"build\":\"${p_build}\",\"test\":\"${p_test}\",\"check\":\"${p_check}\",\"lint\":\"${p_lint}\",\"fmt\":\"${p_fmt}\"}"
echo "{\"type\":\"nodejs\",\"build\":\"${pm} run build\",\"test\":\"${pm} test\",\"check\":\"${pm} run lint\"}"
return 0
fi
@@ -142,7 +82,7 @@ _detect_heuristic() {
check_cmd="uv run ruff check ."
fi
echo "{\"type\":\"python\",\"build\":\"\",\"test\":\"${test_cmd}\",\"check\":\"${check_cmd}\",\"lint\":\"${check_cmd}\",\"fmt\":\"ruff format .\"}"
echo "{\"type\":\"python\",\"build\":\"\",\"test\":\"${test_cmd}\",\"check\":\"${check_cmd}\"}"
return 0
fi
@@ -204,6 +144,17 @@ _detect_heuristic() {
return 0
fi
# Generic build systems (last resort before LLM)
if [[ -f "${dir}/justfile" ]] || [[ -f "${dir}/Justfile" ]]; then
echo '{"type":"just","build":"just build","test":"just test","check":"just lint"}'
return 0
fi
if [[ -f "${dir}/Makefile" ]] || [[ -f "${dir}/makefile" ]] || [[ -f "${dir}/GNUmakefile" ]]; then
echo '{"type":"make","build":"make build","test":"make test","check":"make lint"}'
return 0
fi
return 1
}
@@ -267,9 +218,7 @@ _detect_with_llm() {
local prompt
prompt=$(cat <<-EOF
Analyze this project directory and determine the project type, primary language, and the correct shell commands to build, test, check (typecheck/vet), lint, and format it.
PRIORITY RULE: if the project declares its own task-runner interface (a Taskfile, justfile, Makefile, package.json scripts, or similar), those declared targets ARE the correct commands — prefer them over generic ecosystem defaults, and never invent a target the interface does not declare.
Analyze this project directory and determine the project type, primary language, and the correct shell commands to build, test, and check (lint/typecheck) it.
EOF
)
@@ -277,25 +226,25 @@ _detect_with_llm() {
prompt+=$(cat <<-EOF
Respond with ONLY a valid JSON object. No markdown fences, no explanation, no extra text.
The JSON must have exactly these 6 keys:
{"type":"<language>","build":"<build command>","test":"<test command>","check":"<typecheck/vet command>","lint":"<lint command>","fmt":"<format command>"}
The JSON must have exactly these 4 keys:
{"type":"<language>","build":"<build command>","test":"<test command>","check":"<lint or typecheck command>"}
Rules:
- "type" must be a single lowercase word (e.g. rust, go, python, nodejs, java, ruby, elixir, cpp, c, zig, haskell, scala, kotlin, dart, swift, php, dotnet, etc.)
- If a command doesn't apply to this project, use an empty string, "" — NEVER guess a command that might not exist; a wrongly-guessed command is worse than an empty one
- If a command doesn't apply to this project, use an empty string, ""
- Use the most standard/common commands for the detected ecosystem
- If you detect a package manager lockfile, use that package manager (e.g. pnpm over npm)
EOF
)
local llm_response
llm_response=$(coyote --no-stream "${prompt}" 2>/dev/null) || return 1
llm_response=$(loki --no-stream "${prompt}" 2>/dev/null) || return 1
llm_response=$(echo "${llm_response}" | sed 's/^```json//;s/^```//;s/```$//' | tr -d '\n' | sed 's/^[[:space:]]*//')
llm_response=$(echo "${llm_response}" | grep -o '{[^}]*}' | head -1)
if echo "${llm_response}" | jq -e '.type and .build != null and .test != null and .check != null' &>/dev/null; then
echo "${llm_response}" | jq -c '{type: (.type // "unknown"), build: (.build // ""), test: (.test // ""), check: (.check // ""), lint: (.lint // ""), fmt: (.fmt // "")}'
echo "${llm_response}" | jq -c '{type: (.type // "unknown"), build: (.build // ""), test: (.test // ""), check: (.check // "")}'
return 0
fi
@@ -309,7 +258,7 @@ detect_project() {
local cached
if cached=$(_read_project_cache "${dir}"); then
echo "${cached}" | jq -c '{type, build, test, check, lint: (.lint // ""), fmt: (.fmt // "")}'
echo "${cached}" | jq -c '{type, build, test, check}'
return 0
fi
@@ -337,31 +286,6 @@ detect_project() {
echo '{"type":"unknown","build":"","test":"","check":""}'
}
# resolve_gate_dir maps a workspace root to the directory verification gates
# must run in. A delivery-repo worker's workspace root holds only dotfiles
# plus the clone, so gates aimed at the root detect nothing and silently
# no-op. When the root has no project markers and exactly ONE first-level
# git repo exists, gates run inside it; anything ambiguous stays at the root.
resolve_gate_dir() {
local dir="${1:-.}"
local m
for m in Taskfile.yml Taskfile.yaml taskfile.yml Cargo.toml go.mod package.json pyproject.toml setup.py pom.xml build.gradle mix.exs Gemfile composer.json Makefile justfile Justfile CMakeLists.txt; do
if [[ -e "${dir}/${m}" ]]; then
echo "${dir}"
return 0
fi
done
local repos=() d
for d in "${dir}"/*/; do
[[ -d "${d}/.git" ]] && repos+=("${d}")
done
if [[ ${#repos[@]} -eq 1 ]]; then
echo "${repos[0]%/}"
return 0
fi
echo "${dir}"
}
###########################
## FILE SEARCH UTILITIES ##
###########################
assets/agents/adversary/README.md
-94
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@@ -1,94 +0,0 @@
# Adversary
An **adversarial plan-conformance reviewer**. Where [`code-reviewer`](../code-reviewer/README.md)
asks *"is this code good?"*, `adversary` asks a different, harder question:
> **"Is this the code the plan asked for — all of it, and only it?"**
It hunts the gap between what a task/plan *specified* and what the implementer actually *built*:
silently skipped acceptance criteria, scope creep, interface substitution, approach drift, and the
requirements that never showed up in the diff at all ("the dog that didn't bark"). It assumes the
implementer drifted until the diff proves otherwise — the independence is the value.
## Why it's separate from `code-reviewer`
| | `code-reviewer` | `adversary` |
|---|---|---|
| Question | Is the code correct/clean/safe? | Does the code match the plan? |
| Input | The diff | The diff **+ the plan's acceptance criteria** |
| Blind spot it covers | slop, bugs, coupling, footguns | skipped criteria, scope drift, contract breakage |
| Output | severity-tagged findings (🔴🟡🟢) | a blocking verdict: `CONFORMS` / `DIVERGES` |
They are **complementary passes**, not substitutes. `sisyphus` runs both on non-trivial work: one
guards quality, the other guards fidelity to the plan.
## Verdict (blocking)
The agent ends every review with one sentinel:
```
ADVERSARIAL_REVIEW: CONFORMS
Criteria: N/N met (all with tests).
```
```
ADVERSARIAL_REVIEW: DIVERGES
Criteria: X/N met, Y partial, Z unmet/diverged.
Complaints:
1. Acceptance criterion "<quoted>" — <Unmet|Partial|Diverged> — <what the diff does/omits, file:line> — <fix>
2. ...
```
A `DIVERGES` verdict **blocks** completion. The caller (sisyphus/architect) must reconcile it —
resume the SAME coder/sisyphus session with the complaints pasted verbatim — or escalate. It mirrors
the `oracle` + `plan-review` gate used before implementation, but applied *after* implementation.
Every complaint ties to a quoted acceptance criterion (or a named scope/interface/out-of-scope
violation) and cites `file:line`. Vague complaints are not emitted.
## How it reviews
Driven by the [`adversarial-review`](../../skills/adversarial-review/SKILL.md) skill:
1. Map **every** acceptance criterion to specific evidence in the diff → ✅ Met / ⚠️ Partial / ❌ Unmet / 🔀 Diverged. No test proving the behavior ⇒ at best ⚠️ Partial.
2. Ground-truth with read-only tools (`fs_grep`/`fs_read`/`ast_grep`): confirm required symbols exist as specified, changes land where they must, new behavior is actually reached, tests target behavior not implementation.
3. Hunt adversarially for the **absent**: skipped criteria, scope creep, interface/approach substitution, out-of-scope touches, downstream contract breakage.
It is **read-only** — it produces a verdict, never a fix.
## Usage
Typically spawned by `sisyphus` (or `architect`) alongside `code-reviewer`. The spawn prompt IS its
entire context, so it must include the diff (or a base ref to fetch) **and** the acceptance criteria:
```sh
agent__spawn --agent adversary --prompt "
## TASK
Adversarially review the recent changes for TASK-NNN against its plan. Return CONFORMS/DIVERGES.
## DIFF
Run get_diff (or --base main), or: <paste diff>
## PLAN — acceptance criteria to check against
<paste the task index.md body + the relevant PLAN-*.md section, verbatim>
"
```
Direct invocation for ad-hoc use:
```sh
coyote -a adversary --agent-variable project_dir /path/to/repo \
"Review staged changes against these criteria: <paste criteria>"
```
### Tools
- `get_diff [--base <ref>]` — staged → unstaged → `HEAD~1` fallback (or an explicit base/PR branch).
- `get_changed_files [--base <ref>]` — quick changed-file map.
- Plus read-only `fs_*` and `ast_grep` for ground-truth checks.
## Related
- [`adversarial-review`](../../skills/adversarial-review/SKILL.md) — the conformance methodology it runs on.
- [`code-reviewer`](../code-reviewer/README.md) — the quality reviewer it runs alongside.
- [`plan-review`](../../skills/plan-review/SKILL.md) — the *pre*-implementation plan gate; `adversary` is its *post*-implementation counterpart.
assets/agents/adversary/config.yaml
-118
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@@ -1,118 +0,0 @@
name: adversary
description: Adversarial plan-conformance reviewer - judges whether an implementation matches the task/plan it was supposed to satisfy (not code quality). Returns a blocking CONFORMS/DIVERGES verdict. Complements code-reviewer. Designed to be delegated to by sisyphus.
version: 1.0.0
auto_continue: true
max_auto_continues: 15
inject_todo_instructions: true
skills_enabled: true
enabled_skills:
- adversarial-review
variables:
- name: project_dir
description: Project directory containing the changes under review
default: '.'
- name: auto_confirm
description: Auto-confirm command execution
default: '1'
global_tools:
- ast_grep.sh
- fs_read.sh
- fs_cat.sh
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
- execute_command.sh
instructions: |
You are an adversarial plan-conformance reviewer. You answer ONE question: **does this
implementation match the plan it was supposed to satisfy — all of it, and only it?** You are NOT
the code-quality reviewer (that is `code-reviewer`/`file-reviewer`, which judges correctness, slop,
and style). You judge CONFORMANCE: skipped acceptance criteria, silent scope drift, interface
substitution, and things the plan required that never showed up in the diff.
Your value is independence and suspicion. Assume the implementer drifted, cut a corner, or misread
the plan until the diff proves otherwise.
## Step 0: Load the skill
Before anything else, `skill__load` `adversarial-review`. It carries your methodology: the
criterion-by-criterion evidence mapping, the adversarial checklist (silently skipped criteria,
scope drift, interface drift, ground-truth verification, out-of-scope violations, downstream
contract breakage), and the exact verdict format. The skill body is your source of truth for HOW to
review and WHAT to flag; these instructions handle workflow and I/O.
## Input (the spawn prompt IS your entire context)
You are given:
1. **The diff** — pasted inline, or run `get_diff` (optionally `--base <ref>`) if told to fetch it.
2. **The plan** — the task's Objective, Tasks, and especially its **Acceptance criteria**, pasted
inline (e.g. a task file's What/Steps/Acceptance criteria + the relevant plan section), or a path to read.
If the plan / acceptance criteria are missing, STOP and say so: conformance cannot be judged
without a spec. Do not invent criteria or guess intent.
## Workflow
1. Load `adversarial-review`.
2. Get the diff (inline or via `get_diff`) and identify the changed files.
3. For EACH acceptance criterion: find the specific evidence in the diff that satisfies it and
classify it ✅ Met / ⚠️ Partial / ❌ Unmet / 🔀 Diverged. A criterion with no test proving its
behavior is at best ⚠️ Partial.
4. Ground-truth every claim: `fs_grep` the symbols the plan requires (confirm they exist, spelled
as specified), `fs_read` around each hunk to confirm the change makes the criterion true, grep
callers to confirm new behavior is reached, confirm tests target behavior not implementation.
Use `ast_grep` for structural checks (e.g. "was this function signature actually changed?").
5. Hunt adversarially for what's ABSENT (the dog that didn't bark), scope creep, interface/approach
substitution, out-of-scope touches, and downstream contract breakage — per the skill checklist.
6. Emit the verdict in the skill's exact format.
## Output — verdict (MANDATORY, exact format)
End with EXACTLY one of these sentinels so the caller can route on it:
```
ADVERSARIAL_REVIEW: CONFORMS
Criteria: N/N met (all with tests).
<optional: 1-3 non-blocking observations>
```
```
ADVERSARIAL_REVIEW: DIVERGES
Criteria: X/N met, Y partial, Z unmet/diverged.
Complaints:
1. Acceptance criterion "<quoted>" — <Unmet|Partial|Diverged> — <what the diff does/omits, file:line> — <what would make it conform>
2. Scope drift / interface drift / out-of-scope — <file:line> — <the violation> — <the fix>
3. ...
```
Every complaint MUST quote the specific acceptance criterion (or name the specific scope/interface/
out-of-scope violation) AND cite file:line. A complaint with no criterion reference and no location
is noise — do not emit it.
## Rules
1. **You are read-only.** Never modify files. You produce a verdict; the implementer owns the fix.
2. **Conformance, not quality.** Do not flag style/naming/micro-optimizations unless they cause a
criterion to be unmet. If a quality defect breaks a criterion (a race violating a correctness
criterion), flag it as a conformance failure and note it is also a quality issue.
3. **No test ⇒ not met.** An acceptance criterion is a promise of observable behavior; unproven
behavior is at best Partial.
4. **Absence is a finding.** Review what SHOULD be in the diff per the plan, not only what IS.
5. **Don't re-litigate a settled decision** — but DO flag when the diff silently overrode one the
plan recorded ("do X not Y because Z" → diff does Y).
6. **The plan can be the culprit.** If the plan is impossible/self-contradictory, that is DIVERGES
with the plan named as root cause — never judge against a plan you silently corrected.
7. Be terse and decisive. Three real divergences beat fifteen weak ones. If everything is a nitpick,
it CONFORMS — say so.
## Context
- Project: {{project_dir}}
- CWD: {{__cwd__}}
- Shell: {{__shell__}}
## Available Tools
{{__tools__}}
assets/agents/adversary/tools.sh
-78
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@@ -1,78 +0,0 @@
#!/usr/bin/env bash
set -eo pipefail
# @env LLM_OUTPUT=/dev/stdout
# @env LLM_AGENT_VAR_PROJECT_DIR=.
# @describe Adversarial plan-conformance reviewer tools
_project_dir() {
local dir="${LLM_AGENT_VAR_PROJECT_DIR:-.}"
(cd "${dir}" 2>/dev/null && pwd) || echo "${dir}"
}
# @cmd Get the git diff to review for plan conformance. Returns staged changes, or unstaged if nothing is staged, or the HEAD~1 diff if the working tree is clean.
# @option --base Optional base ref to diff against (e.g., "main", "HEAD~3", a commit SHA, or a PR base branch)
get_diff() {
local project_dir
project_dir=$(_project_dir)
# shellcheck disable=SC2154
local base="${argc_base:-}"
local diff_output=""
if [[ -n "${base}" ]]; then
diff_output=$(cd "${project_dir}" && git diff "${base}" 2>&1) || true
else
diff_output=$(cd "${project_dir}" && git diff --cached 2>&1) || true
if [[ -z "${diff_output}" ]]; then
diff_output=$(cd "${project_dir}" && git diff 2>&1) || true
fi
if [[ -z "${diff_output}" ]]; then
diff_output=$(cd "${project_dir}" && git diff HEAD~1 2>&1) || true
fi
fi
if [[ -z "${diff_output}" ]]; then
echo "No changes found to review in ${project_dir}." >> "$LLM_OUTPUT"
return 0
fi
local file_count
file_count=$(echo "${diff_output}" | grep -c '^diff --git' || true)
{
echo "Diff contains changes to ${file_count} file(s):"
echo ""
echo "${diff_output}"
} >> "$LLM_OUTPUT"
}
# @cmd Get the list of changed files with stats (a quick map of what to check against the plan).
# @option --base Optional base ref to diff against
get_changed_files() {
local project_dir
project_dir=$(_project_dir)
local base="${argc_base:-}"
local stat_output=""
if [[ -n "${base}" ]]; then
stat_output=$(cd "${project_dir}" && git diff --stat "${base}" 2>&1) || true
else
stat_output=$(cd "${project_dir}" && git diff --cached --stat 2>&1) || true
if [[ -z "${stat_output}" ]]; then
stat_output=$(cd "${project_dir}" && git diff --stat 2>&1) || true
fi
if [[ -z "${stat_output}" ]]; then
stat_output=$(cd "${project_dir}" && git diff --stat HEAD~1 2>&1) || true
fi
fi
if [[ -z "${stat_output}" ]]; then
echo "No changes found in ${project_dir}." >> "$LLM_OUTPUT"
return 0
fi
{
echo "Changed files:"
echo ""
echo "${stat_output}"
} >> "$LLM_OUTPUT"
}
assets/agents/architect/README.md
-182
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@@ -1,182 +0,0 @@
# Architect
A **design-doc orchestrator for any project**. Give it one high-level design doc; it decomposes the
doc into a quality-gated plan and ~1-engineer-day task files, spawns **one
[Sisyphus](../sisyphus/README.md) per task** on a single run branch, verifies each task with an
adversarial plan-conformance check, and finishes with **one draft PR** (CI checks watched to green)
plus tracked follow-up tasks for the manual work the code can't do for itself.
Architect does **not** write feature code itself. It owns the *process*; Sisyphus owns each *task*.
## The pipeline it drives
```mermaid
flowchart TD
user([Design doc]) --> architect["Architect<br/>design-doc orchestrator"]
architect --> orient["Phase A — Orient<br/>project conventions · build/test commands · design doc"]
orient --> design["Phase B — design-session<br/>plans_dir/PLAN-&lt;slug&gt;.md + 1-day task breakdown"]
design -. "grounding" .-> explore[["explore<br/>codebase grep<br/>× parallel"]]
design -. "unfamiliar libraries" .-> librarian[["librarian<br/>docs + OSS grep"]]
explore -. "findings ground<br/>the breakdown" .-> design
librarian -. "findings ground<br/>the breakdown" .-> design
design --> gatekeeper[["gatekeeper<br/>self-containedness audit<br/>(docker-container test)"]]
gatekeeper --> g1{"PLAN_GATE?"}
g1 -->|"LEAKY (≤ 2 cycles)"| amend["Answer the missing questions<br/>via explore / librarian / docs<br/>(user__ask only for business rules)<br/>→ amend the plan"]
amend --> gatekeeper
g1 -->|"LEAKY after 2 cycles"| escalate
g1 -->|"SEALED"| oracle[["oracle<br/>plan-review<br/>(executability)"]]
oracle --> g2{"PLAN_REVIEW?"}
g2 -->|"REJECT — fix complaints,<br/>re-submit SAME session"| oracle
g2 -->|"OKAY"| tasks["Phase D — materialize tasks<br/>plans_dir/tasks/TASK-NNN-*/ (task-tracking)"]
tasks --> branch["Phase E — run branch<br/>feat/PLAN-&lt;slug&gt; off base_branch"]
branch --> claim["Claim task (sequential, dependency order)<br/>status: in-progress + base SHA"]
claim --> sisyphus[["sisyphus<br/>implement ONE task on the run branch<br/>commit + push — NO PR"]]
sisyphus --> adversary[["adversary<br/>conformance check<br/>diff vs task base SHA"]]
adversary --> verdict{"ADVERSARIAL_REVIEW?"}
verdict -->|"DIVERGES — resume<br/>SAME sisyphus session (once)"| sisyphus
verdict -->|"still DIVERGES"| escalate
verdict -->|"CONFORMS"| taskdone["Close task<br/>status: complete · log commits + follow-ups"]
taskdone --> more{"More tasks?"}
more -->|"yes"| claim
more -->|"no"| finish["Phase F — full build + tests<br/>on the integrated run branch"]
finish --> pr["ONE DRAFT PR: run branch → base_branch<br/>(never marked ready — user reviews first)<br/>body: task checklist + Follow-up / manual actions"]
pr --> checks{"PR runs/checks<br/>green?"}
checks -->|"failure — resume responsible<br/>sisyphus session, fix, push"| checks
checks -->|"external flake /<br/>broken base branch"| escalate
checks -->|"green"| followups["Create follow-up task files<br/>(type: followup, pending)<br/>→ picked up by the user post-merge"]
followups --> backfill["Backfill PR link into PLAN + task logs<br/>PLAN status: implemented"]
backfill --> validate["task-tracking consistency checks"]
validate --> done([Run complete])
escalate([user__ask — escalate to user])
branch -. "parallel_tasks=1 (opt-in):<br/>per-task worktrees + task branches,<br/>merged one at a time with<br/>integration tests after every merge" .-> claim
```
## Where state lives
Everything is file-based in **`plans_dir`** (default `plans/`, resolved against the project):
```
<plans_dir>/
PLAN-<slug>.md # problem / approach / alternatives / task breakdown
tasks/TASK-NNN-<slug>/
index.md # What / Steps / Acceptance criteria; status in frontmatter
log.md # append-only audit trail (branch, commits, follow-ups, PR)
```
- `plans_dir` **inside the repo** (default) → planning files ride the run branch and land in the PR
(self-documenting review).
- `plans_dir` **absolute, outside the repo** (e.g. a common runs directory) → nothing planning-related
is ever committed.
Disk is the durable store: task statuses, logs, and follow-ups survive context compression; chat
history does not.
## The three review gates
| Gate | Agent | Question | When |
|------|-------|----------|------|
| Self-containedness | [`gatekeeper`](../gatekeeper/README.md) | "Can a context-free LLM implement from this plan alone?" | Before tasks exist |
| Executability | `oracle` + `plan-review` | "Is the approach sound, verifiable, correctly ordered?" | After sealing |
| Conformance | [`adversary`](../adversary/README.md) | "Is the built code what the plan asked for?" | After each task |
## Key conventions it enforces
- **One task = one engineer-day** — anything larger gets decomposed at the design stage.
- **Task state on disk** — `status:` frontmatter lifecycle per the `task-tracking` skill; no state
lives only in chat.
- **One run branch, one draft PR** — `feat/PLAN-<slug>` off `base_branch`; the PR is never opened
per-task, never non-draft, never marked ready-for-review (you flip it yourself).
- **CI checks watched to green** — failures are routed back to the responsible Sisyphus session; the
run isn't done with red or pending checks.
- **No plan references in code comments** — comments never cite the design doc, plan, phases, steps,
or TASK numbers (docs drift; comments rot). Plan references live in commit messages only.
- **`.env` never lands in a repo** — only `.env.example` with placeholder keys; real values become a
follow-up.
- **Follow-ups are tracked, never dropped** — every manual action (secrets, cloud roles, console
steps, cross-repo changes) is reported per task, logged durably, rolled into the PR's
`## Follow-up / manual actions` section (pre-merge items first), and materialized as
`type: followup` task files for you to pick up post-merge.
## Usage
```sh
# From the target project root (default autonomy: full)
coyote -a architect --agent-variable design_doc docs/design/my-feature.md \
"Implement this design doc end to end"
# Approve the task breakdown once, then run autonomously
coyote -a architect \
--agent-variable design_doc docs/design/my-feature.md \
--agent-variable autonomy plan-gate \
"Decompose and implement"
# Different project / plans outside the repo / PR against a non-main base
coyote -a architect \
--agent-variable project_dir ~/code/my-service \
--agent-variable plans_dir ~/architect-runs/my-service \
--agent-variable base_branch develop \
--agent-variable design_doc ~/docs/big-refactor.md \
"Run the pipeline"
```
### Variables
| Variable | Default | Meaning |
|----------|---------|---------|
| `project_dir` | `.` | The target repo — the only WRITE target for feature code. |
| `plans_dir` | `plans` | Where PLAN + task files live. Relative → in-repo (rides the PR); absolute → outside git. |
| `design_doc` | *(empty)* | Path to the design doc; asked for if unset. |
| `base_branch` | `main` | Branch the run branch forks from and the PR targets. |
| `autonomy` | `full` | `full` (no gates) · `plan-gate` (approve breakdown once) · `phase-gate` (approve each task). |
| `parallel_tasks` | `0` | `0` = sequential (default) · `1` = opt-in worktree-parallel execution for eligible tasks. |
| `auto_confirm` | `1` | Skip the shell confirm guard (needed for non-interactive autonomous runs). |
## Autonomy
Fully autonomous end-to-end by default — it halts only for genuine blockers: scope-changing
ambiguity or unresolved design questions, a task that fails after Sisyphus's own recovery (consults
Oracle, then escalates), and any destructive/irreversible action. Use `plan-gate` or `phase-gate`
to insert approval checkpoints.
## Parallel task execution (opt-in)
By default (`parallel_tasks: 0`) tasks run **sequentially** on the single run branch. Setting
`parallel_tasks: 1` enables worktree-based parallelism:
- Eligible tasks (mutually unblocked, plan-declared file-disjoint, max 3 concurrent) each get an
isolated `git worktree` + task branch forked from the run branch tip.
- Tasks touching **migrations, generated code, or dependency manifests/lockfiles** are never
parallel-eligible — shared hotspots collide even when the plan calls tasks independent.
- Architect integrates: completed task branches merge into the run branch **one at a time**, with a
full build + test run after every merge. Conflicts go back to that task's Sisyphus session to
rebase and re-verify.
- Worktrees and task branches are cleaned up after each clean merge. Phase F (single draft PR +
CI-check watch) is unchanged in both modes.
## Sub-agents it spawns
| Agent | Used for |
|-------|----------|
| [`sisyphus`](../sisyphus/README.md) | Implement ONE task's code (its own explore→coder→verify→review loop). One per task. |
| [`gatekeeper`](../gatekeeper/README.md) | Plan self-containedness gate (`PLAN_GATE: SEALED/LEAKY`). |
| [`adversary`](../adversary/README.md) | Per-task plan-conformance verdict (`ADVERSARIAL_REVIEW: CONFORMS/DIVERGES`). |
| [`oracle`](../oracle/README.md) | Plan review (`plan-review`); diagnosis when a task fails after Sisyphus recovery. |
| [`explore`](../explore/README.md) | Ground the design/plan in real code; read other local repos for library usage and call sites. |
| [`librarian`](../librarian/README.md) | External docs / OSS examples for unfamiliar libraries. |
## Related skills
- [`design-session`](../../skills/design-session/SKILL.md) — design doc → grounded proposal → PLAN + sized breakdown.
- [`task-tracking`](../../skills/task-tracking/SKILL.md) — the task-file schema, lifecycle, and consistency checks.
- [`plan-gatekeeping`](../../skills/plan-gatekeeping/SKILL.md) — the gatekeeper's self-containedness manifest.
- [`plan-authoring`](../../skills/plan-authoring/SKILL.md) / [`plan-review`](../../skills/plan-review/SKILL.md) — plan schema + oracle's executability review.
- [`adversarial-review`](../../skills/adversarial-review/SKILL.md) — the adversary's conformance methodology.
assets/agents/architect/config.yaml
-460
View File
@@ -1,460 +0,0 @@
name: architect
description: |
Design-doc orchestrator for any project. Consumes a high-level design doc, decomposes it into a
gated plan (gatekeeper self-containedness + oracle plan-review) and ~1-engineer-day task files,
spawns one Sisyphus per task on a single run branch, verifies each with an adversarial
plan-conformance check, and finishes with ONE draft PR (CI checks watched to green) plus tracked
follow-up tasks. Task state lives on disk in a plans directory, so runs survive context compression.
version: 2.0.0
agent_session: temp
auto_continue: true
max_auto_continues: 100
inject_todo_instructions: true
can_spawn_agents: true
spawnable_agents:
- sisyphus
- oracle
- explore
- librarian
- adversary
- gatekeeper
max_concurrent_agents: 10
max_agent_depth: 10
inject_spawn_instructions: true
summarization_threshold: 100000
skills_enabled: true
enabled_skills:
- design-session
- task-tracking
- plan-authoring
- delegation-protocol
- git-master
- parallel-research
variables:
- name: project_dir
description: Absolute path to the target project repo — the ONLY write target for feature code
default: '.'
- name: plans_dir
description: Where the PLAN file and task dirs live. Relative paths resolve against project_dir (and then ride the run branch into the PR); an absolute path outside the repo keeps planning files out of git entirely.
default: 'plans'
- name: design_doc
description: Path to the high-level design doc to implement (absolute, or relative to project_dir)
default: ''
- name: base_branch
description: The branch the run branch forks from and the PR targets
default: 'main'
- name: autonomy
description: 'How autonomous the run is: full (no gates), plan-gate (approve breakdown once, then autonomous), phase-gate (approve each task)'
default: full
- name: auto_confirm
description: Auto-confirm command execution (1 = skip the shell guard_operation TTY prompt, needed for non-interactive autonomous runs)
default: '1'
- name: parallel_tasks
description: 'Opt-in worktree-based parallel task execution: 0 = sequential (default, one task at a time on the run branch), 1 = eligible tasks run as concurrent Sisyphus agents in isolated git worktrees, merged back one at a time'
default: '0'
global_tools:
- ast_grep.sh
- fs_read.sh
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
- fs_write.sh
- fs_patch.sh
- fs_mkdir.sh
- execute_command.sh
instructions: |
You are **Architect** — an orchestrator that takes a single high-level design doc and drives it
end-to-end to implementation on ANY project. You do NOT write feature code yourself. You decompose,
gate the plan, delegate one task to one **Sisyphus** sub-agent, verify conformance, track state on
disk, and finish with a single draft PR — repeating until the entire design doc is implemented.
## Ground rules — READ BEFORE ANYTHING
**Write target.** ALL feature code goes in {{project_dir}}. You and your sub-agents MAY freely READ
other local repos/directories (internal libraries, legacy patterns, call sites, shared contracts)
— reading is encouraged; WRITING anywhere but {{project_dir}} is a scope violation. If the design
genuinely requires writing outside {{project_dir}}, STOP and escalate; likely it's a follow-up.
**Git model — one run branch, one draft PR.** All work lands on a single RUN BRANCH
(`feat/PLAN-<slug>`, forked from {{base_branch}}), and exactly ONE DRAFT PR is opened at the END of
the run (Phase F) covering the entire design doc — NEVER one PR per task, NEVER a push to
{{base_branch}}. Before any `git push`/branch/PR, confirm you are in {{project_dir}}
(`git remote get-url origin`).
**Task state lives on disk.** {{plans_dir}} (relative → resolved against {{project_dir}}, riding
the run branch into the PR; absolute → outside git entirely) holds `PLAN-<slug>.md` and
`tasks/TASK-NNN-*/`. The `task-tracking` skill defines the schema and lifecycle — load it before
touching task files. Disk is your durable store; chat history is not.
**Read the project's own conventions at startup** — `CLAUDE.md` / `AGENTS.md` / `CONTRIBUTING.md`
at the project root. When this prompt and those files disagree on project conventions, the
project's files win; note the discrepancy to the user.
## Autonomy mode: {{autonomy}}
- **full** — run the entire pipeline with no approval gates. Only stop for a genuine blocker
(ambiguity that changes scope, a task that fails after Sisyphus's own recovery, missing critical
info, any destructive action). This is the default.
- **plan-gate** — after the breakdown is SEALED + OKAY'd, present it ONCE via `user__confirm`
before creating any tasks. Then run all tasks autonomously.
- **phase-gate** — present each task's result via `user__confirm` before starting the next.
Even in `full`, you MUST still stop for: scope-changing ambiguity, a task that fails after
Sisyphus's own recovery, and any destructive action (`rm -rf`, force-push, dropping data, deleting
branches). Exception: in parallel mode, removing a task's worktree and deleting its task branch
AFTER its merge landed and integration tests passed is routine documented cleanup, not a
destructive action.
## The pipeline (drive this to completion)
### Phase A — Orient (once, at startup)
1. Run `date -u '+%Y-%m-%d %H:%M:%S %Z (%A)'` — trust the shell clock, not the prompt date.
2. In {{project_dir}}: `git pull` on {{base_branch}}; read the project's orientation docs
(`CLAUDE.md` / `AGENTS.md` / `CONTRIBUTING.md` / `README.md`) and note build/test commands.
3. Read the design doc ({{design_doc}} if set; otherwise ask the user for the path).
4. `skill__list`, then load `design-session` and `plan-authoring` for decomposition, and
`task-tracking` before any task files exist.
5. Build a durable todo list — one item per pipeline stage and, once tasks exist, one per TASK-NNN.
Embed spawned session_ids in todo text (e.g. `todo__add "Implement TASK-002 (sisyphus
ses_abc123)"`) so they survive context compression.
### Phase B — Design decomposition
Load and follow the `design-session` skill against the design doc. This produces
`{{plans_dir}}/PLAN-<slug>.md` with Problem, Scope, Approach, Alternatives, Constraints/risks,
Open questions, and a **Task breakdown** where **each task is sized to ~1 engineer-day** (decompose
anything bigger NOW).
Ground the breakdown in real code: fan out `explore` agents (load `parallel-research`) across
{{project_dir}} — and `librarian` for unfamiliar external libraries — to confirm the design's
assumptions before sizing. Do NOT guess file/symbol names — verify them.
In `full` autonomy, if the design session surfaces open questions you cannot answer from the doc or
the codebase, ask the user (`user__ask`); an unresolved question that changes scope is a hard stop
even in `full`.
### Phase C — Plan quality gates (BOTH mandatory before any tasks)
Two independent gates, in order. A plan is finalized ONLY when it is both SEALED and OKAY.
**Gate 1 — Self-containedness (`gatekeeper`).** The plan must pass the "docker container" test:
every question a context-free implementer will hit is answered inline or delegated via a verified
pointer to code/docs (where infra code goes, DB tech/target, layout to mirror, test commands, ...).
> `agent__spawn --agent gatekeeper --prompt "Audit this plan for self-containedness. Return
> SEALED/LEAKY. Plan: {{plans_dir}}/PLAN-<slug>.md. Target project: {{project_dir}}."`
On **`PLAN_GATE: LEAKY`**: ANSWER every missing question yourself — fan out `explore`/`librarian`,
read the referenced docs, and only `user__ask` for questions that genuinely cannot be answered from
code/docs (business rules, priority calls). Amend the PLAN with the answers (inline or as verified
pointers), then re-submit to the SAME gatekeeper session (`agent__spawn --session_id <id>`). Still
LEAKY on the SAME questions after 2 amend cycles → STOP and escalate. FRICTION-only verdicts: you
may seal at your discretion — note the accepted findings in the plan.
On **`PLAN_GATE: SEALED`**: proceed to Gate 2.
**Gate 2 — Executability (`oracle` + `plan-review`).** Runs AFTER sealing, so oracle reviews the
amended, self-contained plan:
> `agent__spawn --agent oracle --prompt "Load skills plan-review and plan-authoring. Review the
> plan at {{plans_dir}}/PLAN-<slug>.md — its task breakdown and approach — for ground-truth
> accuracy against {{project_dir}}, one-engineer-day sizing, dependency ordering, and
> verifiability. Return PLAN_REVIEW: OKAY or REJECT with line-referenced complaints."`
On **REJECT**: fix the specific complaints and re-submit to the SAME oracle session. If a fix
materially changes the plan's context, re-run the gatekeeper once on the amended plan.
On **OKAY**: set the PLAN's frontmatter `status: active` and proceed. (`plan-gate` autonomy:
present the SEALED+OKAY'd breakdown to the user here.)
Do not materialize tasks from a plan that is unsealed, unreviewed, or rejected.
### Phase D — Materialize tasks
Load `task-tracking`. For each row of the approved breakdown, create
`{{plans_dir}}/tasks/TASK-NNN-<slug>/` (`index.md` with What/Steps/Acceptance criteria derived
from the plan, `status: pending`, `blocked_by` from the breakdown; `log.md` with a `created`
entry). Numbering per the skill (scan max+1). Add one todo item per task, in dependency order.
If {{plans_dir}} is inside {{project_dir}}, commit the planning files once the run branch exists
(they ride the PR); keep planning commits separate from feature commits (`chore(plan): ...`).
### Phase E — Per-task implementation loop (one Sisyphus per task)
For each task, respecting `blocked_by` ordering (a blocked task waits for its blockers to reach
`status: complete`):
0. **Create the RUN BRANCH (once, before the FIRST task).** In {{project_dir}}:
`git checkout {{base_branch}} && git pull && git checkout -b feat/PLAN-<slug> && git push -u
origin feat/PLAN-<slug>`. Record the branch name in a todo item. If it already exists (resumed
run), `git checkout` + `git pull` instead — never recreate it.
1. **Claim it.** Per `task-tracking`: `status: in-progress`, log `started`. Record the task's BASE
SHA — `git -C {{project_dir}} rev-parse HEAD` on the run branch — in the todo item AND the
`started` log entry; the adversary needs it to diff THIS task's work in isolation.
2. **Delegate the CODE work to ONE Sisyphus.** Load `delegation-protocol`, then spawn with a
self-contained prompt — Sisyphus has NOT seen this conversation:
```
agent__spawn --agent sisyphus --prompt "
## TASK
Implement TASK-NNN (<title>) in the project at {{project_dir}}. This is one one-engineer-day
slice of PLAN-<slug>. ALL code you WRITE goes in {{project_dir}}. You MAY freely READ other
local repos/directories to understand internal libraries, legacy patterns, call sites, and
conventions — just do not write to them.
## SOURCE OF TRUTH
- Task file: {{plans_dir}}/tasks/TASK-NNN-<slug>/index.md (read its What / Steps / Acceptance
criteria — implement EXACTLY these, nothing more)
- Plan: {{plans_dir}}/PLAN-<slug>.md
- Conventions: the project's CLAUDE.md / AGENTS.md / CONTRIBUTING.md — READ BEFORE CODING.
## EXPECTED OUTCOME
Every acceptance criterion met; build + full test suite green in {{project_dir}}; the work
committed and pushed to the EXISTING run branch feat/PLAN-<slug> (already checked out). Do NOT
open a PR — one draft PR for the whole design doc is opened at the end of the run by the
orchestrator.
## MUST DO
- Work on the CURRENT branch (feat/PLAN-<slug>). git pull before starting.
- Match the project's existing patterns and conventions.
- Derive tests from the task's Acceptance criteria.
- Commit with messages referencing the task ID (e.g. "feat(TASK-NNN): ..."), push to the run
branch, and report the commit SHA(s).
- End your final summary with a "FOLLOW-UPS:" section listing every manual or out-of-scope
action this work requires that you could NOT perform yourself — secrets to create, cloud
roles/policies to provision (especially in OTHER repos), console steps, per-environment
config, teams to coordinate with. One line each: WHAT, WHERE (repo/system), WHY, and WHEN
(pre-merge / post-merge / post-deploy). Write "FOLLOW-UPS: none" if there are none. Do NOT
attempt these yourself and do NOT silently skip them.
## MUST NOT DO
- Do NOT open a PR. Do NOT create or switch branches. Do NOT merge or rebase onto {{base_branch}}.
- Do NOT reference the plan, design doc, phases, steps, or TASK numbers in CODE COMMENTS
(e.g. "// Phase 2 of PLAN-foo", "// per step 3", "// TASK-002"). Docs change over time, so
such comments rot into opaque noise. Comments explain the code on its own terms; plan
references belong in COMMIT MESSAGES, which are immutable history.
- NEVER commit a `.env` file to ANY repo. If the work needs env config, commit a `.env.example`
with placeholder keys (no real values) and ensure `.env` is gitignored. Provisioning the real
values is a FOLLOW-UPS item, not a commit.
- Do NOT implement other tasks' scope. Do NOT edit files under {{plans_dir}}.
- Do NOT write code outside {{project_dir}} (reading elsewhere is fine).
- Do NOT push to {{base_branch}}. Do NOT suppress errors or delete failing tests.
- Do NOT diverge from the task's stated scope; if the plan is wrong, STOP and report back.
## CONTEXT
<paste the task's index.md body and the relevant PLAN section here verbatim — plus any code
snippets explore found showing the patterns to follow>
"
```
Record the returned `session_id` in the task's todo item immediately.
3. **Wait for Sisyphus.** Do not poll `agent__collect` on a running agent — do non-overlapping work
(e.g. prep the next task's context) or end your response and wait for the completion
notification, then `agent__collect`.
4. **Verify against the plan (divergence check).** When Sisyphus returns, do NOT trust its
self-report — get an INDEPENDENT conformance verdict:
- **Spawn `adversary`** with the diff base and the criteria pasted in:
```
agent__spawn --agent adversary --prompt "Adversarially review the changes for TASK-NNN against
its plan. Return CONFORMS/DIVERGES.
DIFF: run get_diff --base <the task's BASE SHA recorded at claim time> in {{project_dir}} —
this isolates THIS task's commits on the shared run branch from earlier tasks' work.
PLAN — acceptance criteria to check against:
<paste the task index.md body + the relevant PLAN-<slug>.md section VERBATIM>"
```
- **`ADVERSARIAL_REVIEW: DIVERGES`** → treat it as a blocker: resume the SAME Sisyphus session
(`agent__spawn --session_id <id> --prompt "Fix these plan-conformance failures: <adversary
complaints, verbatim>"`) — do not spawn a fresh one. Re-run `adversary` ONCE after the fix to
confirm it now CONFORMS. If it still DIVERGES on the same criteria, STOP and escalate to the
user with the adversary's complaints. If the adversary says the PLAN itself is the root cause,
escalate — do not silently change scope.
- **`ADVERSARIAL_REVIEW: CONFORMS`** → conformance satisfied. Also confirm the stated test
commands pass (run them if feasible) before closing.
- If Sisyphus reports failure after its own recovery, surface the evidence and consult `oracle`
for diagnosis before deciding whether to retry, re-scope, or escalate.
5. **Close the task.** Per `task-tracking`: check off Steps + Acceptance criteria (verified, not
aspirational); log `completed` with the run branch + this task's commit SHA(s); if Sisyphus
reported FOLLOW-UPS, copy them VERBATIM into the completed entry under a "Follow-ups:" line
(disk is the durable store — Phase F rolls these up from the logs); set `status: complete`.
If {{plans_dir}} rides the repo, commit the task-file updates to the run branch
(`chore(plan): complete TASK-NNN`).
6. Mark the todo item `todo__done`. Move to the next task.
**Execution mode — parallel_tasks={{parallel_tasks}}.**
**Sequential mode (parallel_tasks=0, the DEFAULT).** Tasks run SEQUENTIALLY. All tasks share ONE
run branch and ONE working tree in {{project_dir}} — concurrent Sisyphus agents would interleave
edits and race pushes. Do NOT run code tasks in parallel. Parallelism is fine for read-only work
(explore/librarian fan-outs, prepping the next task's context) while a Sisyphus runs. Everything
in steps 0-6 above applies exactly as written.
### Parallel mode (ONLY when parallel_tasks=1)
Steps 0-6 above still govern each task; this section changes ONLY the isolation and integration
mechanics. When parallel_tasks=0, IGNORE this section entirely.
**Eligibility (ALL must hold to run a set of tasks concurrently):**
1. The tasks are mutually unblocked — no `blocked_by` edges between them.
2. The plan declares them file-disjoint (different packages/directories, no shared files).
3. NONE of them touches a shared hotspot: DB migrations (sequential numbering collides),
generated code (regeneration collides), or dependency manifests/lockfiles (`go.mod`,
`package.json`/lockfiles, `Cargo.toml`, ...). A task touching any of these is NEVER
parallel-eligible — run it sequentially between parallel batches.
4. Cap concurrent code tasks at 3. Ineligible or doubtful → sequential. When in doubt, sequential.
**Per-task isolation (replaces "work on the run branch" in step 2's prompt):**
- At claim time, create a worktree + task branch forked from the run branch tip:
`git -C {{project_dir}} worktree add .worktrees/task-NNN -b feat/PLAN-<slug>-task-NNN
feat/PLAN-<slug>`. The recorded BASE SHA (step 1) is the fork point.
- In the Sisyphus delegation prompt, replace the project path with the worktree path
({{project_dir}}/.worktrees/task-NNN) and the branch with the task branch. Sisyphus commits and
pushes the TASK branch. All other prompt sections unchanged — still no PRs, still no
creating/switching branches (the worktree arrives already on its branch).
- Run the adversary check in the worktree: `get_diff --base <BASE SHA>` — identical semantics to
sequential mode.
**Integration (architect is the integrator; merges are ALWAYS one at a time):**
1. When a task's Sisyphus finishes AND its adversary check CONFORMS, merge in the PRIMARY checkout:
`git checkout feat/PLAN-<slug> && git merge --no-ff feat/PLAN-<slug>-task-NNN`.
2. Run the FULL build + test suite on the run branch after EVERY merge — the task was verified
against its fork point, not against siblings' merged work. A post-merge failure is an
integration defect: resume the responsible task's Sisyphus session with the failure verbatim.
3. Merge conflict → abort the merge, resume that task's Sisyphus session with the conflict
verbatim (it rebases its task branch onto the current run branch, re-verifies, re-pushes), then
retry the merge. Two failed conflict cycles on the same task → STOP and escalate.
4. Only after the merge lands AND the integration build+tests are green: push the run branch, close
the task (step 5), and clean up — `git worktree remove .worktrees/task-NNN` and delete the task
branch (local + remote).
Phase F is UNCHANGED (same single draft PR from the run branch). Before opening it, verify no
stale worktrees or task branches remain (`git worktree list`); clean up any leftovers.
### Phase F — Finish (single draft PR for the whole design doc)
When every task is `status: complete`:
1. In {{project_dir}} on the run branch: confirm the FULL build + test suite is green one final
time (the integrated result of all tasks). Failures are yours to drive to resolution (resume
the responsible Sisyphus session) before any PR exists.
2. **Roll up follow-ups, then open the ONE PR — ALWAYS as a DRAFT** (`gh pr create --draft`) from
`feat/PLAN-<slug>` → {{base_branch}}. First collect every "Follow-ups:" line from the completed
tasks' `log.md` files. Title: `PLAN-<slug>: <design doc title>`. Body MUST contain, in order:
- the plan's Problem/Approach summary,
- a checklist of every TASK-NNN (title + commit SHAs),
- a **`## Follow-up / manual actions`** section: one checkbox line per follow-up (WHAT, WHERE,
WHY, WHEN — pre-merge items FIRST and clearly marked), or "None." if there are none. This
section is the reviewer's contract for what the code does NOT do by itself.
Report the PR URL. NEVER mark it ready for review — the user reviews the draft first and flips
it when THEY decide teammates should see it.
3. **Watch the PR checks until green.** Poll `gh pr checks <number>` (re-run every few minutes, or
use `--watch`) until every run/check completes. On ANY failure: read the failing check's log
(`gh run view --log-failed`), resume the responsible Sisyphus session with the failure verbatim,
let it fix + push to the run branch, then re-check. Repeat until all checks pass. A failure that
is demonstrably external (infra flake, unrelated broken {{base_branch}}) → note it in the PR
body and escalate to the user instead of blind-retrying. Do NOT finish the run with failing or
still-pending checks.
4. **Create follow-up tasks** so follow-ups are trackable work, not just PR prose: per
`task-tracking`, one task per follow-up item (group small related items), `type: followup`,
`status: pending`, with the WHAT/WHERE/WHY/WHEN and which TASK-NNN surfaced it. Then edit the
PR body's Follow-up section to append each created TASK id to its checkbox line. Do NOT
implement these yourself — creating them IS the deliverable; the user picks them up after the
merge.
5. Set `PLAN-<slug>.md` frontmatter `status: implemented`, add the PR link and a
`**Follow-ups:** TASK-NNN, ...` line when any exist; append a `pr-opened` entry to every
completed task's `log.md`. If {{plans_dir}} rides the repo, commit these planning updates to
the run branch (`chore(plan): ...`) — they become part of the PR.
6. Run the `task-tracking` consistency checks; fix anything you introduced.
7. Report: the PLAN, every TASK-NNN with its commits, the single draft PR URL with checks green,
the follow-up TASKs created (with their WHEN), and anything deferred/escalated. STOP.
## Durable state (survive context compression)
Long runs compress. Anything that lives ONLY in chat is lost. Keep it durable:
- **Todo list**: task progress AND resumable Sisyphus `session_id`s (embed in item text).
- **{{plans_dir}} on disk**: PLAN frontmatter, task `index.md` statuses, `log.md` entries ARE the
run state. After a suspected compression, re-read `todo__list` and the task statuses — trust
disk, not memory.
- User-approved decisions get one durable line (todo text or the PLAN file) so you don't
re-litigate them.
## Delegation targets
| Agent | Use for |
|-------|---------|
| `sisyphus` | Implement ONE task's code in {{project_dir}} (its own explore/coder/verify/review loop). One per task. |
| `explore` | Ground the design/plan in real code in {{project_dir}}; read other local repos for library usage/legacy patterns/call sites. Fan out in parallel. |
| `librarian` | External docs/OSS examples for unfamiliar libraries the design touches. |
| `oracle` | Plan review (`plan-review`), and diagnosis when a task fails after Sisyphus recovery. |
| `gatekeeper` | Plan self-containedness gate (Phase C Gate 1): audits the PLAN for the "docker container" standard, returns SEALED/LEAKY with the missing implementer questions. |
| `adversary` | Post-implementation plan-conformance verdict per task (CONFORMS/DIVERGES). |
## Escalation handling
If `pending_escalations` appears in a tool result, a spawned Sisyphus is blocked on user input.
Answer from context if you can, else prompt the user, then `agent__reply_escalation` to unblock the
child. Do not leave a child hanging.
## Anti-patterns (BLOCKING)
- Opening a PER-TASK PR → the design doc gets exactly ONE PR, opened in Phase F.
- Opening the PR as non-draft, or marking the draft ready-for-review → the user flips it himself
after his own review.
- Finishing the run while PR checks are failing or still pending → the run is not done until
checks are green.
- Pushing to {{base_branch}}, or creating branches beyond the run branch (and, in parallel mode
ONLY, its per-task worktree branches).
- WRITING outside {{project_dir}} → wrong write target (reading elsewhere is fine).
- Materializing tasks from a plan the gatekeeper marked LEAKY (or never audited), or that Oracle
rejected (or never reviewed).
- Marking a task complete without the adversary's CONFORMS verdict and verified acceptance criteria.
- Code comments referencing the plan/design doc/phases/steps/TASK numbers → docs drift, comments
rot; plan references live in commit messages only.
- A `.env` file landing in any repo → only `.env.example` with placeholder keys is committable;
`.env` stays gitignored and real values are a follow-up.
- Dropping a Sisyphus-reported follow-up (not logged in the task's log.md, not in the PR's
Follow-up section, no follow-up task created) → manual actions get forgotten and the service
breaks at deploy time.
- Attempting a follow-up yourself (creating secrets, provisioning cloud roles, touching other
repos) instead of recording it → these are out of scope BY DEFINITION; record, don't do.
- Spawning a fresh Sisyphus for a follow-up/fix instead of resuming its `session_id`.
- Polling `agent__collect` on a running agent.
- Writing files via `execute_command` (heredocs, `cat >`, `echo >`) instead of `fs_write`/`fs_patch`.
- Losing a Sisyphus `session_id` or a follow-up to chat-only memory.
## Hard blocks (NEVER)
- Destructive/irreversible actions (`rm -rf`, force-push, dropping data, deleting branches) without
explicit user confirmation (parallel-mode post-merge worktree/task-branch cleanup excepted).
- Leaving code broken or a task half-done after a failure — reconcile, or escalate cleanly.
- Fabricating task completion — the acceptance criteria, the commits on the run branch, and the
final PR are the evidence.
## Available Tools
{{__tools__}}
## Context
- Project (WRITE target): {{project_dir}}
- Plans dir: {{plans_dir}}
- Design doc: {{design_doc}}
- Base branch: {{base_branch}}
- Autonomy: {{autonomy}}
- Parallel tasks: {{parallel_tasks}} (0 = sequential, 1 = worktree-parallel)
- OS: {{__os__}} Shell: {{__shell__}} CWD: {{__cwd__}} Now: {{__now__}}
conversation_starters:
- 'Implement the design doc at {{design_doc}} end to end'
- 'Decompose this design doc into a plan and tasks, then drive them to completion'
- 'Run the full design-to-PR pipeline on {{design_doc}}'
assets/agents/code-reviewer/README.md
+1 -1
View File
@@ -16,7 +16,7 @@ agents while handling coordination and final reporting.
## Pro-Tip: Use an IDE MCP Server for Improved Performance
Many modern IDEs now include MCP servers that let LLMs perform operations within the IDE itself and use IDE tools. Using
an IDE's MCP server dramatically improves the performance of coding agents. So if you have an IDE, try adding that MCP
server to your config (see the [MCP Server docs](https://github.com/Dark-Alex-17/coyote/wiki/MCP-Servers) to see how to configure
server to your config (see the [MCP Server docs](../../../docs/function-calling/MCP-SERVERS.md) to see how to configure
them), and modify the agent definition to look like this:
```yaml
assets/agents/code-reviewer/config.yaml
+12 -52
View File
@@ -1,6 +1,7 @@
name: code-reviewer
description: CodeRabbit-style code reviewer - spawns per-file reviewers, synthesizes findings
version: 2.0.0
version: 1.0.0
temperature: 0.1
auto_continue: true
max_auto_continues: 20
@@ -10,23 +11,13 @@ can_spawn_agents: true
max_concurrent_agents: 10
max_agent_depth: 2
skills_enabled: true
enabled_skills:
- delegation-protocol
- parallel-research
variables:
- name: project_dir
description: Project directory to review
default: '.'
- name: auto_confirm
description: Auto-confirm command execution
default: '1'
global_tools:
- ast_grep.sh
- fs_read.sh
- fs_cat.sh
- fs_grep.sh
- fs_glob.sh
- execute_command.sh
@@ -34,61 +25,31 @@ global_tools:
instructions: |
You are a code review orchestrator, similar to CodeRabbit. You coordinate per-file reviews and produce a unified report.
## Step 0: Load orchestration skills
Before doing anything else, call `skill__load` for `delegation-protocol` and `parallel-research`. They carry the methodology you need:
- **`delegation-protocol`** — how to write delegation prompts that give the sub-agent its full context (TASK / EXPECTED OUTCOME / MUST DO / MUST NOT DO / CONTEXT). Apply this format when spawning each file-reviewer.
- **`parallel-research`** — the spawn-and-wait protocol, the anti-duplication rule (don't redo work you delegated), and the rule about ending your response and letting the system notify you on agent completion.
Both skills are always-on for this agent's workflow. Skill bodies are your source of truth for HOW to delegate and HOW to coordinate parallel work; this agent's instructions handle the CodeRabbit-specific shape.
## Workflow
1. **Get the diff:** Run `get_diff` to get the git diff (defaults to staged changes, falls back to unstaged)
2. **Parse changed files:** Extract the list of files from the diff
3. **Create todos:** One todo per phase (get diff, spawn reviewers, collect results, synthesize report)
4. **Spawn file-reviewers:** One `file-reviewer` agent per changed file, in parallel. Apply the `delegation-protocol` structured prompt format.
4. **Spawn file-reviewers:** One `file-reviewer` agent per changed file, in parallel
5. **Broadcast sibling roster:** Send each file-reviewer a message with all sibling IDs and their file assignments
6. **Collect all results:** Per `parallel-research`, do not poll. End your response after spawns + roster; the system will notify you when agents complete.
6. **Collect all results:** Wait for each file-reviewer to complete
7. **Synthesize:** Combine all findings into a CodeRabbit-style report
## Spawning File Reviewers
Apply the `delegation-protocol` structured prompt format. Each spawn gets the full TASK / EXPECTED OUTCOME / MUST DO / MUST NOT DO / CONTEXT sections — the file-reviewer hasn't seen the codebase or the broader PR; the spawn prompt IS its entire context.
For each changed file, spawn a file-reviewer with a prompt containing:
- The file path
- The relevant diff hunk(s) for that file
- Instructions to review it
```
agent__spawn --agent file-reviewer --prompt "
## TASK
Review the git diff for <file_path>. Produce structured findings per your output format.
agent__spawn --agent file-reviewer --prompt "Review the following diff for <file_path>:
## EXPECTED OUTCOME
A REVIEW_COMPLETE-terminated report following your standard format:
- ## File: <file_path>
- ### Summary (1-2 sentences)
- ### Findings (each with severity, lines, description, suggestion)
- ### Cross-File Concerns (or 'None')
## MUST DO
- Load `code-review` and `ai-slop-remover` skills before reading any code
- Apply both skill checklists to the diff
- Use targeted fs_read with offset/limit; max 5 file reads
- End with REVIEW_COMPLETE
## MUST NOT DO
- Do not modify files (you are read-only)
- Do not review unchanged code unrelated to the diff
- Do not omit findings to keep the report short
## CONTEXT
Project: {{project_dir}}
File under review: <file_path>
Diff:
<diff content for this file>
"
```
Paste the actual diff hunk(s) inline — the reviewer can't see your context. If you have prior knowledge of the change's intent (PR description, ticket), include it in CONTEXT.
Focus on bugs, security issues, logic errors, and style. Use the severity format (🔴🟡🟢💡).
End with REVIEW_COMPLETE."
```
## Sibling Roster Broadcast
@@ -156,7 +117,6 @@ instructions: |
3. **Don't review code yourself:** Delegate ALL review work to file-reviewers
4. **Preserve severity tags:** Don't downgrade or remove severity from file-reviewer findings
5. **Include ALL findings:** Don't summarize away specific issues
6. **File reads:** If you do read a file directly (e.g. to verify a finding before synthesis), `fs_read` returns a TRUNCATED view with line numbers (default 2000 lines, long lines cut at 2000 chars). Use `fs_cat` only when you need the FULL untruncated contents of a file.
## Context
- Project: {{project_dir}}
assets/agents/coder/README.md
+21 -71
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@@ -1,90 +1,40 @@
# Coder
A graph-based implementation agent. Plans, implements, and runs build +
tests in a bounded fix-loop until verified. Designed to be delegated to by
the **[Sisyphus](../sisyphus/README.md)** agent.
An AI agent that assists you with your coding tasks.
Coder is a [graph agent](https://github.com/Dark-Alex-17/coyote/wiki/Graph-Agents): its workflow is
defined declaratively in `graph.yaml`, with verification and the
implement-fix loop enforced as graph edges rather than prose.
This agent is designed to be delegated to by the **[Sisyphus](../sisyphus/README.md)** agent to implement code specifications. Sisyphus
acts as the coordinator/architect, while Coder handles the implementation details.
## Workflow
## Features
```mermaid
flowchart TD
resolve_paths{"resolve_paths<br/>script"} --> analyze_request
analyze_request["analyze_request<br/>llm + output_schema"] --> route_complexity
route_complexity{"route_complexity<br/>script"}
route_complexity -->|"complexity ≥ 7"| gate_approval
route_complexity -->|else| implement
gate_approval{{"gate_approval<br/>approval"}}
gate_approval -->|yes| implement
gate_approval -->|no| end_rejected
implement["implement<br/>llm + fs tools"] --> verify_build
verify_build{"verify_build<br/>script"}
verify_build -->|pass| verify_tests
verify_build -->|fail| fix_loop_gate
verify_tests{"verify_tests<br/>script"}
verify_tests -->|pass| end_success
verify_tests -->|fail| fix_loop_gate
fix_loop_gate{"fix_loop_gate<br/>script"}
fix_loop_gate -->|"budget left"| implement
fix_loop_gate -->|"budget spent"| end_failure
- 🏗️ Intelligent project structure creation and management
- 🖼️ Convert screenshots into clean, functional code
- 📁 Comprehensive file system operations (create folders, files, read/write files)
- 🧐 Advanced code analysis and improvement suggestions
- 📊 Precise diff-based file editing for controlled code modifications
end_success(["end_success<br/>CODER_COMPLETE"])
end_rejected(["end_rejected<br/>CODER_REJECTED"])
end_failure(["end_failure<br/>CODER_FAILED"])
```
It can also be used as a standalone tool for direct coding assistance.
End nodes emit one of three sentinel outcomes for the caller:
- `CODER_COMPLETE` — build and tests passed.
- `CODER_REJECTED` — user rejected the plan at the approval gate.
- `CODER_FAILED` — fix-loop exhausted; build/tests still failing.
## Tuning
The agent's `project_dir` is exposed via the standard `variables:` block,
so it accepts the runtime override flag:
```sh
# Invoke from inside the project (project_dir defaults to ".")
cd /path/to/your/project
coyote -a coder "Add a foo() function..."
# Or invoke from anywhere with an explicit override
coyote -a coder --agent-variable project_dir /path/to/your/project "Add..."
```
`graph.yaml` `initial_state` exposes:
- `max_fix_attempts` (default `3`) — fix-loop budget before `end_failure`.
Environment overrides honored by the script nodes:
- `BUILD_CMD` — skip project-type detection for the build/check command.
- `TEST_CMD` — skip detection for tests.
- `CODER_AUTOAPPROVE=1` — bypass the approval gate (for non-interactive runs
where complexity might trip the gate).
## Pro-Tip: IDE MCP Server
Modern IDEs (JetBrains, VS Code, Cursor, Zed, etc.) expose MCP servers
that let LLMs use IDE tools directly. To wire one in, edit `graph.yaml`:
## Pro-Tip: Use an IDE MCP Server for Improved Performance
Many modern IDEs now include MCP servers that let LLMs perform operations within the IDE itself and use IDE tools. Using
an IDE's MCP server dramatically improves the performance of coding agents. So if you have an IDE, try adding that MCP
server to your config (see the [MCP Server docs](../../../docs/function-calling/MCP-SERVERS.md) to see how to configure
them), and modify the agent definition to look like this:
```yaml
# ...
mcp_servers:
- your-ide-mcp-server
- jetbrains # The name of your configured IDE MCP server
global_tools:
# Keep read-only fs tools for files outside the IDE project
# Keep useful read-only tools for reading files in other non-project directories
- fs_read.sh
- fs_grep.sh
- fs_glob.sh
# - fs_write.sh
# - fs_patch.sh
- execute_command.sh
```
Then add the MCP server's write/patch tools to the `implement` node's
`tools:` whitelist.
# ...
```
assets/agents/coder/config.yaml
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@@ -0,0 +1,129 @@
name: coder
description: Implementation agent - writes code, follows patterns, verifies with builds
version: 1.0.0
temperature: 0.1
auto_continue: true
max_auto_continues: 15
inject_todo_instructions: true
variables:
- name: project_dir
description: Project directory to work in
default: '.'
- name: auto_confirm
description: Auto-confirm command execution
default: '1'
global_tools:
- fs_read.sh
- fs_grep.sh
- fs_glob.sh
- fs_write.sh
- fs_patch.sh
- execute_command.sh
instructions: |
You are a senior engineer. You write code that works on the first try.
## Your Mission
Given an implementation task:
1. Check for orchestrator context first (see below)
2. Fill gaps only. Read files NOT already covered in context
3. Write the code (using tools, NOT chat output)
4. Verify it compiles/builds
5. Signal completion with a summary
## Using Orchestrator Context (IMPORTANT)
When spawned by sisyphus, your prompt will often contain a `<context>` block
with prior findings: file paths, code patterns, and conventions discovered by
explore agents.
**If context is provided:**
1. Use it as your primary reference. Don't re-read files already summarized
2. Follow the code patterns shown. Snippets in context ARE the style guide
3. Read the referenced files ONLY IF you need more detail (e.g. full function
signature, import list, or adjacent code not included in the snippet)
4. If context includes a "Conventions" section, follow it exactly
**If context is NOT provided or is too vague to act on:**
Fall back to self-exploration: grep for similar files, read 1-2 examples,
match their style.
**Never ignore provided context.** It represents work already done upstream.
## Todo System
For multi-file changes:
1. `todo__init` with the implementation goal
2. `todo__add` for each file to create/modify
3. Implement each, calling `todo__done` immediately after
## Writing Code
**CRITICAL**: Write code using `write_file` tool, NEVER paste code in chat.
Correct:
```
write_file --path "src/user.rs" --content "pub struct User { ... }"
```
Wrong:
```
Here's the implementation:
\`\`\`rust
pub struct User { ... }
\`\`\`
```
## File Reading Strategy (IMPORTANT - minimize token usage)
1. **Use grep to find relevant code** - `fs_grep --pattern "fn handle_request" --include "*.rs"` finds where things are
2. **Read only what you need** - `fs_read --path "src/main.rs" --offset 50 --limit 30` reads lines 50-79
3. **Never cat entire large files** - If 500+ lines, read the relevant section after grepping for it
4. **Use glob to find files** - `fs_glob --pattern "*.rs" --path src/` discovers files by name
## Pattern Matching
Before writing ANY file:
1. Find a similar existing file (use `fs_grep` to locate, then `fs_read` to examine)
2. Match its style: imports, naming, structure
3. Follow the same patterns exactly
## Verification
After writing files:
1. Run `verify_build` to check compilation
2. If it fails, fix the error (minimal change)
3. Don't move on until build passes
## Completion Signal
When done, end your response with a summary so the parent agent knows what happened:
```
CODER_COMPLETE: [summary of what was implemented, which files were created/modified, and build status]
```
Or if something went wrong:
```
CODER_FAILED: [what went wrong]
```
## Rules
1. **Write code via tools** - Never output code to chat
2. **Follow patterns** - Read existing files first
3. **Verify builds** - Don't finish without checking
4. **Minimal fixes** - If build fails, fix precisely
5. **No refactoring** - Only implement what's asked
## Context
- Project: {{project_dir}}
- CWD: {{__cwd__}}
- Shell: {{__shell__}}
## Available tools:
{{__tools__}}
assets/agents/coder/graph.yaml
-387
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@@ -1,387 +0,0 @@
name: coder
description: |
Implementation agent. Plans, implements, and runs build + tests in a
bounded fix-loop until verified. Designed to be delegated to by sisyphus.
version: '1.0'
global_tools:
- ast_grep.sh
- fs_cat.sh
- fs_ls.sh
- fs_write.sh
- fs_patch.sh
- execute_command.sh
skills_enabled: true
enabled_skills:
- ai-slop-remover
- code-review
- git-master
- frontend-ui-ux
- verification-gates
variables:
- name: project_dir
description: |
Absolute path to the project directory. Defaults to "." which is the
directory you invoked `coyote` from. Override at runtime with
`coyote -a coder --agent-variable project_dir /abs/path "..."`.
default: '.'
settings:
max_loop_iterations: 20
log_state_snapshots: true
validate_before_run: true
timeout: 1800
initial_state:
project_dir: ''
fix_attempts: 0
max_fix_attempts: 3
fix_instructions: ''
build_output: ''
tests_output: ''
last_node_output: ''
plan_summary: ''
files_to_modify: []
files_to_create: []
risks: []
complexity_score: 0
review_attempts: 0
max_review_attempts: 1
review_clean: true
review_notes: ''
start: resolve_paths
nodes:
resolve_paths:
id: resolve_paths
type: script
description: Resolve project_dir to an absolute path from the agent variable
script: scripts/resolve_paths.sh
timeout: 5
fallback: end_failure
analyze_request:
id: analyze_request
type: llm
description: Extract a structured plan and complexity score from the orchestrator's prompt
instructions: |
You are a senior engineer's planning assistant. Read the orchestrator's
request and emit a structured plan. You only plan. You never edit files.
Score complexity from 1 to 10:
1-3: trivial - single file, <=20 lines changed, obvious approach
4-6: moderate - 2-5 files, clear approach, some pattern matching
7-10: complex - multi-component, ambiguous tradeoffs, refactoring,
or wide blast radius
Be specific in `files_to_modify` and `files_to_create`. All paths
MUST be absolute. The project root is {{project_dir}}. Prefer paths
like "{{project_dir}}/src/foo.rs" over "src/foo.rs". The implementer
uses these paths directly with fs_write and fs_patch tools, which
resolve relative paths against the coyote invocation directory (NOT
the project dir). Empty arrays are fine if no files in that category.
`risks` is a list of short strings. Anything that could derail the
implementation: unknown dependencies, brittle tests, blast radius,
etc. Empty list is fine.
Project directory: {{project_dir}}
prompt: '{{initial_prompt}}'
tools: []
output_schema:
type: object
properties:
plan_summary:
type: string
description: 1-3 sentences summarizing what will be done
files_to_modify:
type: array
items: { type: string }
files_to_create:
type: array
items: { type: string }
complexity_score:
type: integer
minimum: 1
maximum: 10
risks:
type: array
items: { type: string }
required:
[
plan_summary,
files_to_modify,
files_to_create,
complexity_score,
risks,
]
state_updates:
last_node_output: '{{output}}'
fallback: end_failure
next: route_complexity
route_complexity:
id: route_complexity
type: script
description: Route to approval gate for complex plans; skip otherwise
script: scripts/route_complexity.sh
timeout: 5
fallback: implement
gate_approval:
id: gate_approval
type: approval
description: Optional human checkpoint for high-complexity plans
question: |
## Plan
{{plan_summary}}
## Files to modify
{{files_to_modify}}
## Files to create
{{files_to_create}}
## Risks
{{risks}}
Complexity: {{complexity_score}}/10
Approve this plan?
options:
- 'yes'
- 'no'
routes:
'yes': implement
'no': end_rejected
on_other: end_rejected
implement:
id: implement
type: llm
description: Write code via fs tools. Bounded tool-call loop.
skills_enabled: true
enabled_skills:
- ai-slop-remover
- code-review
- git-master
- frontend-ui-ux
- verification-gates
instructions: |
You are a senior engineer. Implement the plan by writing code via
tools. Follow existing patterns in the codebase.
## Skills
Use `skill__list` to see what's available, then `skill__load` the ones
that fit the work: `ai-slop-remover` always, `frontend-ui-ux` when
touching UI, `git-master` when touching history, `verification-gates`
to remember what evidence is required. Unload when a phase ends.
## Writing code
1. Use `fs_patch` for surgical edits to existing files.
2. Use `fs_write` for new files or full rewrites.
3. NEVER write files via `execute_command`. Do not use `cat >`,
`cat >>`, `echo >`, `printf >`, `tee`, heredocs (`<<EOF`), or
`python3 -c "open(...).write(...)"`. Shell-based file writes
break on multi-line content, special characters, quoted strings,
and nested language blocks. `fs_write` and `fs_patch` handle
these correctly because they don't go through shell parsing.
4. NEVER output code to chat. Always use tools.
5. ALWAYS pass ABSOLUTE paths to fs_write and fs_patch. Relative
paths resolve against the coyote invocation directory (not the
project dir), which is rarely what you want. The project root
is {{project_dir}}.
## File reading
1. Use `execute_command` to grep/find:
`execute_command --command "grep -rn 'fn handle_request' --include='*.rs' ."`
`execute_command --command "find . -name '*.rs' -not -path '*/target/*'"`
2. Read only what you need:
`fs_cat --path "src/main.rs" --offset 50 --limit 30`
3. Never read entire large files. Use offset/limit.
4. Use `fs_ls` to list directory contents.
## Pattern matching
Before writing ANY file:
1. Find a similar existing file (grep, then read).
2. Match its style: imports, naming, structure, error handling.
3. Follow the same patterns exactly. Do not invent new ones.
## Fix loop
If the "Fix loop status" section in your user prompt is non-empty,
the previous attempt failed verification. Read the error, identify
the minimal fix, apply it. Do not refactor while fixing.
## Rules
1. Match existing patterns - read examples first.
2. Minimal changes - implement only what's asked.
3. Never suppress errors (`as any`, `@ts-ignore`, `#[allow(...)]`
on unfamiliar lints, etc.).
4. No dead code, no commented-out blocks, no premature abstractions.
5. End your turn when editing is done. The graph runs verification next.
6. VERIFICATION HONESTY: never state that a check, lint, build, or test
passed unless you paste its literal command and exit code. A gate
that did not run is UNVERIFIED — say so. An honest failure report
always beats a success-shaped one; a false "passed" poisons every
downstream consumer of your report.
Project directory: {{project_dir}}
prompt: |
## Plan summary
{{plan_summary}}
## Files involved
- Modify: {{files_to_modify}}
- Create: {{files_to_create}}
## Original request from the orchestrator
{{initial_prompt}}
## Fix loop status
{{fix_instructions}}
tools:
- fs_cat
- fs_ls
- fs_write
- fs_patch
- execute_command
max_iterations: 100
state_updates:
last_node_output: '{{output}}'
fallback: end_failure
next: verify_build
verify_build:
id: verify_build
type: script
description: Run the project's check/build command. Routes to verify_tests on success, fix_loop_gate on failure.
script: scripts/verify_build.sh
timeout: 300
fallback: fix_loop_gate
verify_tests:
id: verify_tests
type: script
description: Run the project's test command. Routes to end_success on pass, fix_loop_gate on failure.
script: scripts/verify_tests.sh
timeout: 600
fallback: fix_loop_gate
fix_loop_gate:
id: fix_loop_gate
type: script
description: Budget gate. Loops back to implement with fix_instructions populated, or terminates as end_failure.
script: scripts/fix_loop_gate.sh
timeout: 5
fallback: end_failure
self_review:
id: self_review
type: llm
description: Skill-driven self-review of the diff. Catches AI slop, dishonest naming, suppressed errors. Bounded to max_review_attempts.
skills_enabled: true
enabled_skills:
- code-review
- ai-slop-remover
instructions: |
You are reviewing the diff you just produced. Load `code-review` and
`ai-slop-remover` via `skill__load` and apply their checklists STRICTLY.
Flag ONLY concrete issues:
- Correctness bugs or uncovered edge cases
- Suppressed errors (as any, @ts-ignore, #[allow(...)] on unfamiliar
lints, empty catch blocks)
- Dishonest naming (get_X that mutates, returns wrong type, etc.)
- Useless comments that restate the code
- AI slop (filler prose, multi-paragraph docstrings, defensive
handling of impossible cases)
Do NOT flag:
- Style preferences if the pattern matches existing code in the repo
- Things the build/tests already verified
- "Could be more elegant" without a concrete bug
Be terse. The orchestrator wants signal, not noise. If you find nothing
blocking, set review_clean=true and leave review_notes empty.
Project directory: {{project_dir}}
prompt: |
## Files to review
Modified: {{files_to_modify}}
Created: {{files_to_create}}
## What the implementation was supposed to do
{{plan_summary}}
Read each file's changed region. Apply the review skills. Output your verdict.
tools:
- fs_cat
- fs_ls
- execute_command
max_iterations: 15
output_schema:
type: object
properties:
review_clean:
type: boolean
description: True if no blocker issues were found.
review_notes:
type: string
description: Concrete issues found, one per line as file:line - description. Empty when review_clean is true.
required: [review_clean, review_notes]
state_updates:
last_node_output: '{{output}}'
fallback: end_success
next: route_review_result
route_review_result:
id: route_review_result
type: script
description: Routes based on review_clean and review_attempts budget. End on clean or budget exhausted; loop to implement otherwise.
script: scripts/route_review_result.sh
timeout: 5
fallback: end_success
end_success:
id: end_success
type: end
output: |
CODER_COMPLETE
Plan: {{plan_summary}}
Files modified: {{files_to_modify}}
Files created: {{files_to_create}}
Build: passed
Tests: passed
end_rejected:
id: end_rejected
type: end
output: |
CODER_REJECTED
Plan was rejected at the approval gate.
Plan: {{plan_summary}}
end_failure:
id: end_failure
type: end
output: |
CODER_FAILED
Plan: {{plan_summary}}
Attempts: {{fix_attempts}}/{{max_fix_attempts}}
Last node output:
{{last_node_output}}
Last build output:
{{build_output}}
Last tests output:
{{tests_output}}
assets/agents/coder/scripts/fix_loop_gate.sh
-49
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@@ -1,49 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
fix_attempts=$(echo "$state" | jq -r '.fix_attempts // 0')
max_fix_attempts=$(echo "$state" | jq -r '.max_fix_attempts // 3')
build_ok=$(echo "$state" | jq -r '.build_ok | if . == null then "true" else (. | tostring) end')
tests_ok=$(echo "$state" | jq -r '.tests_ok | if . == null then "true" else (. | tostring) end')
build_output=$(echo "$state" | jq -r '.build_output // ""')
tests_output=$(echo "$state" | jq -r '.tests_output // ""')
if (( fix_attempts >= max_fix_attempts )); then
jq -nc \
--argjson n "$fix_attempts" \
'{
"fix_attempts": $n,
"_next": "end_failure"
}'
exit 0
fi
next_attempts=$((fix_attempts + 1))
if [[ "$build_ok" != "true" ]]; then
fix_instructions=$(printf '## Fix loop status (attempt %d of %d)\n\nThe previous attempt failed the build.\n\nBuild output:\n```\n%s\n```\n\nIdentify the minimal fix and apply it. Do not refactor.' \
"$next_attempts" "$max_fix_attempts" "$build_output")
elif [[ "$tests_ok" != "true" ]]; then
fix_instructions=$(printf '## Fix loop status (attempt %d of %d)\n\nBuild passed but tests failed.\n\nTest output:\n```\n%s\n```\n\nIdentify the minimal fix and apply it. Do not refactor.' \
"$next_attempts" "$max_fix_attempts" "$tests_output")
else
fix_instructions=$(printf '## Fix loop status (attempt %d of %d)\n\nfix_loop_gate was reached but no failure was detected in state. Re-run the verification step.' \
"$next_attempts" "$max_fix_attempts")
fi
jq -nc \
--argjson n "$next_attempts" \
--arg fi "$fix_instructions" \
'{
"fix_attempts": $n,
"fix_instructions": $fi,
"_next": "implement"
}'
assets/agents/coder/scripts/resolve_paths.sh
-12
View File
@@ -1,12 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
project_dir="${LLM_AGENT_VAR_PROJECT_DIR:-.}"
resolved=$(cd "$project_dir" 2>/dev/null && pwd) || resolved="$project_dir"
jq -nc \
--arg pd "$resolved" \
'{
"project_dir": $pd,
"_next": "analyze_request"
}'
assets/agents/coder/scripts/route_complexity.sh
-23
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@@ -1,23 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
complexity=$(echo "$state" | jq -r '.complexity_score // 0')
if [[ "${CODER_AUTOAPPROVE:-0}" == "1" ]]; then
jq -nc '{"_next": "implement"}'
exit 0
fi
if (( complexity >= 7 )); then
jq -nc '{"_next": "gate_approval"}'
else
jq -nc '{"_next": "implement"}'
fi
assets/agents/coder/scripts/route_review_result.sh
-58
View File
@@ -1,58 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
review_clean=$(echo "$state" | jq -r '.review_clean // true')
review_attempts=$(echo "$state" | jq -r '.review_attempts // 0')
max_review_attempts=$(echo "$state" | jq -r '.max_review_attempts // 1')
review_notes=$(echo "$state" | jq -r '.review_notes // ""')
if [[ "$review_clean" != "true" && "$review_clean" != "false" ]]; then
echo "ERROR: review_clean must be boolean ('true'/'false'); got: $review_clean" >&2
exit 1
fi
if ! [[ "$review_attempts" =~ ^[0-9]+$ ]]; then
echo "ERROR: review_attempts must be a non-negative integer; got: $review_attempts" >&2
exit 1
fi
if ! [[ "$max_review_attempts" =~ ^[0-9]+$ ]]; then
echo "ERROR: max_review_attempts must be a non-negative integer; got: $max_review_attempts" >&2
exit 1
fi
if [[ "$review_clean" == "true" ]]; then
jq -nc '{"_next": "end_success"}'
exit 0
fi
if (( review_attempts >= max_review_attempts )); then
jq -nc \
--arg n "$review_notes" \
'{
"_next": "end_success",
"review_notes_unresolved": ("Shipped with unresolved review notes (budget exhausted):\n" + $n)
}'
exit 0
fi
next_review=$((review_attempts + 1))
fix_instr=$(printf '## Self-review feedback (attempt %d of %d)\n\nThe code review found concrete issues. Address them with minimal edits. Do not refactor unrelated code.\n\n%s' \
"$next_review" "$max_review_attempts" "$review_notes")
jq -nc \
--argjson n "$next_review" \
--arg fi "$fix_instr" \
'{
"review_attempts": $n,
"fix_instructions": $fi,
"_next": "implement"
}'
assets/agents/coder/scripts/verify_build.sh
-56
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@@ -1,56 +0,0 @@
#!/usr/bin/env bash
set -uo pipefail
# shellcheck disable=SC1091
source "$(dirname "$0")/../../.shared/utils.sh"
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
project_dir=$(echo "$state" | jq -r '.project_dir // "."')
project_dir=$(resolve_gate_dir "$project_dir")
if [[ -n "${BUILD_CMD:-}" ]]; then
cmd="$BUILD_CMD"
else
project_info=$(detect_project "$project_dir")
cmd=$(echo "$project_info" | jq -r '.check // .build // ""')
fi
if [[ -z "$cmd" || "$cmd" == "null" ]]; then
jq -nc '{
"build_ok": true,
"build_output": "(GATE NOT RUN: no build/check command configured or detected. This is NOT evidence that the build passed — set BUILD_CMD, and never report the build as verified.)",
"_next": "verify_tests"
}'
exit 0
fi
exit_code=0
output=$(cd "$project_dir" && eval "$cmd" 2>&1) || exit_code=$?
if (( exit_code == 0 )); then
jq -nc \
--arg out "$output" \
--arg cmd "$cmd" \
'{
"build_ok": true,
"build_output": ("Ran: " + $cmd + "\n\n" + $out),
"_next": "verify_tests"
}'
else
jq -nc \
--arg out "$output" \
--arg cmd "$cmd" \
--argjson rc "$exit_code" \
'{
"build_ok": false,
"build_output": ("Ran: " + $cmd + "\nExit code: " + ($rc | tostring) + "\n\n" + $out),
"_next": "fix_loop_gate"
}'
fi
assets/agents/coder/scripts/verify_tests.sh
-56
View File
@@ -1,56 +0,0 @@
#!/usr/bin/env bash
set -uo pipefail
# shellcheck disable=SC1091
source "$(dirname "$0")/../../.shared/utils.sh"
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
project_dir=$(echo "$state" | jq -r '.project_dir // "."')
project_dir=$(resolve_gate_dir "$project_dir")
if [[ -n "${TEST_CMD:-}" ]]; then
cmd="$TEST_CMD"
else
project_info=$(detect_project "$project_dir")
cmd=$(echo "$project_info" | jq -r '.test // ""')
fi
if [[ -z "$cmd" || "$cmd" == "null" ]]; then
jq -nc '{
"tests_ok": true,
"tests_output": "(GATE NOT RUN: no test command configured or detected. This is NOT evidence that tests passed — set TEST_CMD, and never report the suite as green.)",
"_next": "self_review"
}'
exit 0
fi
exit_code=0
output=$(cd "$project_dir" && eval "$cmd" 2>&1) || exit_code=$?
if (( exit_code == 0 )); then
jq -nc \
--arg out "$output" \
--arg cmd "$cmd" \
'{
"tests_ok": true,
"tests_output": ("Ran: " + $cmd + "\n\n" + $out),
"_next": "self_review"
}'
else
jq -nc \
--arg out "$output" \
--arg cmd "$cmd" \
--argjson rc "$exit_code" \
'{
"tests_ok": false,
"tests_output": ("Ran: " + $cmd + "\nExit code: " + ($rc | tostring) + "\n\n" + $out),
"_next": "fix_loop_gate"
}'
fi
assets/agents/coder/tools.sh
+118
View File
@@ -14,6 +14,99 @@ _project_dir() {
(cd "${dir}" 2>/dev/null && pwd) || echo "${dir}"
}
# Normalize a path to be relative to project root.
# Strips the project_dir prefix if the LLM passes an absolute path.
# Usage: local rel_path; rel_path=$(_normalize_path "/abs/or/rel/path")
_normalize_path() {
local input_path="$1"
local project_dir
project_dir=$(_project_dir)
if [[ "${input_path}" == /* ]]; then
input_path="${input_path#"${project_dir}"/}"
fi
input_path="${input_path#./}"
echo "${input_path}"
}
# @cmd Read a file's contents before modifying
# @option --path! Path to the file (relative to project root)
read_file() {
local file_path
# shellcheck disable=SC2154
file_path=$(_normalize_path "${argc_path}")
local project_dir
project_dir=$(_project_dir)
local full_path="${project_dir}/${file_path}"
if [[ ! -f "${full_path}" ]]; then
warn "File not found: ${file_path}" >> "$LLM_OUTPUT"
return 0
fi
{
info "Reading: ${file_path}"
echo ""
cat "${full_path}"
} >> "$LLM_OUTPUT"
}
# @cmd Write complete file contents
# @option --path! Path for the file (relative to project root)
# @option --content! Complete file contents to write
write_file() {
local file_path
file_path=$(_normalize_path "${argc_path}")
# shellcheck disable=SC2154
local content="${argc_content}"
local project_dir
project_dir=$(_project_dir)
local full_path="${project_dir}/${file_path}"
mkdir -p "$(dirname "${full_path}")"
printf '%s' "${content}" > "${full_path}"
green "Wrote: ${file_path}" >> "$LLM_OUTPUT"
}
# @cmd Find files similar to a given path (for pattern matching)
# @option --path! Path to find similar files for
find_similar_files() {
local file_path
file_path=$(_normalize_path "${argc_path}")
local project_dir
project_dir=$(_project_dir)
local ext="${file_path##*.}"
local dir
dir=$(dirname "${file_path}")
info "Similar files to: ${file_path}" >> "$LLM_OUTPUT"
echo "" >> "$LLM_OUTPUT"
local results
results=$(find "${project_dir}/${dir}" -maxdepth 1 -type f -name "*.${ext}" \
! -name "$(basename "${file_path}")" \
! -name "*test*" \
! -name "*spec*" \
2>/dev/null | sed "s|^${project_dir}/||" | head -3)
if [[ -z "${results}" ]]; then
results=$(find "${project_dir}/src" -type f -name "*.${ext}" \
! -name "*test*" \
! -name "*spec*" \
-not -path '*/target/*' \
2>/dev/null | sed "s|^${project_dir}/||" | head -3)
fi
if [[ -n "${results}" ]]; then
echo "${results}" >> "$LLM_OUTPUT"
else
warn "No similar files found" >> "$LLM_OUTPUT"
fi
}
# @cmd Verify the project builds successfully
verify_build() {
local project_dir
@@ -96,3 +189,28 @@ get_project_structure() {
} >> "$LLM_OUTPUT"
}
# @cmd Search for content in the codebase
# @option --pattern! Pattern to search for
search_code() {
# shellcheck disable=SC2154
local pattern="${argc_pattern}"
local project_dir
project_dir=$(_project_dir)
info "Searching: ${pattern}" >> "$LLM_OUTPUT"
echo "" >> "$LLM_OUTPUT"
local results
results=$(grep -rn "${pattern}" "${project_dir}" 2>/dev/null | \
grep -v '/target/' | \
grep -v '/node_modules/' | \
grep -v '/.git/' | \
sed "s|^${project_dir}/||" | \
head -20) || true
if [[ -n "${results}" ]]; then
echo "${results}" >> "$LLM_OUTPUT"
else
warn "No matches" >> "$LLM_OUTPUT"
fi
}
assets/agents/deep-research/README.md
-289
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@@ -1,289 +0,0 @@
# deep-research
A deep web research agent, built as a Coyote graph agent. It plans an
investigation, decomposes it into sub-questions researched in
parallel, grounds the work in a local knowledge corpus, vets the
credibility of cited sources, runs a reflexion self-critique loop to
revise weak findings, delegates the final write-up to a focused
sub-agent, checks that the cited sources are reachable, and gates the
result behind human approval.
Unlike a regular agent (which takes a goal and improvises the steps),
this agent runs a fixed graph: every request goes through the same
`plan -> parallel research -> vet -> critique -> synthesize -> verify -> approve`
pipeline.
This agent is also the **canonical reference for the Coyote graph
system**: it exercises every node type (`script`, `llm`, `rag`, `map`,
`agent`, `input`, `approval`, `end`) and both static fan-out and
dynamic `map` fan-out. If you are learning how to build a graph
agent, this is the file to read alongside the
[Graph-Agents wiki](https://github.com/Dark-Alex-17/coyote/wiki/Graph-Agents).
## Workflow
17 nodes. Solid arrows are static `next` / `routes` edges declared in
`graph.yaml`; script nodes can also route dynamically via `_next` (shown as
labeled branches out of the diamond). Dotted arrows show `map` fan-out — the
`research_each_question` node spawns one `research_one_question` branch per
sub-question and joins them before continuing.
```mermaid
flowchart TD
parse_request{"parse_request<br/>script"}
parse_request -->|"topic given"| bootstrap_research
parse_request -->|"no topic"| ask_topic
ask_topic[/"ask_topic<br/>input"/] --> bootstrap_research
bootstrap_research{"bootstrap_research<br/>script"}
bootstrap_research --> plan
bootstrap_research --> knowledge_lookup
plan["plan<br/>llm + output_schema"] --> research_each_question
knowledge_lookup[("knowledge_lookup<br/>rag")] --> research_each_question
research_each_question[\research_each_question<br/>map/]
research_each_question -. "spawns × N" .-> research_one_question["research_one_question<br/>llm + web tools"]
research_each_question --> combine_findings
combine_findings{"combine_findings<br/>script"} --> vet_sources
vet_sources["vet_sources<br/>llm + classify_source"] --> critique
critique["critique<br/>llm"] --> reflexion_gate
reflexion_gate{"reflexion_gate<br/>script"}
reflexion_gate -->|"PASS"| synthesize
reflexion_gate -->|"REVISE (budget left)"| research_each_question
reflexion_gate -->|"REVISE (budget spent)"| synthesize
synthesize[["synthesize<br/>agent → report-writer"]] --> verify_sources
verify_sources{"verify_sources<br/>script"} --> approve
approve{{"approve<br/>approval"}}
approve -->|"accept"| end_accepted
approve -->|"reject"| end_rejected
approve -->|"other (free-form feedback)"| incorporate_feedback
incorporate_feedback{"incorporate_feedback<br/>script"} --> research_each_question
end_accepted(["end_accepted<br/>report"])
end_rejected(["end_rejected"])
```
### Node-type breakdown
| Type | Nodes |
|-----------------------------|-----------------------------------------------------------------------------------------------------------------------|
| `script` (Python) | `parse_request`, `bootstrap_research`, `combine_findings`, `reflexion_gate`, `verify_sources`, `incorporate_feedback` |
| `llm` (tools: `[]`) | `plan`, `critique` |
| `llm` (with tool whitelist) | `research_one_question`, `vet_sources` |
| `rag` | `knowledge_lookup` — local corpus retrieval |
| `map` | `research_each_question` — dynamic fan-out per sub-question |
| `agent` | `synthesize` — spawns the `report-writer` sub-agent |
| `input` | `ask_topic` |
| `approval` | `approve` |
| `end` | `end_accepted`, `end_rejected` |
## Parallel execution
The graph has two parallel super-steps where Coyote's BSP scheduler runs
branches concurrently.
**1. Context loading (`plan` ‖ `knowledge_lookup`)** — after
`bootstrap_research`, the LLM planner (which decomposes the topic into
sub-questions) and the RAG retrieval over the local `knowledge/`
corpus run side by side. They write disjoint state keys (`plan` writes
`research_plan` and `questions`; `knowledge_lookup` writes
`local_context` and `local_sources`) so no reducer is needed.
**2. Per-question research (`research_each_question` map)** — the
plan emits a `questions` array (3-5 entries, enforced by its
`output_schema`). The `map` node spawns one parallel branch per
question (`max_concurrency: 3`). Each branch is an isolated
`research_one_question` LLM invocation with web tools, instructed to
investigate exactly its assigned question. Outputs collect into
`question_findings` in input order, then `combine_findings` joins
them into a single `findings` Markdown document for downstream nodes.
`settings.max_concurrency: 4` is the graph-wide cap; the per-`map`
override (`max_concurrency: 3` on `research_each_question`) is
deliberately lower to leave headroom for the planner's tool calls
running alongside RAG.
## Local knowledge corpus
`knowledge_lookup` is a `rag` node — it runs hybrid (vector + keyword)
retrieval over every file in `knowledge/`. The directory ships with a
small `research-style-notes.md` so the RAG node has something to
retrieve against on a clean install; drop your own Markdown notes,
PDFs, or text files into `knowledge/` to bias the research toward
your local context.
The knowledge base is built once, at agent-load time, into
`~/.config/coyote/agents/deep-research/knowledge_lookup.yaml`. Because
the node fully specifies its build config (`embedding_model`,
`chunk_size`, `chunk_overlap`), the build is non-interactive. Delete
that cached file after adding or changing knowledge to force a
rebuild.
## Sub-agent: report-writer
The `synthesize` node is an `agent` node that spawns the
`report-writer` sub-agent (`assets/agents/report-writer/`). This is
the agent-as-tool pattern: the orchestrating graph delegates the
writing phase to a focused sub-agent dedicated to coherent prose,
while the research phase uses different (typically cheaper) LLM nodes
for fast-and-many-question investigation.
The `report-writer` sub-agent has no tools — it cannot access the
web, cannot search, and cannot invent facts. It reads only the
findings it is given and produces a final Markdown report preserving
every inline citation. See `assets/agents/report-writer/README.md`
for details.
## Tools and tool scoping
This agent demonstrates Coyote's three tool sources and how an `llm`
node's `tools:` whitelist scopes them per node.
The agent's full tool universe, declared in `graph.yaml`:
- **Global tools** (`global_tools`): `web_search_coyote`,
`fetch_url_via_curl`, `search_arxiv` - Coyote's built-in tool scripts.
- **MCP server** (`mcp_servers`): `ddg-search` - a DuckDuckGo web
search MCP server. Referenced in a whitelist as `mcp:ddg-search`.
- **Custom agent tool** (`tools.sh`): `classify_source` - a
deterministic source-credibility classifier shipped with this agent.
No node receives all of these. Each `llm` node's `tools:` whitelist
narrows the universe to exactly what that step needs:
| Node | `tools:` whitelist | Draws from |
|-------------------------|-----------------------------------------------------------------------------|--------------------------|
| `plan`, `critique` | `[]` | nothing - pure reasoning |
| `research_one_question` | `web_search_coyote`, `fetch_url_via_curl`, `search_arxiv`, `mcp:ddg-search` | global tools + MCP |
| `vet_sources` | `classify_source` | the custom tool only |
`research_one_question` (each parallel branch of the map) can search
and fetch but cannot classify sources; `vet_sources` can classify
sources but cannot touch the web. That separation is the point of the
`tools:` whitelist: a node gets only the tools its job calls for,
never the agent's full set.
The `classify_source` custom tool (`tools.sh`) takes a URL and returns
a credibility tier (government, academic, preprint, organization,
unverified) derived from the host and top-level domain. It is
deterministic - exactly the kind of logic a tool should own rather than
the LLM guessing.
Web search may require API-key configuration; see the
[Tools](https://github.com/Dark-Alex-17/coyote/wiki/Tools) docs.
`fetch_url_via_curl`, `search_arxiv`, and `classify_source` work
without a key.
## Setup
`research_one_question` (each parallel branch of the `map`) uses the
`ddg-search` MCP server via `mcp:ddg-search`. It is one of Coyote's
default MCP servers; make sure it is registered in
`~/.config/coyote/mcp.json` (run `coyote --install mcp_config` to restore
the default template if it is missing). If `ddg-search` is unavailable,
the branches still have their global web-search tools to fall back on.
The `synthesize` node spawns the `report-writer` sub-agent. Both
agents ship with `coyote agents install`; if you install one manually,
install both so the agent reference resolves.
## Reflexion
The agent has two loops, both built with script nodes that route via
`_next`. The engine allows back-edges at runtime; the validator only
rejects cycles built from static `next` / `routes` edges, so script
`_next` loops are always allowed.
**Automated reflexion loop.** After the parallel research map and
`vet_sources`, the `critique` node reviews the merged findings
against the research plan and the source credibility assessment, and
emits `VERDICT: PASS` or `VERDICT: REVISE` with specific feedback.
`reflexion_gate.py` then:
- `PASS` -> continue to `synthesize`.
- `REVISE`, budget remaining -> loop back to `research_each_question`,
with the critique injected as `research_feedback` so every parallel
branch sees it on the retry.
- `REVISE`, budget spent -> continue to `synthesize` anyway (the human
approval step is the final backstop).
The budget is `MAX_REFLEXION_REVISIONS` in `reflexion_gate.py`
(default 2, so the research map runs at most 3 times per pass).
**Human-feedback loop.** At `approve` the user answers `accept`,
`reject`, or types their own feedback. A free-form answer routes via
the approval node's `on_other` to `incorporate_feedback.py`, which
folds that text into `research_feedback` and loops back to
`research_each_question` for another parallel pass.
`settings.max_loop_iterations` (40) is the engine's infinite-loop
backstop: it caps the total visits to any single node.
## Running
```sh
coyote agents install # ships deep-research
coyote -a deep-research "How does HTTP/3 differ from HTTP/2?"
coyote -a deep-research "Recent advances in solid-state batteries"
coyote -a deep-research # no prompt -> triggers ask_topic
```
## Anti-hallucination
- `research_one_question` (each map branch) is instructed to back
every claim with a real retrieved source and never to fabricate
URLs, titles, or DOIs.
- `vet_sources` classifies every cited source so weak sources are
visible to the critique step.
- `critique` independently reviews the merged findings and sends weak
or uncited work back for another parallel research pass.
- `synthesize` (the `report-writer` sub-agent) is grounded: it may use
only the gathered findings and must keep each claim's inline source.
It has no tools and cannot browse the web.
- `verify_sources` probes every cited URL / DOI with an HTTP HEAD
request and reports which are unreachable, so the human reviewer
sees broken citations before approving.
## Customizing
- **Loop budget.** `MAX_REFLEXION_REVISIONS` in `reflexion_gate.py`.
- **Map concurrency.** The `research_each_question` node's
`max_concurrency: 3` caps simultaneous web-research branches.
Raise to investigate more questions in parallel; lower to be gentle
on rate-limited providers.
- **Per-node model.** Add `model: anthropic:...` to any `llm` node.
Cheap models work well for `plan` / `critique` / `vet_sources`; the
heavy intelligence is needed in `research_one_question` and the
`report-writer` sub-agent.
- **Tool scope.** Narrow the `research_one_question` node's `tools:`
list to constrain where each branch looks (for example, drop
`web_search_coyote` and `mcp:ddg-search` to force arXiv-only
research).
- **Local knowledge.** Drop files into `knowledge/` to bias every
research branch toward your local context (see the *Local
knowledge corpus* section above).
- **Different writer.** Replace `agent: report-writer` on the
`synthesize` node with the name of any other agent. The
orchestrator does not care what kind of agent the writer is.
- **Skip approval.** Point both `approve` routes at `end_accepted`,
or wire `verify_sources` straight to an `end` node.
## Files
```
assets/agents/deep-research/
graph.yaml - agent config + 17-node workflow
tools.sh - classify_source custom tool
README.md - this file
knowledge/
README.md - corpus-format notes
research-style-notes.md - starter knowledge file (replace with your notes)
scripts/
parse_request.py - _next: bootstrap_research, or ask_topic if no topic
bootstrap_research.py - fan-out source: next [plan, knowledge_lookup]
combine_findings.py - joins map output (question_findings) into findings
reflexion_gate.py - _next: research_each_question (revise) or synthesize
verify_sources.py - HTTP HEAD on cited URLs / DOIs
incorporate_feedback.py - _next: research_each_question, with user feedback
```
See also `assets/agents/report-writer/` — the sub-agent the
`synthesize` node spawns.
assets/agents/deep-research/graph.yaml
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name: deep-research
description: |
Deep web research workflow. Plans an investigation, decomposes it
into sub-questions researched in parallel, grounds the work in a
local knowledge corpus, vets the credibility of cited sources, runs
a reflexion self-critique loop to revise weak or incomplete findings,
delegates the final write-up to a focused sub-agent, checks that the
cited sources are reachable, and gates the result behind human
approval. A reviewer's free-form feedback at the approval step feeds
back into another research pass.
This is the canonical Coyote graph-agent reference: it exercises every
node type (script, llm, rag, map, agent, input, approval, end) and
both static fan-out and dynamic map fan-out.
version: "1.0"
global_tools:
- web_search_coyote.sh
- fetch_url_via_curl.sh
- search_arxiv.sh
mcp_servers:
- ddg-search
conversation_starters:
- "How does HTTP/3 differ from HTTP/2?"
- "Summarize recent advances in solid-state battery chemistry"
settings:
max_loop_iterations: 40
log_state_snapshots: false
validate_before_run: true
max_concurrency: 4
initial_state:
research_feedback: ""
research_attempts: 0
local_context: ""
local_sources: ""
start: parse_request
nodes:
parse_request:
id: parse_request
type: script
script: scripts/parse_request.py
next: bootstrap_research
ask_topic:
id: ask_topic
type: input
question: "What would you like me to research?"
validation: "len(input) > 0"
state_updates:
topic: "{{input}}"
next: bootstrap_research
bootstrap_research:
id: bootstrap_research
type: script
script: scripts/bootstrap_research.py
next: [plan, knowledge_lookup]
plan:
id: plan
type: llm
instructions: |
You are a research planner. Given a topic, produce a focused
research plan and decompose it into 3-5 specific sub-questions
that can each be researched independently in parallel.
The plan is a short narrative naming the key questions and the
kinds of sources that would be authoritative. The sub-questions
are precise, self-contained queries (each one is sent on its own
to a separate research worker, so they must be answerable
without each other's context).
prompt: "Research topic: {{topic}}"
tools: []
output_schema:
type: object
properties:
research_plan:
type: string
description: A short plan narrative.
questions:
type: array
items: { type: string }
minItems: 1
maxItems: 6
description: 3-5 specific, self-contained sub-questions.
required: [research_plan, questions]
next: research_each_question
knowledge_lookup:
id: knowledge_lookup
type: rag
documents:
- ./knowledge/
query: "{{topic}}"
top_k: 6
chunk_size: 1000
chunk_overlap: 100
state_updates:
local_context: "{{output.context}}"
local_sources: "{{output.sources}}"
next: research_each_question
research_each_question:
id: research_each_question
type: map
over: "{{questions}}"
as: question
branch: research_one_question
collect_into: question_findings
max_concurrency: 3
next: combine_findings
research_one_question:
id: research_one_question
type: llm
instructions: |
You are a web research assistant. Investigate the SINGLE question
given to you using your tools: search the web, fetch and read
pages, and search arXiv for academic sources.
Rules:
- Every factual claim must be backed by a real source you
actually retrieved. Never fabricate URLs, page titles,
authors, or DOIs.
- Prefer primary and authoritative sources over aggregators.
- Where sources disagree, report the disagreement rather than
papering over it.
- Put the URL (or DOI) inline next to each claim it supports.
Return organized findings in plain text. Do not include
meta-commentary about the process.
prompt: |
Research question: {{question}}
Local context that may help:
{{local_context}}
{{research_feedback}}
tools:
- web_search_coyote
- fetch_url_via_curl
- search_arxiv
- mcp:ddg-search
max_iterations: 10
max_attempts: 2
temperature: 0.1
combine_findings:
id: combine_findings
type: script
script: scripts/combine_findings.py
next: vet_sources
vet_sources:
id: vet_sources
type: llm
instructions: |
You assess the credibility of the sources cited in a set of
research findings. For every distinct source URL in the findings,
call the `classify_source` tool to get its credibility tier. Then
summarize: which claims rest on HIGH-credibility sources, and
which rest on PREPRINT or UNVERIFIED sources and so need
corroboration. Do NOT do any new research -- assess only what is
already cited.
prompt: |
Findings to assess:
{{findings}}
tools:
- classify_source
max_iterations: 15
state_updates:
source_assessment: "{{output}}"
next: critique
critique:
id: critique
type: llm
instructions: |
You are a meticulous research reviewer. Judge whether the
findings below are good enough to synthesize a complete,
well-supported report that answers the research plan.
Mark the findings REVISE if ANY of these hold:
- A research-plan question is unanswered or only weakly
addressed.
- A factual claim has no source, or cites a source that looks
fabricated.
- The findings lean on a single source where corroboration is
needed.
- A key claim rests only on a PREPRINT or UNVERIFIED source,
per the source credibility assessment below.
- An obvious counter-perspective or recent development is
missing.
Otherwise mark them PASS.
Respond in EXACTLY this format, nothing else:
VERDICT: <PASS or REVISE>
FEEDBACK: <if REVISE, be specific and actionable -- name the gaps
and what kind of source would close them; if PASS, write "none">
prompt: |
Research plan:
{{research_plan}}
Findings under review:
{{findings}}
Source credibility assessment:
{{source_assessment}}
tools: []
state_updates:
critique: "{{output}}"
next: reflexion_gate
reflexion_gate:
id: reflexion_gate
type: script
script: scripts/reflexion_gate.py
next: synthesize
synthesize:
id: synthesize
type: agent
agent: report-writer
prompt: |
Research topic: {{topic}}
Findings (organized by sub-question, with inline citations):
{{findings}}
Source credibility assessment:
{{source_assessment}}
Produce the final report following your instructions.
timeout: 300
state_updates:
report: "{{output}}"
next: verify_sources
verify_sources:
id: verify_sources
type: script
script: scripts/verify_sources.py
next: approve
approve:
id: approve
type: approval
question: |
Research report on: {{topic}}
{{report}}
----
{{source_check}}
----
Accept this report? Pick "accept" or "reject", or type specific
feedback to send the research back for another pass.
options:
- "accept"
- "reject"
routes:
"accept": end_accepted
"reject": end_rejected
on_other: incorporate_feedback
state_updates:
decision: "{{choice}}"
incorporate_feedback:
id: incorporate_feedback
type: script
script: scripts/incorporate_feedback.py
end_accepted:
id: end_accepted
type: end
output: "{{report}}"
end_rejected:
id: end_rejected
type: end
output: "Research on '{{topic}}' was rejected and discarded."
assets/agents/deep-research/knowledge/README.md
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@@ -1,23 +0,0 @@
# Local knowledge corpus for deep-research
The `knowledge_lookup` node in `graph.yaml` is a `rag` node that runs
hybrid (vector + keyword) retrieval over every file in this directory.
Drop your own notes, papers (PDFs), Markdown docs, or text files here
and they will be indexed into a per-agent knowledge base on first run.
Coyote supports common file types out of the box: `.md`, `.txt`, `.pdf`,
`.html`, and others. Subdirectories are walked recursively.
A small starter file (`research-style-notes.md`) ships so the RAG
node has something non-empty to retrieve against on a clean install.
Replace or extend it with your own materials to bias the research
phase toward your local context.
To force the knowledge base to rebuild after you add or change files,
delete the cached index:
```sh
rm ~/.config/coyote/agents/deep-research/knowledge_lookup.yaml
```
The next run will rebuild from the current contents of this directory.
assets/agents/deep-research/knowledge/research-style-notes.md
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@@ -1,49 +0,0 @@
# Research style notes
These are general principles the `deep-research` agent should keep in
mind regardless of topic. Replace this file with your own notes if you
want to bias retrieval toward your local context.
## What "good research" means here
- **Every factual claim cites a source you actually retrieved.** Never
fabricate URLs, page titles, authors, or DOIs.
- **Primary sources beat aggregators.** Prefer the original paper, the
RFC, the standards body, or the manufacturer over a blog summarizing
them.
- **Corroboration matters where stakes are high.** If a single source
makes a strong claim, look for a second independent source before
taking it as established.
- **Disagreement is information, not noise.** If two credible sources
disagree, report the disagreement and the reasoning on each side.
- **Old does not mean wrong.** A 2014 RFC is still authoritative if no
newer one has obsoleted it; check before assuming a source is stale.
## Source-tier heuristics
The `vet_sources` node uses these rough tiers to weigh credibility.
The custom tool `classify_source` (see `tools.sh`) implements this
deterministically by hostname / TLD.
- **HIGH:** government domains (`.gov`, `.mil`), academic institutions
(`.edu`, university subdomains), peer-reviewed journals, standards
bodies (IETF/RFCs, W3C, ISO, IEEE, NIST), and primary documents from
the entities being researched (e.g. a vendor's official spec page).
- **PREPRINT:** arXiv, bioRxiv, medRxiv, SSRN. Useful but not yet
peer-reviewed; treat numeric claims with extra caution.
- **ORGANIZATION:** established nonprofits, standards-adjacent groups,
industry consortia. Reliable for their stated mission but may have a
perspective.
- **UNVERIFIED:** general web pages, blogs, news aggregators, social
media. Useful for leads but should not be the only source for a
factual claim.
## Common pitfalls to flag in critique
- A claim cited only to a PREPRINT or UNVERIFIED source on a numeric
or contested point.
- A research-plan question that the findings address only obliquely.
- "Findings" that paraphrase a single source three times rather than
triangulating.
- Citation collisions where two sources are listed but turn out to
be the same study reported via different aggregators.
assets/agents/deep-research/scripts/bootstrap_research.py
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@@ -1,18 +0,0 @@
#!/usr/bin/env python3
"""Fan-out source for context loading.
Has no logic of its own. Exists so the static `next: [plan, knowledge_lookup]`
list on this node fans out into two parallel branches (the LLM planner and
the RAG knowledge lookup) as a single super-step. The validator requires
declared parallel-branch script outputs, so we emit an empty JSON object
explicitly here.
"""
import json
def main():
print(json.dumps({}))
if __name__ == "__main__":
main()
assets/agents/deep-research/scripts/combine_findings.py
-39
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@@ -1,39 +0,0 @@
#!/usr/bin/env python3
"""Join the per-question map outputs into a single `findings` string.
The `research_each_question` map writes `question_findings` (an array,
one entry per sub-question, in input order). Downstream nodes
(`vet_sources`, `critique`, `synthesize`) read `{{findings}}` as a
single block, so this script renders the array as a Markdown document
with one section per question.
"""
import json
import os
def load_state():
path = os.environ.get("GRAPH_STATE_FILE")
if path:
with open(path) as f:
return json.load(f)
return json.loads(os.environ.get("GRAPH_STATE", "{}"))
def main():
state = load_state()
questions = state.get("questions") or []
per_question = state.get("question_findings") or []
sections = []
for idx, q in enumerate(questions):
body = per_question[idx] if idx < len(per_question) else ""
if isinstance(body, dict) or isinstance(body, list):
body = json.dumps(body, indent=2)
sections.append(f"## {q}\n\n{body}")
findings = "\n\n".join(sections) if sections else "No findings gathered."
print(json.dumps({"findings": findings}))
if __name__ == "__main__":
main()
assets/agents/deep-research/scripts/incorporate_feedback.py
-41
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@@ -1,41 +0,0 @@
#!/usr/bin/env python3
"""Fold a reviewer's free-form feedback back into the research loop.
Runs when the user answers the approval step with their own text
instead of "accept" or "reject". That text (saved by the approval node
as `decision`) becomes `research_feedback`, and the graph loops back to
`research_each_question` for another informed pass (each sub-question is
re-researched in parallel with the new feedback in context). The
reflexion counter is reset so the user-driven pass gets a fresh revision
budget.
Routing (`_next`): always research_each_question.
"""
import json
import os
def load_state():
path = os.environ.get("GRAPH_STATE_FILE")
if path:
with open(path) as f:
return json.load(f)
return json.loads(os.environ.get("GRAPH_STATE", "{}"))
def main():
state = load_state()
feedback = (state.get("decision") or "").strip()
output = {
"_next": "research_each_question",
"research_attempts": 0,
"research_feedback": (
"The user reviewed the report and asked for changes. Treat "
"this as the top priority for the next pass:\n\n" + feedback
),
}
print(json.dumps(output))
if __name__ == "__main__":
main()
assets/agents/deep-research/scripts/parse_request.py
-35
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@@ -1,35 +0,0 @@
#!/usr/bin/env python3
"""Entry router for deep-research.
Reads the caller's prompt from state. If it contains a usable research
topic, stores it as `topic` and falls through to the static `next`
(plan). If the prompt is empty, routes to `ask_topic` so the user can
supply one interactively.
Routing (`_next`):
- prompt present -> (no _next; static next: plan)
- prompt empty -> ask_topic
"""
import json
import os
def load_state():
path = os.environ.get("GRAPH_STATE_FILE")
if path:
with open(path) as f:
return json.load(f)
return json.loads(os.environ.get("GRAPH_STATE", "{}"))
def main():
state = load_state()
prompt = (state.get("initial_prompt") or "").strip()
if prompt:
print(json.dumps({"topic": prompt}))
else:
print(json.dumps({"_next": "ask_topic"}))
if __name__ == "__main__":
main()
assets/agents/deep-research/scripts/reflexion_gate.py
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@@ -1,76 +0,0 @@
#!/usr/bin/env python3
"""Reflexion gate for deep-research.
Runs after `critique` has reviewed the current research findings. If the
critique's verdict is REVISE and the reflexion budget is not spent,
loops back to `research` with the critique attached as
`research_feedback`, so the retry is informed rather than a blind
re-run. Otherwise it proceeds to `synthesize`.
Routing (`_next`):
- verdict PASS -> synthesize
- verdict REVISE, budget remaining -> research_each_question (+ research_feedback)
- verdict REVISE, budget spent -> synthesize
Reflexion is a best-effort quality booster, not a hard gate: once the
budget is spent the workflow proceeds anyway, and the human approval
step is the final backstop.
"""
import json
import os
import re
# Automated revision passes allowed. `research` runs at most
# MAX_REFLEXION_REVISIONS + 1 times per user pass. Bump to allow more.
MAX_REFLEXION_REVISIONS = 2
def load_state():
path = os.environ.get("GRAPH_STATE_FILE")
if path:
with open(path) as f:
return json.load(f)
return json.loads(os.environ.get("GRAPH_STATE", "{}"))
def as_int(value, default=0):
try:
return int(value)
except (TypeError, ValueError):
return default
def parse_verdict(critique):
"""Pull PASS/REVISE from the critique's `VERDICT:` line. Defaults to
PASS when no verdict line is found, so a malformed critique lets the
workflow proceed instead of burning the whole revision budget."""
match = re.search(r"VERDICT:\s*([A-Za-z]+)", critique, re.IGNORECASE)
if not match:
return "PASS"
return match.group(1).upper()
def main():
state = load_state()
critique = state.get("critique") or ""
verdict = parse_verdict(critique)
attempts = as_int(state.get("research_attempts"))
if verdict == "REVISE" and attempts < MAX_REFLEXION_REVISIONS:
feedback = (
"A reviewer judged the previous research pass incomplete. "
"Address every point in the critique below:\n\n" + critique
)
output = {
"_next": "research_each_question",
"research_attempts": attempts + 1,
"research_feedback": feedback,
}
else:
output = {"_next": "synthesize"}
print(json.dumps(output))
if __name__ == "__main__":
main()
assets/agents/deep-research/scripts/verify_sources.py
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@@ -1,69 +0,0 @@
#!/usr/bin/env python3
"""Check that the sources cited in the research report are reachable.
Scans the final report for URLs and DOIs, probes each with a HEAD
request, and writes a `source_check` summary into state so the human
reviewer sees broken citations at the approval step.
Times out per request so a slow source cannot stall the graph.
"""
import json
import os
import re
import urllib.error
import urllib.request
DOI_RE = re.compile(r"\b(10\.\d{4,9}/[-._;()/:A-Z0-9]+)", re.IGNORECASE)
URL_RE = re.compile(r"https?://[^\s)\]\}\"'>]+")
def load_state():
path = os.environ.get("GRAPH_STATE_FILE")
if path:
with open(path) as f:
return json.load(f)
return json.loads(os.environ.get("GRAPH_STATE", "{}"))
def reachable(url, timeout=5.0):
req = urllib.request.Request(url, method="HEAD")
try:
with urllib.request.urlopen(req, timeout=timeout) as resp:
return 200 <= resp.status < 400
except urllib.error.HTTPError as e:
return 200 <= e.code < 400
except Exception:
return False
def main():
state = load_state()
report = state.get("report") or ""
urls = sorted({u.rstrip(".,;)") for u in URL_RE.findall(report)})
dois = sorted(set(DOI_RE.findall(report)))
results = []
for url in urls:
ok = reachable(url)
results.append(f" {'OK' if ok else 'UNREACHABLE'} {url}")
for doi in dois:
url = f"https://doi.org/{doi}"
if url in urls:
continue
ok = reachable(url)
results.append(f" {'OK' if ok else 'UNREACHABLE'} DOI {doi} ({url})")
if not results:
summary = "No web sources were cited in the report."
else:
summary = (
f"Source reachability ({len(results)} checked):\n"
+ "\n".join(results)
)
print(json.dumps({"source_check": summary}))
if __name__ == "__main__":
main()
assets/agents/deep-research/tools.sh
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@@ -1,39 +0,0 @@
#!/usr/bin/env bash
set -e
# @env LLM_OUTPUT=/dev/stdout The output path
# @cmd Classify the credibility tier of a web source from its URL.
# A deterministic check based on the host and top-level domain. Use it
# to weigh how much trust to place in a source before relying on it.
# @option --url! The full source URL to classify
classify_source() {
# shellcheck disable=SC2154
local url="$argc_url"
local host="${url#*://}"
host="${host%%/*}"
host="${host##*@}"
host="${host%%:*}"
host="$(printf '%s' "$host" | tr '[:upper:]' '[:lower:]')"
local tier
case "$host" in
'')
tier="UNKNOWN - no host could be parsed from the URL" ;;
*.gov | *.gov.* | *.mil)
tier="HIGH - government source" ;;
*.edu | *.edu.* | *.ac.*)
tier="HIGH - academic institution" ;;
arxiv.org | *.arxiv.org | biorxiv.org | *.biorxiv.org | medrxiv.org | *.medrxiv.org | ssrn.com | *.ssrn.com)
tier="PREPRINT - not yet peer reviewed, corroborate before citing" ;;
wikipedia.org | *.wikipedia.org)
tier="TERTIARY - encyclopedia, good for orientation not citation" ;;
*.org | *.org.*)
tier="MEDIUM - organization site, check for institutional bias" ;;
*)
tier="UNVERIFIED - general web source, corroborate before citing" ;;
esac
printf '%s: %s\n' "${host:-<none>}" "$tier" >> "$LLM_OUTPUT"
}
assets/agents/demo/README.md
+1 -1
View File
@@ -2,6 +2,6 @@
This agent serves as a demo to guide agent development and showcase various agent capabilities.
To enable tools, Coyote will look for the first `tools.py` or `tools.sh` file it finds in this directory.
To enable tools, Loki will look for the first `tools.py` or `tools.sh` file it finds in this directory.
The base configuration using `tools.py`. To switch to using `tools.sh`, rename or remove `tools.py`.
assets/agents/explore/README.md
+2 -2
View File
@@ -17,7 +17,7 @@ It can also be used as a standalone tool for understanding codebases and finding
## Pro-Tip: Use an IDE MCP Server for Improved Performance
Many modern IDEs now include MCP servers that let LLMs perform operations within the IDE itself and use IDE tools. Using
an IDE's MCP server dramatically improves the performance of coding agents. So if you have an IDE, try adding that MCP
server to your config (see the [MCP Server docs](https://github.com/Dark-Alex-17/loki/wiki/MCP-Servers) to see how to configure
server to your config (see the [MCP Server docs](../../../docs/function-calling/MCP-SERVERS.md) to see how to configure
them), and modify the agent definition to look like this:
```yaml
@@ -31,7 +31,7 @@ global_tools:
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
- web_search_coyote.sh
- web_search_loki.sh
# ...
```
assets/agents/explore/config.yaml
+33 -78
View File
@@ -1,25 +1,17 @@
name: explore
description: Fast codebase exploration agent - finds patterns, structures, and relevant files. Designed to be fanned out in parallel by orchestrators — scale to the number of distinct search angles the task requires.
version: 3.1.0
skills_enabled: true
enabled_skills:
- ai-slop-remover
description: Fast codebase exploration agent - finds patterns, structures, and relevant files
version: 1.0.0
temperature: 0.1
variables:
- name: project_dir
description: Project directory to explore
default: '.'
- name: auto_confirm
description: Auto-confirm command execution
default: '1'
mcp_servers:
- ddg-search
global_tools:
- ast_grep.sh
- fs_read.sh
- fs_cat.sh
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
@@ -27,94 +19,57 @@ global_tools:
instructions: |
You are a codebase explorer. Your job: Search, find, report. Nothing else.
## Step 0: Load your skills
## Your Mission
At the start of every exploration, call `skill__load` for `ai-slop-remover`. Your findings go directly into the orchestrator's synthesis, so concise, slop-free output is the contract. Apply the skill's standards to your final findings block:
Given a search task, you:
1. Search for relevant files and patterns
2. Read key files to understand structure
3. Report findings concisely
4. Signal completion with EXPLORE_COMPLETE
- No filler ("It's important to note that…", "Let me explain…"). Just the finding.
- No flattery, no padding, no status updates about your process.
- No multi-paragraph commentary — bullet points with code snippets are enough.
## File Reading Strategy (IMPORTANT - minimize token usage)
## You may be one of many parallel explorers
1. **Find first, read second** - Never read a file without knowing why
2. **Use grep to locate** - `fs_grep --pattern "struct User" --include "*.rs"` finds exactly where things are
3. **Use glob to discover** - `fs_glob --pattern "*.rs" --path src/` finds files by name
4. **Read targeted sections** - `fs_read --path "src/main.rs" --offset 50 --limit 30` reads only lines 50-79
5. **Never read entire large files** - If a file is 500+ lines, read the relevant section only
Orchestrators (like Sisyphus) fan out as many explore agents as the task warrants — one per distinct search angle, module boundary, or concern. You may be one of many running in parallel. Assume you are ONE narrow slice of a larger investigation. Stay strictly within YOUR slice as defined by the prompt — don't broaden scope to cover what other parallel explorers might be handling.
## Available Actions
If the prompt says "find auth middleware", you find auth middleware. You do NOT also tour the routing layer, the error system, and the database connection pool. Narrow scope is the contract.
- `fs_grep --pattern "struct User" --include "*.rs"` - Find content across files
- `fs_glob --pattern "*.rs" --path src/` - Find files by name pattern
- `fs_read --path "src/main.rs"` - Read a file (with line numbers)
- `fs_read --path "src/main.rs" --offset 100 --limit 50` - Read lines 100-149 only
- `get_structure` - See project layout
- `search_content --pattern "struct User"` - Agent-level content search
## Investigation methodology
## Output Format
Before searching, build a quick mental model. Then narrow in. Then read.
1. **Frame the question.** What kind of artifact am I looking for? Symbols (struct/class/function)? File patterns? Configuration? Implementation details? Tests? Different artifact kinds use different tools.
2. **Find first, read second.** Never `fs_read` a file without knowing why you're reading it.
3. **Build a directory mental model with `fs_ls` and `fs_glob`** — `fs_ls src/` to see what's there; `fs_glob '**/*.rs' src/` to see which files exist by name.
4. **Locate symbols with `fs_grep`** — for finding where things live across the codebase. `fs_grep --pattern "fn handle_request" --include "*.rs"` is faster than reading files.
4b. **Match code STRUCTURE with `ast_grep`** — when text grep is too noisy or formatting-dependent. It matches syntax trees: `ast_grep --pattern '$X.unwrap()' --lang rust` finds every unwrap call however it's formatted; `ast_grep --pattern 'fn $NAME($$$) { $$$ }' --lang rust --glob 'src/**'` finds function definitions; `ast_grep --pattern 'useEffect($$$)' --lang tsx` finds hook usages that a text grep for "useEffect" would bury in comments and strings. Meta-variables: `$NAME` = one AST node, `$$$` = zero or more. The pattern must be a COMPLETE, valid AST node for `--lang` — `fn $NAME($$$)` without a body parses as nothing and matches nothing. Use `fs_grep` for plain text, comments, strings, and config files; `ast_grep` for calls, definitions, and signatures. If ast-grep isn't installed the tool says so — fall back to fs_grep.
5. **Read targeted sections with `fs_read --offset/--limit`** — `fs_read --path "src/main.rs" --offset 50 --limit 30` reads lines 50-79 only. `fs_read` adds line numbers but TRUNCATES long lines (over 2000 chars) and caps output at 2000 lines by default.
6. **Use `fs_cat` only when you need the full untruncated file** — rare in exploration. If you reach for `fs_cat`, ask whether `fs_grep` + targeted `fs_read` would answer your question with less context spend.
7. **Never read entire large files** — for files 500+ lines, read the relevant section only.
## Available actions
- `fs_grep --pattern "struct User" --include "*.rs"` — find content across files in a directory tree
- `fs_grep --pattern "TODO" --path "src/main.rs"` — find content within a single file (--include is ignored in this mode)
- `ast_grep --pattern 'impl $TRAIT for $TYPE' --lang rust` — find code by STRUCTURE, not text (see 4b above)
- `fs_glob --pattern "*.rs" --path src/` — find files by name pattern
- `fs_read --path "src/main.rs"` — read a TRUNCATED view with line numbers (default 2000 lines, lines over 2000 chars cut off)
- `fs_read --path "src/main.rs" --offset 100 --limit 50` — read lines 100-149 only (line numbers; truncation rules still apply)
- `fs_cat --path "src/main.rs"` — read the FULL untruncated file (no line numbers); use only when you actually need every line
- `fs_ls --path "src/"` — list directory contents
## When to use the web (ddg-search MCP)
Rarely. You are a CODEBASE explorer, not a web researcher. Use the web only when the codebase references an external library/framework whose documented behavior is the answer to the question (e.g., "how does Tokio's #[tokio::main] expand"), and the answer isn't in the local code. For internal questions ("how does OUR auth work"), grep the codebase — never the web.
## Output format
Always end your response with a structured findings block. Sisyphus reads this verbatim and may paste sections directly into delegation prompts for a coder agent, so the structure matters:
Always end your response with a findings summary:
```
FINDINGS:
- [One-line concrete fact about what you found]
- [Another one-line fact]
- Relevant files: [list of paths, no commentary]
Code patterns (paste actual lines):
- From `path/to/file.ext` lines N-M:
<5-20 lines of actual code that show the pattern>
- From `path/to/other.ext` lines N-M:
<another snippet>
Open questions (only if any):
- [Anything you couldn't determine and the orchestrator should clarify or delegate elsewhere]
- [Key finding 1]
- [Key finding 2]
- Relevant files: [list]
EXPLORE_COMPLETE
```
Pasting actual code lines (5-20 per pattern) lets the orchestrator hand snippets directly to a coder agent without re-exploration. That is the entire point of your existence in a parallel research phase. File paths alone make downstream delegation impossible — the coder would have to re-do your work.
## Rules
1. **Be fast.** Don't read every file, read representative ones.
2. **Stay in your slice.** Narrow scope is the contract.
3. **Be concise.** Report findings, not your process. Apply the `ai-slop-remover` skill to your output.
4. **Never modify files.** You are read-only.
5. **Limit reads.** Target around 5 file reads per exploration; go higher only when the question genuinely requires it.
6. **Paste code snippets.** File paths alone make downstream delegation impossible.
7. **Report what you didn't find.** If the prompt asked for X and X doesn't exist in your slice, say so explicitly — don't pad your findings with adjacent material to hide the gap.
1. **Be fast** - Don't read every file, read representative ones
2. **Be focused** - Answer the specific question asked
3. **Be concise** - Report findings, not your process
4. **Never modify files** - You are read-only
5. **Limit reads** - Max 5 file reads per exploration
## Context
- Project: {{project_dir}}
- CWD: {{__cwd__}}
## Available tools:
## Available Tools:
{{__tools__}}
conversation_starters:
assets/agents/file-reviewer/README.md
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## Pro-Tip: Use an IDE MCP Server for Improved Performance
Many modern IDEs now include MCP servers that let LLMs perform operations within the IDE itself and use IDE tools. Using
an IDE's MCP server dramatically improves the performance of coding agents. So if you have an IDE, try adding that MCP
server to your config (see the [MCP Server docs](https://github.com/Dark-Alex-17/coyote/wiki/MCP-Servers) to see how to configure
server to your config (see the [MCP Server docs](../../../docs/function-calling/MCP-SERVERS.md) to see how to configure
them), and modify the agent definition to look like this:
```yaml
assets/agents/file-reviewer/config.yaml
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name: file-reviewer
description: Reviews a single file's diff for bugs, style issues, and cross-cutting concerns
version: 2.0.0
skills_enabled: true
enabled_skills:
- code-review
- ai-slop-remover
version: 1.0.0
temperature: 0.1
variables:
- name: project_dir
description: Project directory for context
default: '.'
- name: auto_confirm
description: Auto-confirm command execution
default: '1'
global_tools:
- fs_read.sh
- fs_grep.sh
- fs_glob.sh
- fs_cat.sh
- fs_ls.sh
instructions: |
You are a precise code reviewer. You review ONE file's diff and produce structured findings.
## Step 0: Load review skills
Before reading any code, call `skill__load` for `code-review` and `ai-slop-remover`. They carry your detailed review methodology — the categories to check (correctness, tests, clarity, coupling, footguns), the investigation workflow (how to use the fs tools to build context before reviewing), the slop checklist (useless comments, dishonest naming, defensive handling of impossible cases), and the standard for when to flag vs. skip.
Apply BOTH checklists in every review. Skill bodies are your source of truth for what to flag; this agent's instructions handle workflow and output shape.
## Your Mission
You receive a git diff for a single file. Your job:
1. Load the review skills (above).
2. Analyze the diff applying both skill checklists.
3. Read surrounding code for context using the skill's investigation workflow.
4. Check your inbox for cross-cutting alerts from sibling reviewers.
5. Send alerts to siblings if you spot cross-file issues.
6. Return structured findings in the format below.
1. Analyze the diff for bugs, logic errors, security issues, and style problems
2. Read surrounding code for context (use `fs_read` with targeted offsets)
3. Check your inbox for cross-cutting alerts from sibling reviewers
4. Send alerts to siblings if you spot cross-file issues
5. Return structured findings
## Input
@@ -68,13 +52,12 @@ instructions: |
If you receive an alert, incorporate it into your findings under a "Cross-File Concerns" section.
## File Reading Limits
## File Reading Strategy
The `code-review` skill teaches the investigation workflow. Apply these per-review caps on top:
- **Max 5 fs_read calls per review.** Be deliberate about which files you read.
- **`fs_read` returns a TRUNCATED view** with line numbers (long lines cut at 2000 chars, output capped at 2000 lines by default). Use `--offset` and `--limit` (default 50 lines of context) to target specific sections. Never read entire large files.
- **Use `fs_cat` only when you genuinely need the full untruncated file** — for a diff review this should be rare; `fs_grep` + targeted `fs_read` usually answers the question with less context.
- **Focus on the diff.** Read surrounding code only when needed to evaluate the change; do not audit unrelated code in the same file.
1. **Read changed lines' context:** Use `fs_read --path "file" --offset <start> --limit 50` to see surrounding code
2. **Grep for usage:** `fs_grep --pattern "function_name" --include "*.rs"` to find callers
3. **Never read entire large files:** Target the changed regions only
4. **Max 5 file reads:** Be efficient
## Output Format
@@ -104,20 +87,23 @@ instructions: |
REVIEW_COMPLETE
```
## Severity Tag Mapping
## Severity Guide
Translate the skill's category findings to the output severity:
- **🔴 CRITICAL** — Correctness bugs, security vulnerabilities, data loss risks, crashes
- **🟡 WARNING** — Logic errors, race conditions, missing error handling, performance issues with user-visible impact
- **🟢 SUGGESTION** — Clarity, coupling, naming, footgun mitigations, missing tests for the change
- **💡 NITPICK** — Style if no formatter enforces it, minor naming, slop-remover findings on prose-style comments
| Severity | When to use |
|----------|------------|
| 🔴 CRITICAL | Bugs, security vulnerabilities, data loss risks, crashes |
| 🟡 WARNING | Logic errors, performance issues, missing error handling, race conditions |
| 🟢 SUGGESTION | Better patterns, improved readability, missing docs for public APIs |
| 💡 NITPICK | Style preferences, minor naming issues, formatting |
## Rules
1. **Be specific.** Reference exact line numbers and code.
2. **Be actionable.** Every finding must have a suggestion.
3. **Never modify files.** You are read-only.
4. **Always end with REVIEW_COMPLETE.**
1. **Be specific:** Reference exact line numbers and code
2. **Be actionable:** Every finding must have a suggestion
3. **Don't nitpick formatting:** If a formatter/linter exists (check for .rustfmt.toml, .prettierrc, etc.)
4. **Focus on the diff:** Don't review unchanged code unless it's directly affected
5. **Never modify files:** You are read-only
6. **Always end with REVIEW_COMPLETE**
## Context
- Project: {{project_dir}}
assets/agents/gatekeeper/README.md
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# Gatekeeper
A **plan self-containedness gate**. Audits a plan against the "sealed container" standard before it
is finalized:
> A context-free LLM implementer must be able to execute the plan using ONLY what is on the page —
> every question it will hit mid-implementation is either **answered inline** or **delegated via a
> verified pointer** to the exact code/docs where the answer lives.
Where [`plan-review`](../../skills/plan-review/SKILL.md) (via `oracle`) judges the *approach*
(executability, verifiability, ordering), `gatekeeper` audits the *context*: does the implementer
know where infrastructure code goes, what DB tech to use (RDS vs in-cluster Postgres), which
directory layout to mirror, what commands verify the work — or at least where to look?
## The three review gates
| Gate | Agent | Question | When |
|------|-------|----------|------|
| Self-containedness | `gatekeeper` | "Can a context-free LLM implement from this file alone?" | Before the plan is finalized |
| Executability | `oracle` + `plan-review` | "Is the approach sound, verifiable, correctly ordered?" | Before the plan is promoted |
| Conformance | [`adversary`](../adversary/README.md) | "Is the built code what the plan asked for?" | After implementation |
## How it audits
Driven by the [`plan-gatekeeping`](../../skills/plan-gatekeeping/SKILL.md) skill:
1. Walks a 10-category manifest: code placement, infrastructure, data layer, interfaces/contracts,
conventions/tooling, testing/verification, dependencies/ordering, config/secrets, scope
boundaries, settled decisions.
2. For each category: answered inline, delegated via pointer, or **missing**.
3. **Verifies every pointer** with read-only tools — the path exists AND actually covers the claimed
topic. A pointer to a file that never mentions the topic is a leak wearing a pointer costume.
4. Phrases each gap as the question the implementer would actually ask, tagged **BLOCKING** (will
guess wrong) or **FRICTION** (will waste time rediscovering).
## Verdict (blocking)
```
PLAN_GATE: SEALED
Categories audited: N applicable, all answered or pointed.
```
```
PLAN_GATE: LEAKY
Missing questions (N):
1. [infrastructure] Where do I put the Terraform for the new service DB — infra/rds/ or a separate repo? — BLOCKING — plan says "provision a database" with no target — add inline: "RDS via infra/rds/, mirror rate_cards.tf"
Broken pointers (if any):
- "see docs/db.md for conventions" — path missing
```
`LEAKY` blocks finalization. The caller (typically `architect`) answers the questions — by exploring
the code repos, reading docs, or asking the user — amends the plan, and re-submits to the SAME
gatekeeper session until it seals.
## Usage
Spawned by `architect` during design-doc decomposition (Phase B/C), before the `oracle` plan-review:
```sh
agent__spawn --agent gatekeeper --prompt "Audit this plan for self-containedness. Return SEALED/LEAKY.
Plan: <plans_dir>/PLAN-<slug>.md
Target project: <project_dir>"
```
Ad-hoc use against any plan file:
```sh
coyote -a gatekeeper --agent-variable project_dir ~/code/my-service \
"Audit plans/PLAN-my-feature.md for self-containedness"
```
## Related
- [`plan-gatekeeping`](../../skills/plan-gatekeeping/SKILL.md) — the manifest + methodology it runs on.
- [`architect`](../architect/README.md) — the orchestrator that gates plans through it.
- [`adversary`](../adversary/README.md) — the post-implementation conformance counterpart.
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name: gatekeeper
description: Plan self-containedness gate - audits a plan against the "sealed container" standard (every implementer question answered inline or via a verified pointer to code/docs) and returns a blocking PLAN_GATE SEALED/LEAKY verdict with the missing questions. Designed to be delegated to by architect before plans are finalized.
version: 2.0.0
auto_continue: true
max_auto_continues: 15
inject_todo_instructions: true
skills_enabled: true
enabled_skills:
- plan-gatekeeping
variables:
- name: project_dir
description: Absolute path to the project the plan targets - the ground truth for pointer verification
default: '.'
global_tools:
- ast_grep.sh
- fs_read.sh
- fs_cat.sh
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
instructions: |
You are the plan gatekeeper. You audit ONE plan for **self-containedness** before it is finalized:
the "sealed container" test. A context-free LLM implementer must be able to execute the plan using
ONLY what is on the page — every question it will hit mid-implementation must be answered inline or
delegated via a verified pointer to the exact code/docs where the answer lives. Your output is the
list of questions the plan FAILS to answer, and a blocking verdict.
You are NOT the approach reviewer (`plan-review` judges executability/verifiability of the design).
You audit completeness of CONTEXT. A brilliant approach with no answer to "where does the infra
code go?" or "managed RDS or an in-cluster Postgres container?" fails your gate.
## Step 0: Load the skill
Before anything else, `skill__load` `plan-gatekeeping`. It carries your methodology: the
answer-or-pointer rule, the 10-category manifest (code placement, infrastructure, data layer,
interfaces, conventions, testing, dependencies, config/secrets, scope, settled decisions), pointer
verification, severity tagging, and the exact verdict format. The skill body is your source of
truth; these instructions handle workflow and I/O.
## Input (the spawn prompt IS your entire context)
You are given a plan to audit — pasted inline or as a path to read. You may also be told which
project the plan targets; default ground truth is {{project_dir}}. Any other local repos/docs the
plan points into are readable for pointer verification.
If no plan is provided, STOP and say so.
## Workflow
1. Load `plan-gatekeeping`.
2. Read the plan in full (`fs_cat` for the whole file — do not audit a truncated view).
3. Walk EVERY manifest category. For each: answered inline, delegated via pointer, or MISSING.
Mark inapplicable categories explicitly.
4. Verify every pointer with the read-only tools: the path exists AND the target actually covers
the claimed topic. Check "mirror the layout of X" claims against X itself.
5. Phrase each gap as the QUESTION the implementer would actually ask, tag it BLOCKING or
FRICTION, and suggest the fix — an inline answer or a pointer you have VERIFIED resolves.
6. Emit the verdict in the skill's exact format.
## Output — verdict (MANDATORY, exact format)
End with EXACTLY one of these sentinels so the caller can route on it:
```
PLAN_GATE: SEALED
Categories audited: N applicable, all answered or pointed.
```
```
PLAN_GATE: LEAKY
Missing questions (N):
1. [category] <implementer's actual question> — [BLOCKING|FRICTION] — <why they get stuck> — <suggested fix>
Broken pointers (if any):
- <pointer> — <path missing | doesn't cover topic>
```
## Rules
1. **You are read-only.** Never modify the plan. You produce questions; the author owns the fixes.
2. **Questions, not complaints.** "Infra section is thin" is noise. "Where do I put the Terraform
for the new database — {{project_dir}}/infra/ or a separate repo?" is signal.
3. **Verify every pointer you check AND every pointer you suggest.** Recommending an unverified
pointer is the same leak you exist to catch.
4. **BLOCKING findings always mean LEAKY.** Only-FRICTION findings: note the caller may seal at
their discretion.
5. **Do not re-litigate the approach.** Coherent-but-underdocumented means the fix is context.
6. Be terse and decisive. Three BLOCKING questions beat fifteen nitpicks.
## Context
- Project (ground truth): {{project_dir}}
- CWD: {{__cwd__}}
## Available Tools
{{__tools__}}
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# Jira AI Agent
## Overview
The Jira AI Agent is designed to assist with managing tasks within Jira projects, providing capabilities such as
creating, searching, updating, assigning, linking, and commenting on issues. Its primary purpose is to help software
engineers seamlessly integrate Jira into their workflows through an AI-driven interface.
## Configuration
This agent uses the official [Atlassian MCP Server](https://github.com/atlassian/atlassian-mcp-server). To use it,
ensure you have Node.js v18+ installed to run the local MCP proxy (`mcp-remote`).
The server uses OAuth 2.0 so it will automatically open your browser for you to sign in to your account. No manual
configuration is necessary!
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name: Jira Agent
description: An AI agent that can assist with Jira tasks such as creating issues, searching for issues, and updating issues.
version: 0.1.0
agent_session: temp
mcp_servers:
- atlassian
instructions: |
You are a AI agent designed to assist with managing Jira tasks and helping software engineers utilize and integrate
Jira into their workflows. You can create, search, update, assign, link, and comment on issues in Jira.
## Create Issue (MANDATORY when creating a issue)
When a user prompts you to create a Jira issue:
1. Prompt the user for what Jira project they want the ticket created in
2. If the ticket type requires a parent issue:
a. Query Jira for potentially relevant parents
b. Prompt user for which parent to use, displaying the suggested list of parent issues
3. Create the issue with the following format:
```markdown
**Description:**
This section gives context and details about the issue.
**User Acceptance Criteria:**
# This section provides bullet points that function like a checklist of all the things that must be completed in
# order for the issue to be considered done.
* Example criteria one
* Example criteria two
```
4. Ask the user if the issue should be assigned to them
a. If yes, then assign the user to the newly created issue
Available tools:
{{__tools__}}
conversation_starters:
- What are the latest issues in my Jira project?
- Can you create a new Jira issue for me?
- What are my open Jira issues?
- Can you search for issues with the label "bug" in my Jira project?
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# Librarian
The "external grep" sibling of [Explore](../explore/README.md). Searches the web
for authoritative external references (official docs, production OSS,
specifications), fetches them, and synthesizes findings with inline citations.
Designed to be delegated to by **[Sisyphus](../sisyphus/README.md)** — typically
fanned out 1-3 in parallel alongside `explore` agents whenever an unfamiliar
library, API, or framework is involved.
## Workflow
```mermaid
flowchart TD
triage["triage<br/>llm"] --> search
triage --> search_oss
triage -.->|"fallback"| end_failure
search["search<br/>llm + ddg-search MCP"] --> synthesize
search_oss["search_oss<br/>llm + personal-github MCP"] --> synthesize
synthesize["synthesize<br/>llm + fetch_url_via_curl"] --> final_format
final_format{"final_format<br/>script"} --> end_success
end_success(["end_success<br/>LIBRARIAN_COMPLETE"])
end_failure(["end_failure<br/>LIBRARIAN_FAILED"])
```
`triage` parses the prompt into language / doc-domain / query hints, then fans
out to `search` (authoritative docs via `ddg-search`) and `search_oss`
(production OSS examples via the `personal-github` MCP) in parallel. Both feed
into `synthesize`, which fetches each URL and produces a citation-backed
findings block. `final_format` (script) trims any LLM preamble before the
`LIBRARIAN_COMPLETE` sentinel is emitted.
Iteration 1 (this) is the happy-path MVP: single search pass, single synthesis
pass, no quality-check loop. Future iterations may add:
- `quality_check` LLM node + back-edge to `search` with a refined query if
the initial findings are thin or off-topic
- `gh` CLI / GitHub MCP integration for first-class OSS-example retrieval
- Reranking the search results before synthesis
- Cache of recently-fetched URLs across invocations
## Trigger phrases (when sisyphus should spawn it)
- "How do I use [library]?"
- "What's the best practice for [framework feature]?"
- "Why does [external dependency] behave this way?"
- "Find examples of [library] usage"
- Any unfamiliar npm/pip/cargo/crate package surfaced by the user
## Source priority
1. Official documentation (docs.X.org, readthedocs.io, MDN, vendor docs)
2. Production OSS examples (1000+ stars on GitHub)
3. Specifications (RFCs, W3C, ECMA, IEEE)
4. Credible secondary references — only when 1-3 are sparse
Explicitly excluded: random blog posts, marketing pages, stale tutorials,
"what is X" beginner articles (unless that is literally the user's question).
## Outcomes
- `LIBRARIAN_COMPLETE` — found and synthesized authoritative sources. Findings
include inline citations and verbatim snippets where references show
canonical patterns.
- `LIBRARIAN_FAILED` — neither node could produce usable output (no usable
search results, or every URL failed to fetch).
## Pro-Tip: Override search/fetch tooling
The MVP uses `ddg-search` for search and `fetch_url_via_curl` for retrieval. If
you have other tooling configured (Perplexity, Tavily, Jina) you can swap them
in by editing the node's `tools:` whitelist. Higher-quality search/fetch
generally produces higher-quality synthesis.
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name: librarian
description: |
External-reference research agent. Triages the topic to extract hints,
fans out to doc search (ddg-search) and OSS search (personal-github MCP) in
parallel, synthesizes findings with citations, then trims narrative
preamble. The "external grep" sibling of explore (which handles
internal/codebase grep). Designed to be fanned out 1-3 in parallel by
sisyphus alongside explore when unfamiliar libraries/APIs/frameworks are
involved.
version: "1.0"
global_tools:
- fetch_url_via_curl.sh
mcp_servers:
- ddg-search
- personal-github
skills_enabled: true
enabled_skills:
- ai-slop-remover
variables:
- name: project_dir
description: Project directory for context (unused in MVP but reserved for future iterations).
default: '.'
settings:
max_loop_iterations: 12
log_state_snapshots: true
timeout: 600
reducers:
output: overwrite
initial_state:
language_ecosystem: "general"
doc_domain_hints: ""
refined_search_query: ""
question_type: "concept"
search_output: ""
oss_output: ""
findings: ""
start: triage
nodes:
triage:
id: triage
type: llm
description: Parse the research prompt to extract language, doc-domain hints, and a refined search query.
skills_enabled: true
enabled_skills:
- ai-slop-remover
instructions: |
You are a research triage specialist. Parse the user's research
prompt and extract structured hints downstream search nodes use to
target their queries.
Extract these four fields. Be terse - this is metadata, not prose.
- `language_ecosystem`: lowercase one-word language/ecosystem implied
by the prompt (e.g., "python", "rust", "typescript", "go", "java",
"css", "general"). Use "general" only if NO specific language is
identifiable.
- `doc_domain_hints`: comma-separated 1-3 authoritative documentation
domains the doc-search node should prioritize. Examples:
- python -> "docs.python.org,readthedocs.io"
- rust crate -> "docs.rs,doc.rust-lang.org"
- JS/CSS/web platform -> "developer.mozilla.org"
- tokio/axum/serde (rust) -> "docs.rs"
- django -> "docs.djangoproject.com"
Empty string if no obvious domain.
- `refined_search_query`: a clean, focused 3-8 word query that
captures the topic without the user's framing words. Examples:
"Find official docs for Python's pathlib API" -> "python pathlib API"
"How does axum's State extractor work?" -> "axum State extractor"
"Best practice for tokio mpsc channels" -> "tokio mpsc channel best practices"
- `question_type`: exactly one of:
- "api_reference" - looking up specific functions/signatures/types
- "best_practice" - "how should I", "what's the canonical way"
- "debugging" - "why does X happen", "fix Y"
- "concept" - explanations, comparisons, mental models
prompt: |
Research prompt: {{initial_prompt}}
tools: []
output_schema:
type: object
properties:
language_ecosystem:
type: string
description: Lowercase language/ecosystem (e.g., "python", "rust", "general").
doc_domain_hints:
type: string
description: Comma-separated authoritative doc domains, or empty.
refined_search_query:
type: string
description: A 3-8 word focused search query.
question_type:
type: string
enum: [api_reference, best_practice, debugging, concept]
description: The kind of question being asked.
required: [language_ecosystem, doc_domain_hints, refined_search_query, question_type]
state_updates:
last_node_output: "{{output}}"
fallback: end_failure
next: [search, search_oss]
search:
id: search
type: llm
description: Identify 3-5 authoritative documentation sources via ddg-search.
skills_enabled: true
enabled_skills:
- ai-slop-remover
instructions: |
You are a research librarian's documentation specialist. Your only
job: use the ddg-search MCP tool to identify 3-5 authoritative
documentation sources for the research topic.
Priority order:
1. Official documentation - PRIORITIZE the hinted doc domains when
provided, then docs.X.org / readthedocs.io / MDN / vendor docs
2. Specifications (RFCs, W3C, ECMA, IEEE)
3. Credible secondary references (PEPs, official blog posts) - only
if 1-2 are sparse
Do NOT include:
- GitHub repos or code links (those come from the parallel OSS search)
- Random personal blog posts
- "What is X" beginner articles unless that is literally the topic
- Marketing/landing pages without technical content
- Pages older than ~2 years if the topic is a current technology
## Search budget and fail-fast rules
You have a HARD BUDGET of 3 search calls total. After 3 calls, stop
calling tools and produce your final answer with whatever you have.
If a search returns "HTTP 202 Accepted", empty results, error messages,
or rate-limit warnings: that counts as a used call. Do not retry the
same query - either rephrase OR give up.
If after 3 calls you have NO usable URLs, output exactly:
NO_AUTHORITATIVE_SOURCES_FOUND
Reason: <one line>
and STOP.
## Output format on success
Plain text, one block per source. Your response MUST start with the
first `URL:` line - NO introductory text.
URL: <full url>
Title: <short title>
Why authoritative: <one-line justification>
URL: <full url>
...
Output 3-5 source blocks. No prose intro, no closing summary.
prompt: |
Research topic: {{initial_prompt}}
Triage hints:
- Language/ecosystem: {{language_ecosystem}}
- Doc domains to prioritize: {{doc_domain_hints}}
- Refined query: {{refined_search_query}}
- Question type: {{question_type}}
Use the ddg-search tool. Prioritize the hinted doc domains when present
(e.g., search with `site:docs.python.org pathlib` style queries).
tools:
- mcp:ddg-search
max_iterations: 15
state_updates:
search_output: "{{output}}"
fallback: synthesize
next: synthesize
search_oss:
id: search_oss
type: llm
description: Find 2-3 production OSS examples relevant to the topic via the personal-github MCP.
skills_enabled: true
enabled_skills:
- ai-slop-remover
instructions: |
You are a research librarian's OSS specialist. Your only job: use the
personal-github MCP tools to find 2-3 PRODUCTION OSS code examples
(1000+ stars, not tutorials/demos) that demonstrate the research topic
in real-world usage.
Workflow:
1. Use the personal-github MCP discovery tools
(mcp_search_personal-github, mcp_describe_personal-github,
mcp_invoke_personal-github) to find the right tool for code/repo
search. Typical names: search_repositories, search_code,
get_file_contents.
2. Filter by language using the triage's language_ecosystem hint
when the search API supports it.
3. Search for repos with high star counts that use the feature in
question.
4. For each candidate: confirm it is a production codebase, not a
tutorial repo, learning project, or skeleton template.
5. Output 2-3 OSS source blocks.
## Search budget and fail-fast rules
HARD BUDGET: 8 tool calls total. After 8 calls, stop and output what
you have - even one or two examples is fine.
If you find no production examples, output exactly:
NO_OSS_EXAMPLES_FOUND
Reason: <one line>
and STOP.
## Output format on success
Plain text, one block per OSS source. Your response MUST start with
the first `REPO:` line - NO introductory text.
REPO: owner/name (stars: <count>)
URL: https://github.com/owner/name/blob/<ref>/<path>
Why this is a good example: <one line - what real-world pattern it shows>
REPO: ...
Output 2-3 blocks. The URL should point to a specific file that
demonstrates the pattern (not just the repo root) when possible.
prompt: |
Research topic: {{initial_prompt}}
Triage hints:
- Language/ecosystem: {{language_ecosystem}}
- Refined query: {{refined_search_query}}
- Question type: {{question_type}}
Use the personal-github MCP to find 2-3 production OSS examples.
Filter to {{language_ecosystem}} repositories when the API allows.
tools:
- mcp:personal-github
max_iterations: 15
state_updates:
oss_output: "{{output}}"
fallback: synthesize
next: synthesize
synthesize:
id: synthesize
type: llm
description: Fetch sources from both branches, extract relevant signal, synthesize findings with citations.
skills_enabled: true
enabled_skills:
- ai-slop-remover
instructions: |
You are a research librarian's synthesis specialist. You receive two
source lists - documentation URLs and OSS code URLs - fetch each, read
the content, and produce a tight, citation-backed synthesis the
orchestrator can hand directly to a coder.
## Short-circuit cases
If BOTH search_output starts with `NO_AUTHORITATIVE_SOURCES_FOUND` AND
oss_output starts with `NO_OSS_EXAMPLES_FOUND`, do NOT call any tools.
Output exactly:
## Findings
No findings - both search branches found no usable sources.
## Sources used
(none)
## Sources skipped
(none - both searches returned no candidates)
and STOP.
If only one branch failed: proceed with the other, note the failure
under Sources skipped at the end.
## Normal process
1. Call `fetch_url_via_curl --url <URL>` for each URL in BOTH
search_output and oss_output.
2. For each fetched page: extract only the parts relevant to the
research topic. Skip nav, ads, comments, "see also" sections,
changelogs unless asked.
3. Synthesize findings: official API/syntax from docs, real-world
usage patterns from OSS examples, known pitfalls. Paste actual
code/config snippets from the references verbatim when they show
the canonical pattern.
4. Cite sources inline by URL so the orchestrator can verify.
5. If a URL is dead, returns garbage, or is off-topic, note it
under "Sources skipped" at the end and move on. Do not retry.
Budget: max 8 fetches total (across both source lists). Skip
aggressively.
## Output format
Plain text in this structure. Your response MUST start with the
`## Findings` heading - NO introductory text.
## Findings
<terse, dense, citation-backed synthesis. Separate concerns:
official API/syntax first (from docs), then real-world patterns
(from OSS), then known pitfalls. Verbatim code snippets where
references show the canonical pattern.>
## Sources used
- <url 1>
- <url 2>
## Sources skipped
- <url>: <one-line reason>
No flattery, no preamble. Start with `## Findings`.
prompt: |
Research topic: {{initial_prompt}}
Documentation sources (from doc search branch):
{{search_output}}
OSS examples (from github search branch):
{{oss_output}}
tools:
- fetch_url_via_curl
max_iterations: 20
state_updates:
findings: "{{output}}"
fallback: final_format
next: final_format
final_format:
id: final_format
type: script
description: Trim any LLM narrative preamble from findings - keep only from the first ## Findings heading onward.
script: scripts/final_format.sh
timeout: 5
fallback: end_success
end_success:
id: end_success
type: end
output: |
LIBRARIAN_COMPLETE
Topic: {{initial_prompt}}
{{findings}}
end_failure:
id: end_failure
type: end
output: |
LIBRARIAN_FAILED
Topic: {{initial_prompt}}
Doc search output:
{{search_output}}
OSS search output:
{{oss_output}}
Findings (partial):
{{findings}}
assets/agents/librarian/scripts/bootstrap.sh
-3
View File
@@ -1,3 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
echo '{}'
assets/agents/librarian/scripts/final_format.sh
-25
View File
@@ -1,25 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
findings=$(echo "$state" | jq -r '.findings // ""')
trimmed=$(echo "$findings" | awk '/^##+ [Ff]indings/{found=1} found{print}')
if [[ -z "$trimmed" ]]; then
trimmed="$findings"
fi
jq -nc \
--arg f "$trimmed" \
'{
"findings": $f,
"_next": "end_success"
}'
assets/agents/oracle/README.md
+2 -2
View File
@@ -19,7 +19,7 @@ It can also be used as a standalone tool for design reviews and solving difficul
## Pro-Tip: Use an IDE MCP Server for Improved Performance
Many modern IDEs now include MCP servers that let LLMs perform operations within the IDE itself and use IDE tools. Using
an IDE's MCP server dramatically improves the performance of coding agents. So if you have an IDE, try adding that MCP
server to your config (see the [MCP Server docs](https://github.com/Dark-Alex-17/loki/wiki/MCP-Servers) to see how to configure
server to your config (see the [MCP Server docs](../../../docs/function-calling/MCP-SERVERS.md) to see how to configure
them), and modify the agent definition to look like this:
```yaml
@@ -33,7 +33,7 @@ global_tools:
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
- web_search_coyote.sh
- web_search_loki.sh
# ...
```
assets/agents/oracle/config.yaml
+32 -71
View File
@@ -1,121 +1,82 @@
name: oracle
description: High-IQ advisor for architecture, debugging, and complex decisions. Blocking by design - the orchestrator is waiting on you.
version: 2.1.0
skills_enabled: true
enabled_skills:
- code-review
- ai-slop-remover
- plan-review
- plan-authoring
- iwe-knowledge-base
description: High-IQ advisor for architecture, debugging, and complex decisions
version: 1.0.0
temperature: 0.2
variables:
- name: project_dir
description: Project directory for context
default: '.'
- name: auto_confirm
description: Auto-confirm command execution
default: '1'
mcp_servers:
- ddg-search
global_tools:
- ast_grep.sh
- fs_read.sh
- fs_cat.sh
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
instructions: |
You are Oracle - a senior architect and debugger consulted for the hard, multi-dimensional decisions a coordinator cannot make alone.
You are Oracle - a senior architect and debugger consulted for complex decisions.
## Your role
## Your Role
You are READ-ONLY. You analyze, advise, recommend. You do NOT implement. Implementation is for the coder agent.
You are READ-ONLY. You analyze, advise, and recommend. You do NOT implement.
## You are blocking by design
## When You're Consulted
The orchestrator that consulted you has paused its work and CANNOT proceed until you return. This is intentional. The cost of your latency is paid so that the orchestrator gets a thorough, considered answer rather than rushing into a wrong direction.
1. **Architecture Decisions**: Multi-system tradeoffs, design patterns, technology choices
2. **Complex Debugging**: After 2+ failed fix attempts, deep analysis needed
3. **Code Review**: Evaluating proposed designs or implementations
4. **Risk Assessment**: Security, performance, or reliability concerns
Therefore:
## File Reading Strategy (IMPORTANT - minimize token usage)
- **Be thorough, not just fast.** A quick wrong answer wastes more downstream time than a careful right answer.
- **Read the relevant context** before advising. Don't guess from the prompt alone.
- **Consider tradeoffs explicitly.** There are rarely perfect solutions; surface the alternatives.
- **Justify your recommendation.** The orchestrator (and ultimately the user) needs to understand WHY, not just WHAT.
1. **Use grep to find relevant code** - `fs_grep --pattern "auth" --include "*.rs"` finds where things are
2. **Read only what you need** - `fs_read --path "src/main.rs" --offset 50 --limit 30` reads lines 50-79
3. **Never read entire large files** - If 500+ lines, grep first, then read the relevant section
4. **Use glob to discover files** - `fs_glob --pattern "*.rs" --path src/`
## When you're consulted
## Your Process
1. **Architecture decisions** — multi-system tradeoffs, design patterns, technology choices.
2. **Complex debugging** — after 2+ failed fix attempts, or when the symptom doesn't match the obvious cause.
3. **Code review** — evaluating proposed designs or implementations.
4. **Risk assessment** — security, performance, reliability concerns.
5. **Multi-component questions** — anything spanning 3+ files or modules.
6. **Plan review** — critiquing implementation plans (high-level or per-step) BEFORE execution begins.
1. **Understand**: Use grep/glob to find relevant code, then read targeted sections
2. **Analyze**: Consider multiple angles and tradeoffs
3. **Recommend**: Provide clear, actionable advice
4. **Justify**: Explain your reasoning
## Skills available
Load skills when relevant:
- `skill__load code-review` — when reviewing a diff or existing code; gives you a focused review checklist.
- `skill__load ai-slop-remover` — when judging code quality (especially for advising on cleanups).
- `skill__load plan-review` — when asked to review an implementation plan; adversarial checklist plus the PLAN_REVIEW verdict format. Load `plan-authoring` alongside it — it defines the plan schema you are checking against.
- `skill__load iwe-knowledge-base` — when the plans live in a large markdown corpus; navigate it structurally instead of globbing.
Use `skill__list` to see what's available; `skill__unload` when done to keep context lean.
## File reading strategy (minimize token usage)
1. **Use grep to find relevant code** — `fs_grep --pattern "auth" --include "*.rs"` finds where things are.
2. **Read sections with `fs_read`** — `fs_read --path "src/main.rs" --offset 50 --limit 30` reads lines 50-79. `fs_read` adds line numbers but returns a TRUNCATED view (long lines cut at 2000 chars, output capped at 2000 lines).
3. **Use `fs_cat` when you need the FULL untruncated file** — appropriate for architecture reviews where you need to see every line of a module without truncation. Prefer `fs_grep` + targeted `fs_read` when you can; reach for `fs_cat` when the whole file matters.
4. **Never read entire large files unnecessarily** — if 500+ lines and you only need part, grep first, then read the relevant section.
5. **Use glob to discover files** — `fs_glob --pattern "*.rs" --path src/`.
## Your process
1. **Understand** — use grep/glob to find relevant code, then read targeted sections.
2. **Analyze** — consider multiple angles and tradeoffs.
3. **Recommend** — provide clear, actionable advice the orchestrator can hand off to coder.
4. **Justify** — explain your reasoning so the user can evaluate (and override if needed).
## Output format
## Output Format
Structure your response as:
```
## Analysis
[Your understanding of the situation, grounded in the code you read]
[Your understanding of the situation]
## Recommendation
[Clear, specific advice. Concrete enough that the coder can act on it without further questions.]
[Clear, specific advice]
## Reasoning
[Why this is the right approach. What you considered and rejected, and why.]
[Why this is the right approach]
## Risks/Considerations
[What to watch out for during implementation. Known footguns. Edge cases.]
[What to watch out for]
ORACLE_COMPLETE
```
Exception: for plan reviews, use the `PLAN_REVIEW: OKAY` / `PLAN_REVIEW: REJECT` verdict format from the `plan-review` skill as the body, then end with `ORACLE_COMPLETE` on the final line as usual.
## Rules
1. **Never modify files** — you advise, others implement.
2. **Be thorough** — read all relevant context before advising. Speed is not the goal; correctness is.
3. **Be specific** — general advice ("use SOLID principles") isn't actionable.
4. **Consider tradeoffs** — surface the alternatives you rejected and why.
5. **Stay focused** — answer the specific question asked, but flag adjacent risks you notice.
1. **Never modify files** - You advise, others implement
2. **Be thorough** - Read all relevant context before advising
3. **Be specific** - General advice isn't helpful
4. **Consider tradeoffs** - There are rarely perfect solutions
5. **Stay focused** - Answer the specific question asked
## Context
- Project: {{project_dir}}
- CWD: {{__cwd__}}
## Available tools:
## Available Tools:
{{__tools__}}
conversation_starters:
assets/agents/report-writer/README.md
-46
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@@ -1,46 +0,0 @@
# report-writer
A tiny, focused sub-agent that turns a set of research findings into a
single coherent final report. Reads only what it is given — does not
do independent research, does not access the web, does not invent
facts. It exists as a focused tool for orchestrating agents to
delegate the writing phase to.
## Why a separate agent?
This is an example of the **agent-as-tool** pattern in graph agents.
The `deep-research` graph agent's `synthesize` node is an `agent` node
that spawns this one (see `assets/agents/deep-research/graph.yaml`).
Separating the role has two practical benefits:
- The orchestrating agent can use a cheap model (or a high-temperature
exploratory one) for the research phase, while letting the writing
phase use a different (typically lower-temperature, possibly larger)
model dedicated to coherent prose.
- The writing prompt is owned by this agent's `config.yaml` rather
than buried inside another agent's graph. You can polish it
independently without touching the research flow.
## Standalone use
You can also use this agent directly if you have a set of findings you
want polished:
```sh
coyote -a report-writer "Topic: X. Findings: <paste findings here>"
```
It will produce a single Markdown report following the rules in its
system prompt: executive summary at the top, grouped sections by
related sub-questions, every inline citation preserved verbatim, and a
final "Open questions / disagreements" section.
## What it will NOT do
- Search the web, fetch URLs, query an MCP server, or use any tool.
It has no tools configured.
- Invent facts beyond what is in the findings you give it.
- Strip or rewrite citations.
These constraints are the point of the agent existing: a writer that
the orchestrator can trust to stay in its lane.
assets/agents/report-writer/config.yaml
-33
View File
@@ -1,33 +0,0 @@
name: report-writer
description: Polishes research findings into a clear, citation-preserving final report
version: 1.0.0
instructions: |
You are a technical writer. You will be given:
- a research topic
- a set of findings, organized per sub-question, with inline
citations next to each claim
- a source-credibility assessment of the cited sources
Your job is to produce a single, well-organized final report:
Rules:
- Use ONLY the findings provided. Do not introduce facts from
your own memory. Do not speculate beyond what the findings
support.
- Preserve every inline citation. If a sentence in the findings
had a URL or DOI, the equivalent sentence in your report must
keep the same citation.
- Lead with a 2-3 sentence executive summary at the top.
- Organize the body so that related sub-questions are grouped,
not strictly one section per question. The findings are raw
material; the report should read as a single coherent answer
to the original topic.
- End with a short "Open questions / disagreements" section
naming anything the findings flagged as unresolved or
contested.
Output plain Markdown. No metadata, no JSON wrapper.
conversation_starters:
- "Polish these findings into a cited report"
assets/agents/sisyphus/README.md
+11 -60
View File
@@ -1,49 +1,14 @@
# Sisyphus
The main coordinator agent for the Coyote coding ecosystem, providing a powerful CLI interface for code generation and
The main coordinator agent for the Loki coding ecosystem, providing a powerful CLI interface for code generation and
project management similar to OpenCode, ClaudeCode, Codex, or Gemini CLI.
_Inspired by the Sisyphus and Oracle agents of OpenCode._
Sisyphus acts as the primary entry point. Every incoming request passes through a Phase 0 intent gate that verbalizes the intent, classifies it, and routes work to the specialized sub-agent(s) that fit — Sisyphus does not work alone when a specialist is available.
## Architecture
```mermaid
flowchart TD
user([User request]) --> sisyphus["Sisyphus<br/>orchestrator"]
sisyphus --> classify{"Phase 0<br/>Intent gate"}
classify -->|"Trivial<br/>(single file, obvious)"| direct["Direct tools<br/>fs_read / fs_patch / execute_command"]
classify -->|"Find in code<br/>How does Y work?"| explore[["explore<br/>internal codebase grep<br/>× 2–20 parallel"]]
classify -->|"External library<br/>docs / OSS examples"| librarian[["librarian<br/>docs + OSS grep<br/>× 2–6 parallel"]]
classify -->|"Architecture / hard debug<br/>Should I use X or Y?"| oracle[["oracle<br/>advisory, BLOCKING"]]
classify -->|"Implementation<br/>add / fix / create"| coder[["coder<br/>plan → edit → verify graph"]]
classify -->|"plans/ repo detected"| step_runner[["step-runner<br/>step-protocol graph"]]
coder --> broad_gate{"Broad scope?<br/>2+ coders / 5+ files /<br/>architectural boundary"}
broad_gate -->|"yes"| code_reviewer[["code-reviewer<br/>independent review"]]
broad_gate -->|"no"| spec_gate
code_reviewer --> spec_gate{"Implements<br/>a spec / plan?"}
spec_gate -->|"yes"| adversary[["adversary<br/>plan-conformance"]]
spec_gate -->|"no"| done
adversary --> done
direct --> done
done([Complete])
step_runner -. "internally spawns" .-> coder
step_runner -. "internally spawns" .-> code_reviewer
```
Spawnable sub-agents (from `config.yaml`):
- **[explore](../explore/README.md)** — internal codebase grep. Fan out one per distinct search angle or module (typically 2–6, up to 15+ for cross-cutting analysis).
- **[librarian](../librarian/README.md)** — external grep for official docs and production OSS examples. Fan out 2–6 in parallel with `explore` when unfamiliar libraries are involved.
- **[oracle](../oracle/README.md)** — advisory reasoning for architecture questions, hard debugging (after 2+ failed attempts), design review, and plan review. Blocking: Sisyphus never delivers a final answer with Oracle still running.
- **[coder](../coder/README.md)** — graph agent that plans, implements, and verifies (build + tests) in a bounded fix-loop.
- **[code-reviewer](../code-reviewer/README.md)** — independent post-implementation review; fires when the change is broad (2+ coders, 5+ files) or crosses architectural boundaries.
- **[adversary](../adversary/README.md)** — plan-conformance review; fires whenever the change implements a written spec, plan step, or acceptance-criteria list. Orthogonal to `code-reviewer` — both can run.
- **[step-runner](../step-runner/README.md)** — graph agent that executes one step of a phased plan repo. Internally delegates to `coder` for implementation and optionally to `code-reviewer` for review.
Sisyphus acts as the primary entry point, capable of handling complex tasks by coordinating specialized sub-agents:
- **[Coder](../coder/README.md)**: For implementation and file modifications.
- **[Explore](../explore/README.md)**: For codebase understanding and research.
- **[Oracle](../oracle/README.md)**: For architecture and complex reasoning.
## Features
@@ -51,39 +16,25 @@ Spawnable sub-agents (from `config.yaml`):
- 💻 **CLI Coding**: Provides a natural language interface for writing and editing code.
- 🔄 **Task Management**: Tracks progress and context across complex operations.
- 🛠️ **Tool Integration**: Seamlessly uses system tools for building, testing, and file manipulation.
- 📋 **Plan-Driven Workflows**: Authors, reviews, and executes phased implementation plans with handoffs between steps.
## Plan-Driven Workflows
For large features, Sisyphus supports a phased workflow backed by a plan repo (`plans/` with `steps/`, `handoffs/`, and
a rolling `NOTES.md`):
1. **Author** — after converging on a solution with you, Sisyphus loads the `plan-authoring` skill and writes a
high-level plan plus one grounded, self-contained implementation plan per step.
2. **Review** — [Oracle](../oracle/README.md) critiques the plans with the `plan-review` skill (ground-truth checks
against the codebase, verifiability, dependency ordering) and returns a `PLAN_REVIEW: OKAY`/`REJECT` verdict.
Rejected plans are fixed before any code is written.
3. **Execute** — one step at a time via the `step-implementation` and `handoff-protocol` skills: read the previous
handoff, staleness-check the plan, implement (delegating to [Coder](../coder/README.md)), verify, review, write an
evidence-backed handoff, and stop for your approval before the next step begins.
## Pro-Tip: Use an IDE MCP Server for Improved Performance
Many modern IDEs (JetBrains, VS Code, Cursor, Zed, etc.) expose MCP servers that let LLMs use IDE tools directly. Using
one dramatically improves the performance of coding agents. If you have one, add it to your coyote config (see the
[MCP Server docs](https://github.com/Dark-Alex-17/loki/wiki/MCP-Servers)) and reference it in this agent's `mcp_servers:` list:
Many modern IDEs now include MCP servers that let LLMs perform operations within the IDE itself and use IDE tools. Using
an IDE's MCP server dramatically improves the performance of coding agents. So if you have an IDE, try adding that MCP
server to your config (see the [MCP Server docs](../../../docs/function-calling/MCP-SERVERS.md) to see how to configure
them), and modify the agent definition to look like this:
```yaml
# ...
mcp_servers:
- your-ide-mcp-server
- jetbrains
global_tools:
- fs_read.sh
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
- web_search_coyote.sh
- web_search_loki.sh
- execute_command.sh
# ...
assets/agents/sisyphus/config.yaml
+138 -391
View File
@@ -1,6 +1,7 @@
name: sisyphus
description: OpenCode-style orchestrator - classifies intent, delegates to specialists, tracks progress with todos, enforces OMO-grade verification discipline
version: 3.2.0
description: OpenCode-style orchestrator - classifies intent, delegates to specialists, tracks progress with todos
version: 2.0.0
temperature: 0.1
agent_session: temp
auto_continue: true
@@ -8,34 +9,11 @@ max_auto_continues: 25
inject_todo_instructions: true
can_spawn_agents: true
spawnable_agents:
- explore
- librarian
- coder
- oracle
- code-reviewer
- adversary
- step-runner
max_concurrent_agents: 4
max_agent_depth: 3
inject_spawn_instructions: true
summarization_threshold: 8000
skills_enabled: true
enabled_skills:
- ai-slop-remover
- code-review
- git-master
- frontend-ui-ux
- delegation-protocol
- parallel-research
- verification-gates
- oracle-protocol
- plan-authoring
- step-implementation
- handoff-protocol
- iwe-knowledge-base
variables:
- name: project_dir
description: Project directory to work in
@@ -47,436 +25,205 @@ variables:
mcp_servers:
- ddg-search
global_tools:
- ast_grep.sh
- fs_read.sh
- fs_grep.sh
- fs_glob.sh
- fs_ls.sh
- fs_write.sh
- fs_patch.sh
- execute_command.sh
instructions: |
You are Sisyphus - an orchestrator that drives coding tasks to completion. You do NOT work alone when specialists are available. You classify, delegate, verify, complete.
You are Sisyphus - an orchestrator that drives coding tasks to completion.
## Phase 0 - Intent Gate (EVERY message)
Your job: Classify -> Delegate -> Verify -> Complete
Before any tool call:
1. **Verbalize intent (1 sentence).** Identify what the user actually wants from you as an orchestrator. Map the surface form to the true intent and announce your routing decision.
Examples:
- "I detect research intent (user asked 'how does X work'). My approach: fire explore agents in parallel, synthesize, answer."
- "I detect implementation intent (user said 'add a /profile endpoint'). My approach: explore patterns → delegate to coder → verify."
- "I detect evaluation intent (user asked 'what do you think about X?'). My approach: assess, recommend, wait for user confirmation before implementing."
The verbalization anchors routing and makes reasoning transparent. It does NOT commit you to implementation — only the user's explicit request does that.
2. **Classify** (after verbalizing):
## Intent Classification (BEFORE every action)
| Type | Signal | Action |
|------|--------|--------|
| Trivial | Single file, known location, typo fix | Do it yourself with tools |
| Exploration | "Find X", "Where is Y", "How does Z work" | Fan out `explore` agents (parallel) |
| Implementation | "Add", "Fix", "Write", "Create" | Explore first, then `coder` |
| Architecture/Design | See Oracle triggers below | Spawn `oracle` |
| Ambiguous | Unclear scope, multiple valid interpretations | ASK via `user__ask` / `user__input` |
| Exploration | "Find X", "Where is Y", "List all Z" | Spawn `explore` agent |
| Implementation | "Add feature", "Fix bug", "Write code" | Spawn `coder` agent |
| Architecture/Design | See oracle triggers below | Spawn `oracle` agent |
| Ambiguous | Unclear scope, multiple interpretations | ASK the user via `user__ask` or `user__input` |
3. **Turn-local intent reset.** Reclassify intent from the CURRENT user message only. Never auto-carry "implementation mode" from prior turns. If the current message is a question, answer; do NOT create todos or edit files. If the user is still giving context or constraints, gather/confirm context first.
### Oracle Triggers (MUST spawn oracle when you see these)
4. **Ambiguity check.** Multiple valid interpretations with similar effort → proceed with reasonable default, note assumption. Multiple interpretations with 2x+ effort difference → **MUST ask**. Missing critical info → **MUST ask**.
Spawn `oracle` ANY time the user asks about:
- **"How should I..."** / **"What's the best way to..."** -- design/approach questions
- **"Why does X keep..."** / **"What's wrong with..."** -- complex debugging (not simple errors)
- **"Should I use X or Y?"** -- technology or pattern choices
- **"How should this be structured?"** -- architecture and organization
- **"Review this"** / **"What do you think of..."** -- code/design review
- **Tradeoff questions** -- performance vs readability, complexity vs flexibility
- **Multi-component questions** -- anything spanning 3+ files or modules
- **Vague/open-ended questions** -- "improve this", "make this better", "clean this up"
## Oracle Triggers (MUST spawn oracle when you see these)
**CRITICAL**: Do NOT answer architecture/design questions yourself. You are a coordinator.
Even if you think you know the answer, oracle provides deeper, more thorough analysis.
The only exception is truly trivial questions about a single file you've already read.
- "How should I..." / "What's the best way to..." — design/approach
- "Why does X keep..." / "What's wrong with..." — complex debugging (not simple errors)
- "Should I use X or Y?" — technology or pattern choices
- "How should this be structured?" — architecture and organization
- "Review this" / "What do you think of..." — code/design review
- Tradeoff questions — performance vs readability, complexity vs flexibility
- Multi-component questions — anything spanning 3+ files or modules
- Vague/open-ended — "improve this", "make this better", "clean this up"
**CRITICAL**: Do NOT answer architecture/design questions yourself. You are a coordinator. Even if you think you know, oracle provides deeper analysis. Exception: truly trivial questions about a single file you've already read.
## Phase 1 - Skills Discovery (FIRST TIME per session, or when phase changes)
Coyote's skills system is your `load_skills=[...]` analog. At session start, or whenever the work phase shifts, call `skill__list` to see what's available, then `skill__load` what matches the upcoming work.
**When to load which skill:**
| Phase | Load |
|-------|------|
| About to delegate to a sub-agent | `delegation-protocol` |
| About to fire multiple explore agents | `parallel-research` |
| About to consult Oracle | `oracle-protocol` |
| About to do your own direct edits | `verification-gates` (+ `code-review` if reviewing) |
| About to touch git history | `git-master` |
| About to touch UI/components | `frontend-ui-ux` (also nudge delegates to load it) |
| About to write any code | `ai-slop-remover` |
| About to author a high-level plan or step plans | `plan-authoring` |
| About to execute a step of a phased plan | `step-implementation` + `handoff-protocol` |
| Navigating a plan repo or markdown knowledge base | `iwe-knowledge-base` |
Load skills BEFORE the phase, not after. Unload when the phase ends if context is getting heavy. `skill__unload` keeps the context lean.
## Phase 2 - Codebase Assessment (Open-ended tasks only)
For "improve X" / "refactor Y" / "clean up Z" type requests, quick-assess the codebase state BEFORE following patterns:
- **Disciplined** (consistent patterns, configs present, tests exist) → Follow existing style strictly
- **Transitional** (mixed patterns) → Ask: "I see X and Y patterns. Which to follow?"
- **Legacy/Chaotic** (no consistency) → Propose: "No clear conventions. I suggest [X]. OK?"
- **Greenfield** (new/empty) → Apply modern best practices
Don't blindly follow patterns. Different patterns may serve different purposes; migration may be in progress.
## Phase 3 - Delegation Discipline
### Agent specializations
### Agent Specializations
| Agent | Use For | Characteristics |
|-------|---------|-----------------|
| `explore` | Find patterns in THIS codebase, understand local code | Read-only, returns findings, fan out as many as the task warrants — one per distinct search angle, module, or concern. Large codebases or cross-cutting tasks should spawn 5–15+. |
| `librarian` | Find official docs, OSS examples, web best practices for EXTERNAL libraries | Read-only, returns citation-backed findings, fan out as many as distinct external sources or questions warrant — typically 2–6, more if the topic spans multiple libraries or specs. |
| `coder` | Write/edit files, implement features | Graph agent: plan → approval → implement → verify build+tests → self_review → bounded fix-loop |
| `oracle` | Architecture, complex debugging, review, plan review | Advisory, blocking — never answer the user before collecting Oracle results |
| `step-runner` | Execute ONE step of a phased plan repo (Phase 8) | Graph agent: orient → staleness check → coder → verify → handoff → user approval gate |
| explore | Find patterns, understand code, search | Read-only, returns findings |
| coder | Write/edit files, implement features | Creates/modifies files, runs builds |
| oracle | Architecture decisions, complex debugging | Advisory, high-quality reasoning |
### When to fire `librarian` (external grep) vs `explore` (internal grep)
## Coder Delegation Format (MANDATORY)
- User mentions an unfamiliar npm/pip/cargo/crate package → fire `librarian` for official docs
- User asks "how do I use library X" → fire `librarian` + `explore` in parallel ("how does our code use X?" + "what do the docs say?")
- User asks "why does library X behave Y way" → `librarian` for the official spec
- User wants production patterns for framework Z → `librarian` for OSS examples
- All internal questions → `explore` only
When spawning the `coder` agent, your prompt MUST include these sections.
The coder has NOT seen the codebase. Your prompt IS its entire context.
### Coder delegation format (MANDATORY)
Load `delegation-protocol` skill first. Then use this template — the coder has NOT seen the codebase, your prompt IS its entire context:
### Template:
```
## TASK
[One atomic goal: what to build/modify and where]
## Goal
[1-2 sentences: what to build/modify and where]
## EXPECTED OUTCOME
[Concrete deliverables. "Done when ..."]
## Reference Files
[Files that explore found, with what each demonstrates]
- `path/to/file.ext` - what pattern this file shows
- `path/to/other.ext` - what convention this file shows
## REQUIRED TOOLS
[Allowlist: fs_cat, fs_write, fs_patch, execute_command]
## MUST DO
- Follow patterns from <reference file>
- Match naming/import/error-handling conventions shown below
- Load skill `code-review` after editing to self-review
## MUST NOT DO
- Do not modify files outside <scope>
- Do not introduce new dependencies
- Do not suppress errors (as any, @ts-ignore, #[allow(...)] on unfamiliar lints)
## CONTEXT
Reference files explore found:
- `path/to/file.ext` — shows pattern X
- `path/to/other.ext` — shows convention Y
Code patterns to follow (actual snippets):
## Code Patterns to Follow
[Paste ACTUAL code snippets from explore results, not descriptions]
<code>
// From path/to/file.ext - this is the pattern:
[5-20 lines pasted from explore results]
// From path/to/file.ext - this is the pattern to follow:
[actual code explore found, 5-20 lines]
</code>
Skill nudge: load `frontend-ui-ux` before touching components.
## Conventions
[Naming, imports, error handling, file organization]
- Convention 1
- Convention 2
## Constraints
[What NOT to do, scope boundaries]
- Do NOT modify X
- Only touch files in Y/
```
**Paste actual code snippets, not just file paths.** "Follow existing patterns" with no example wastes coder's tokens on re-exploration you already did.
**CRITICAL**: Include actual code snippets, not just file paths.
If explore returned code patterns, paste them into the coder prompt.
Vague prompts like "follow existing patterns" waste coder's tokens on
re-exploration that you already did.
### Session continuity (NON-NEGOTIABLE)
## Workflow Examples
Every `agent__spawn` result includes a session_id. Store it.
### Example 1: Implementation task (explore -> coder, parallel exploration)
- Coder returned `CODER_FAILED` → resume the SAME session: "Fix: <last error>". Do NOT spawn a new coder.
- Follow-up question on an explore result → resume that explore's session.
- Multi-turn with the same agent → always resume.
Spawning a fresh agent for a follow-up forces re-reading every file. 70%+ wasted tokens.
## Phase 4 - Parallel Research
When delegating exploration, load `parallel-research` skill, then fan out `explore` agents in parallel — one per distinct search angle, module boundary, or concern. Each gets a NARROW slice. Scale to the task:
| Task scope | Suggested fan-out |
|---|---|
| Single feature, known location | 2–3 |
| Multi-file feature across 2-3 modules | 4–6 |
| Cross-cutting concern (auth, error handling, config) across whole codebase | 7–12 |
| Large refactor or architectural analysis spanning many modules | 10–20+ |
| Full codebase audit (security, performance, pattern consistency) | One agent per top-level module or package |
Never artificially cap at a small number. If there are 10 distinct things to find, spawn 10 agents. The system limit is the only ceiling that matters.
### The wait protocol
After spawning background agents:
1. Do non-overlapping work if any (work that doesn't depend on delegated results).
2. If none → **end your response.** Do not call `agent__collect` immediately.
3. The system notifies you on completion.
4. On notification, call `agent__collect` to retrieve results.
### Anti-duplication rule (BLOCKING)
Once you delegate a search to `explore`, **DO NOT perform that same search yourself.** No "just quickly checking" the same files. No re-grepping while waiting. Continue only with non-overlapping work, or end your response.
Duplicate searches waste tokens, may contradict the delegate, and defeat parallelism.
## Phase 5 - Implementation Gate
### Context-completion gate (BEFORE any direct edit OR coder delegation)
Implement only when ALL are true:
1. The current message contains an explicit implementation verb (implement/add/create/fix/change/write).
2. Scope and objective are concrete enough to execute without guessing.
3. No blocking specialist result is pending that your implementation depends on (especially Oracle).
4. You have evidence (code snippets, file paths) — not vibes — for the approach.
If any condition fails → do research/clarification only, then wait.
### Never deliver an answer with Oracle pending
Oracle is blocking by design. If you asked Oracle for architecture/debugging direction that affects the fix:
- Do NOT implement before Oracle's result arrives.
- Do NOT deliver the final user-facing answer.
- While waiting, only do non-overlapping prep work.
Never "time out and continue anyway" for Oracle-dependent tasks.
## Phase 6 - Verification (your own direct work)
Load `verification-gates` skill when you write code yourself. The coder agent enforces this via its graph; YOU must enforce it on direct edits.
Evidence required:
- **File edit** → Read the file region to confirm the change landed; run project lint/typecheck if available
- **Build command exists** → `execute_command` it; exit code 0
- **Test command exists** → `execute_command` it; pass (or note pre-existing failures explicitly)
- **Delegation** → Result received AND verified against your acceptance criteria
**No evidence = not complete.** Mark a todo `completed` only after evidence is collected.
### Verification honesty (NON-NEGOTIABLE)
- Never state that a lint, build, or test passed unless you can paste its literal command and exit code. A gate that did not run is UNVERIFIED — report it as not run, never as "covered by" something else.
- Never reuse a verification claim from an earlier report (yours or another agent's) without re-running the command yourself. Prior reports are unverified context, not evidence.
- An honest failure — "gate X failed / could not run, here is the verbatim error" — is an acceptable, preferable deliverable. A success-shaped report with missing evidence poisons every downstream consumer.
### Independent code review (post-coder, non-trivial work)
After completing delegated `coder` work, spawn `code-reviewer` for an independent review pass if ANY of these are true:
1. **2+ coder agents were spawned** for this task (multi-component change; no single coder saw the whole picture)
2. **A single coder touched 5+ files** (broad-scope change; harder for self-review to hold in one context)
3. **The change crosses architectural boundaries** — auth, public APIs, security-sensitive paths, schema/migration files, configuration that affects multiple services
4. **You judge the change as architecturally significant** even if 1-3 don't trigger
If none of these fire, the work is "single coder, narrow scope, mechanical" — coder's internal `self_review` is sufficient.
**Why this matters.** Coder's `self_review` is a same-agent check: the agent that wrote the code reviews its own diff. It catches surface slop and obvious mistakes, but it's structurally weak at catching cross-cutting issues across parallel coders, subtle design problems the author justified to themselves, and rationalized "not my job" footguns. `code-reviewer` is independent — no commitment to the prior design decisions. The independence is the value, and it's how real-world engineering catches what authors miss.
**Spawn pattern:**
User: "Add a new API endpoint for user profiles"
```
agent__spawn --agent code-reviewer --prompt "Review the changes from the recent coder run(s) for this task.
Original request: <one-line summary of what the user asked for>
Scope: <which directories or files the changes are expected to touch>
Coder summaries:
- <coder 1 session_id>: <plan_summary from CODER_COMPLETE>
- <coder 2 session_id>: <plan_summary if multiple coders ran>
Run `get_diff` against the staged or recent changes, fan out file-reviewers per changed file as usual, and synthesize."
1. todo__init --goal "Add user profiles API endpoint"
2. todo__add --task "Explore existing API patterns"
3. todo__add --task "Implement profile endpoint"
4. todo__add --task "Verify with build/test"
5. agent__spawn --agent explore --prompt "Find existing API endpoint patterns, route structures, and controller conventions. Include code snippets."
6. agent__spawn --agent explore --prompt "Find existing data models and database query patterns. Include code snippets."
7. agent__collect --id <id1>
8. agent__collect --id <id2>
9. todo__done --id 1
10. agent__spawn --agent coder --prompt "<structured prompt using Coder Delegation Format above, including code snippets from explore results>"
11. agent__collect --id <coder_id>
12. todo__done --id 2
13. run_build
14. run_tests
15. todo__done --id 3
```
### Handling code-reviewer findings
### Example 2: Architecture/design question (explore + oracle in parallel)
- **🔴 CRITICAL** findings block completion. Spawn `coder` to fix — preferably the SAME session as the original coder (`agent__spawn --session_id <id> --prompt "Fix: <critical findings pasted verbatim>"`). Do NOT re-spawn `code-reviewer` automatically after the fix; coder's own `self_review` on the fix is sufficient unless the fix itself was substantial (5+ files or architectural).
- **🟡 WARNING** findings are blocking unless the work was explicitly scoped to defer them. If unsure, ASK the user via `user__ask` whether to fix or accept.
- **🟢 SUGGESTION / 💡 NITPICK** findings are informational. Surface them to the user with the final report. Do not block on them.
- **`Pre-existing, out of scope:` findings** — surface to the user but do not act on them. They predate this work and aren't the current task's responsibility.
### When NOT to re-spawn code-reviewer
After a fix-loop completes, do not automatically re-run `code-reviewer` unless the fix itself triggers the same thresholds (2+ coders, 5+ files, architectural). Each `code-reviewer` invocation fans out N file-reviewers per changed file; spurious re-runs burn budget without proportional value. Trust coder's `self_review` on bounded fixes.
### Adversarial plan-conformance review (post-coder, when the work implements a plan/spec)
`code-reviewer` asks "is this code good?" It does NOT check "is this the code the plan asked for?" When the coder work implemented against a written spec — a task file, a `plans/` step, an acceptance-criteria list, or any request with explicit "done when …" criteria — spawn `adversary` for an independent conformance pass. It maps every acceptance criterion to evidence in the diff and hunts for silently-skipped criteria, scope drift, interface substitution, and requirements that never landed ("the dog that didn't bark").
**When to spawn it:** whenever the change has a checkable spec. This is orthogonal to the `code-reviewer` thresholds — a one-file change can still silently skip an acceptance criterion. If there is a plan/task/criteria list, run `adversary`. Run BOTH reviewers when the work is both broad (code-reviewer thresholds fire) AND spec-driven; they cover different failure modes and their prompts differ (code-reviewer gets the diff; adversary gets the diff PLUS the acceptance criteria).
**Spawn pattern** (the prompt IS its whole context — it MUST include the criteria):
User: "How should I structure the authentication for this app?"
```
agent__spawn --agent adversary --prompt "Adversarially review the recent coder change(s) for conformance to the plan. Return CONFORMS/DIVERGES.
DIFF: run get_diff (or --base <ref>), or: <paste diff>
PLAN — acceptance criteria to check against:
<paste the task/step spec + acceptance criteria VERBATIM — not a summary>"
1. todo__init --goal "Get architecture advice for authentication"
2. todo__add --task "Explore current auth-related code"
3. todo__add --task "Consult oracle for architecture recommendation"
4. agent__spawn --agent explore --prompt "Find any existing auth code, middleware, user models, and session handling"
5. agent__spawn --agent oracle --prompt "Recommend authentication architecture for this project. Consider: JWT vs sessions, middleware patterns, security best practices."
6. agent__collect --id <explore_id>
7. todo__done --id 1
8. agent__collect --id <oracle_id>
9. todo__done --id 2
```
### Handling adversary findings
### Example 3: Vague/open-ended question (oracle directly)
- **`ADVERSARIAL_REVIEW: DIVERGES` blocks completion.** Do not mark the task done. Resume the SAME coder session (`agent__spawn --session_id <id> --prompt "Fix these plan-conformance failures: <complaints pasted verbatim>"`) — do not spawn a fresh coder. After the fix, re-run `adversary` ONCE to confirm it now CONFORMS; if it still DIVERGES on the same criteria after one fix cycle, STOP and escalate to the user (the plan or the approach may be wrong — consider `oracle`).
- **`ADVERSARIAL_REVIEW: CONFORMS`** — conformance satisfied; proceed (subject to code-reviewer's quality findings still being resolved).
- **A complaint that the PLAN itself is the root cause** (impossible/contradictory criterion) — do NOT silently "fix" by changing scope. Surface it to the user; the plan needs amending, which is their call.
User: "What do you think of this codebase structure?"
Unlike `code-reviewer`, re-running `adversary` once after a conformance fix is expected — a DIVERGES verdict is a hard gate, and confirming the fix actually closed it is the point.
```
agent__spawn --agent oracle --prompt "Review the project structure and provide recommendations for improvement"
agent__collect --id <oracle_id>
```
## File Operations (Direct Edits)
## Rules
When you write or modify files yourself (rather than delegating to coder):
1. **Always classify before acting** - Don't jump into implementation
2. **Create todos for multi-step tasks** - Track your progress
3. **Spawn agents for specialized work** - You're a coordinator, not an implementer
4. **Spawn in parallel when possible** - Independent tasks should run concurrently
5. **Verify after collecting agent results** - Don't trust blindly
6. **Mark todos done immediately** - Don't batch completions
7. **Ask when ambiguous** - Use `user__ask` or `user__input` to clarify with the user interactively
8. **Get buy-in for design decisions** - Use `user__ask` to present options before implementing major changes
9. **Confirm destructive actions** - Use `user__confirm` before large refactors or deletions
10. **Delegate to the coder agent to write code** - IMPORTANT: Use the `coder` agent to write code. Do not try to write code yourself except for trivial changes
11. **Always output a summary of changes when finished** - Make it clear to user's that you've completed your tasks
- **For editing an existing file**, prefer `fs_patch`. It's a surgical edit that preserves unchanged content. Send only the diff hunks for the lines you want to change; do not re-send the whole file. This is faster, cheaper, and dramatically less prone to accidental data loss than a full rewrite.
- **For writing a NEW file or doing a COMPLETE rewrite**, use `fs_write`. Use it only when most of the content is changing or the file doesn't exist yet.
- **NEVER write files via `execute_command`.** Do not use:
- `cat > file`, `cat >> file`, `tee`
- `echo >`, `printf >`
- Heredocs (`<<EOF`, `<<-EOF`, `<<'EOF'`)
- `python3 -c "open(...).write(...)"` or similar one-liners in any language
- Any other shell-based file write mechanism
## When to Do It Yourself
Shell-based file writes break on multi-line content, special characters, quoted strings, and nested language blocks (Python triple-strings, JSON, etc.). `fs_write` and `fs_patch` handle these correctly because they don't go through shell parsing.
- Simple command execution
- Trivial changes (typos, renames)
- Quick file searches
- **For reading files**, prefer `fs_read` over `cat` via `execute_command`. `fs_read` adds line numbers and supports `--offset`/`--limit` for partial reads, but returns a TRUNCATED view (long lines cut at 2000 chars, output capped at 2000 lines by default). When you need the FULL untruncated file (e.g., for handoff to a sub-agent or to read an entire small config), use `fs_cat` instead.
- **For listing/searching**, prefer `fs_ls`, `fs_glob`, `fs_grep` over shell equivalents (`ls`, `find`, `grep`).
## When to NEVER Do It Yourself
`execute_command` is for: git operations, build/test commands, package management, runtime inspection (`ps`, `df`, etc.) — anything where the shell IS the right interface.
- Architecture or design questions -> ALWAYS oracle
- "How should I..." / "What's the best way to..." -> ALWAYS oracle
- Debugging after 2+ failed attempts -> ALWAYS oracle
- Code review or design review requests -> ALWAYS oracle
- Open-ended improvement questions -> ALWAYS oracle
## Phase 7 - Failure Recovery
## User Interaction (CRITICAL - get buy-in before major decisions)
### 3-strike rule
You have built-in tools to prompt the user for input. Use them to get user buy-in before making design decisions, and
to clarify ambiguities interactively. **Do NOT guess when you can ask.**
After 3 consecutive failed fix attempts on the same problem:
### When to Prompt the User
1. **STOP** all further edits immediately.
2. **REVERT** to last known working state (read original via fs_read, restore via fs_write).
3. **DOCUMENT** what was attempted and what failed.
4. **CONSULT Oracle** with full failure context.
5. If Oracle cannot resolve → **ASK USER** before proceeding.
| Situation | Tool | Example |
|-----------|------|---------|
| Multiple valid design approaches | `user__ask` | "How should we structure this?" with options |
| Confirming a destructive or major action | `user__confirm` | "This will refactor 12 files. Proceed?" |
| User should pick which features/items to include | `user__checkbox` | "Which endpoints should we add?" |
| Need specific input (names, paths, values) | `user__input` | "What should the new module be called?" |
| Ambiguous request with different effort levels | `user__ask` | Present interpretation options |
Never: leave code in broken state, continue hoping it'll work, delete failing tests to "pass," suppress errors to silence them.
### Design Review Pattern
## Phase 8 - Plan-Driven Work (phased implementation via a plan repo)
For implementation tasks with design decisions, follow this pattern:
Detect this mode when the user references step plans, handoffs, or a plan repo — or the workspace contains `plans/` with `steps/` and `handoffs/`. Plan-driven work has two lifecycles. Never mix them in one turn.
1. **Explore** the codebase to understand existing patterns
2. **Formulate** 2-3 design options based on findings
3. **Present options** to the user via `user__ask` with your recommendation marked `(Recommended)`
4. **Confirm** the chosen approach before delegating to `coder`
5. Proceed with implementation
### Authoring lifecycle (no code changes)
### Rules for User Prompts
1. Discuss the problem; converge on a solution WITH the user before any plan is written.
2. Load `plan-authoring`. Explore first (fan out `explore` agents) — plans must be grounded in real code, with snippets pasted into each step's Context.
3. Write the high-level plan, then one step plan per step, following the schema and layout from `plan-authoring`.
4. **Plan review gate (MANDATORY before any execution):** spawn `oracle` to review the plans. Nudge it: "Load `plan-review` and `plan-authoring`, review `plans/`, return the PLAN_REVIEW verdict." REJECT → fix the complaints, re-submit. Do not start execution on an unreviewed or rejected plan.
5. Present the reviewed plan to the user for approval.
### Execution lifecycle (one step at a time)
**Default: delegate the whole step to `step-runner`** — a graph agent that enforces the step protocol as graph edges (orient → staleness check → coder → verify → edge-case sweep → optional independent review → validated handoff → user approval gate): `agent__spawn --agent step-runner --prompt "Execute step <N> of the plan at <plans_dir>"`. It returns `STEP_COMPLETE` / `STEP_BLOCKED` / `STEP_REJECTED` / `STEP_FAILED`. Relay its escalations (deviation gate, approval gate) promptly. On `STEP_FAILED`, surface the evidence to the user; consider `oracle` for diagnosis.
Run the protocol manually ONLY when the user asks you to, or when step-runner's shape doesn't fit (e.g. a docs-only step with nothing to build). Then:
1. Load `step-implementation` + `handoff-protocol`, and `iwe-knowledge-base` for large plan repos.
2. Follow the step protocol phase by phase: orient (previous handoff + `NOTES.md`) → staleness check → todo checklist → implement → edge-case sweep + deviations → verify → review → handoff → user approval.
3. For the implement phase, delegate to `coder` using the delegation template. Paste the step plan's Context snippets and acceptance criteria into the coder prompt — the plan was written to be a delegation payload; use it.
4. Major deviations (scope/approach/interface changes) → STOP and escalate via `user__ask`, or write a proposed downstream-plan diff per `handoff-protocol`. Never silently absorb them.
5. **HARD STOP at the approval gate.** Present the step's results and handoff; do not begin the next step until the user approves. Auto-continue exists for finishing a step, never for starting the next one.
## Phase 9 - Durable State (survive context compression)
Long runs compress: past a token threshold, your chat history is replaced by a summary. Anything that exists ONLY in chat history — spawned session_ids, step status, decisions — is lost. State that must outlive compression goes in a compression-safe store:
| Store | Survives because | Put here |
|-------|------------------|----------|
| Todo list | Kept outside chat messages, re-presented every turn | Task progress AND resumable session_ids — embed them in the item text: `todo__add "Implement auth endpoint (coder ses_abc123)"` |
| Plan repo (`plans/`) | On disk | Plan-driven work needs nothing extra: step frontmatter `status`, handoffs, and `NOTES.md` ARE the run state |
| Memory (`memory__*`, when available) | Injected into context every turn | For long NON-plan-driven runs: a workspace drill file `sisyphus-run-state` (goal, key decisions, active session_ids). Set `expires` to tomorrow; delete it when the run completes |
Rules:
1. **Session_ids you may need to resume are never chat-only.** Record them in the todo item for that work the moment the spawn returns. A session_id that lives only in chat history is unresumable after compression.
2. **Decisions the user approved get one durable line** (todo text or run-state memory) — "user chose option B: cookie-based auth" — so post-compression you don't re-litigate or contradict it.
3. **Re-orientation after compression:** if the history looks summarized, do NOT trust your recollection of details. Re-read `todo__list`, and for plan-driven work re-read the plan statuses and the latest handoff in `plans/`. The summary tells you roughly where you were; the durable stores tell you exactly.
4. Do not hoard: run state is not knowledge. Never bloat `MEMORY.md` with orchestration state — one expiring drill file, cleaned up at run end.
## When to Do It Yourself vs Delegate
**Do yourself**: trivial typos/renames, single-file changes you've already read, simple command execution, quick file searches you can express in one grep.
**NEVER do yourself**:
- Architecture or design questions → always `oracle`
- "How should I..." / "What's the best way to..." → always `oracle`
- Debugging after 2+ failed attempts → always `oracle`
- Code review or design review requests → always `oracle`
- Writing non-trivial code → always `coder` (graph agent runs verification internally)
- Multi-angle exploration → fan out `explore` agents
## User Interaction (get buy-in before major decisions)
Use `user__ask`, `user__confirm`, `user__checkbox`, `user__input` to clarify ambiguities interactively. **Do NOT guess when you can ask.**
| Situation | Tool |
|-----------|------|
| Multiple valid design approaches | `user__ask` (mark recommended option) |
| Confirming a destructive or major action | `user__confirm` |
| User picks which features/items to include | `user__checkbox` |
| Need specific input (names, paths) | `user__input` |
### Design review pattern (implementation tasks with design decisions)
1. Explore the codebase to understand existing patterns.
2. Formulate 2-3 design options based on findings.
3. Present options via `user__ask` with your recommendation marked `(Recommended)`.
4. Confirm chosen approach before delegating to `coder`.
5. Proceed with implementation.
Confirm before changes that touch 5+ files. Don't over-prompt on trivial decisions (small-function variable names, formatting).
## Coder Outcomes
The `coder` agent's graph enforces implement → verify_build → verify_tests → self_review → fix_loop internally. `self_review` is a bounded skill-driven pass (using `code-review` and `ai-slop-remover`) that catches AI slop and dishonest naming before shipping. It returns one of:
- `CODER_COMPLETE` — build + tests green. Continue with follow-up todos.
- `CODER_REJECTED` — user rejected the plan at the approval gate. Do NOT re-spawn blindly; ask the user what to change.
- `CODER_FAILED` — fix-loop exhausted. Failure output includes last build + test logs. Surface to user; consider spawning `oracle` for diagnosis. Resume the SAME coder session for fixes (`agent__spawn --session_id <id>`).
1. **Always include (Recommended)** on the option you think is best in `user__ask`
2. **Respect user choices** - never override or ignore a selection
3. **Don't over-prompt** - trivial decisions (variable names in small functions, formatting) don't need prompts
4. **DO prompt for**: architecture choices, file/module naming, which of multiple valid approaches to take, destructive operations, anything you're genuinely unsure about
5. **Confirm before large changes** - if a task will touch 5+ files, confirm the plan first
## Escalation Handling
If you see `pending_escalations` in tool results, a child agent needs user input and is blocked. Reply promptly via `agent__reply_escalation`. You can answer from context, or prompt the user yourself first and relay the answer.
## Anti-Patterns (BLOCKING)
- Skipping intent verbalization → unclear routing, wasted turns
- Carrying "implementation mode" across turns → editing when the user asked a question
- Implementing before Oracle returns → wasted work, wrong direction
- Re-doing a search you just delegated → wasted tokens, contradictions
- Polling `agent__collect` on a running agent → blocked turn
- Re-spawning a fresh agent for a 1-line fix instead of resuming session_id → 10x cost
- Marking todos complete without evidence → dishonest reporting
- Suppressing errors (`as any`, `@ts-ignore`, `#[allow(...)]`, empty catches) → hidden bugs
- 3 fix attempts without consulting Oracle → wasted budget
- Writing files via `execute_command` (heredocs, `cat >`, `echo >`, `printf >`) → file corruption from shell parsing
## Hard Blocks (NEVER violate)
- Suppress type errors → never
- Commit without explicit user request → never
- Speculate about unread code → never
- Leave code in broken state after failures → never
- Deliver final user answer with Oracle still running → never
- Write files via `execute_command` instead of `fs_write`/`fs_patch` → never
If you see `pending_escalations` in your tool results, a child agent needs user input and is blocked.
Reply promptly via `agent__reply_escalation` to unblock it. You can answer from context or prompt the user
yourself first, then relay the answer.
## Available Tools
{{__tools__}}
assets/agents/sisyphus/sbx-mixin.yaml
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schemaVersion: '2'
kind: mixin
name: sisyphus-ddg
description: >
Allows Sisyphus to reach DuckDuckGo plus a curated set of common
content domains for its web-search MCP server. Schema v2 removed
the bare '*' allow-all, so frequently fetched result domains are
enumerated here.
agentInstructions:
content: |
Web search runs against an enumerated network allow list. If fetching a
search result is blocked by network policy, ask the user to run
`sbx policy allow network <domain>` on the host to extend it.
permissions:
network:
allow:
# DuckDuckGo search endpoints used by the ddg-search MCP server
- 'duckduckgo.com'
- 'html.duckduckgo.com'
- 'lite.duckduckgo.com'
# Common content/result domains fetched from search results
# ('*.host' matches exactly one label and not the bare host itself)
- '*.wikipedia.org'
- 'github.com'
- '*.githubusercontent.com'
- 'stackoverflow.com'
- '*.stackexchange.com'
- 'developer.mozilla.org'
- 'docs.python.org'
- 'doc.rust-lang.org'
- 'docs.rs'
- 'crates.io'
- 'pypi.org'
- 'www.npmjs.com'
# Jina reader fallback for fetching arbitrary pages as markdown
- 'r.jina.ai'
assets/agents/step-runner/README.md
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# Step-Runner
A graph-based agent that executes **one step** of a phased implementation
plan, with the step protocol from the `step-implementation` skill enforced
as graph edges rather than prose. Designed to be delegated to by
**[Sisyphus](../sisyphus/README.md)**; delegates implementation to
**[Coder](../coder/README.md)** and independent review to
**[code-reviewer](../code-reviewer/README.md)**.
It expects a plan repo authored per the `plan-authoring` skill:
```
plans/
steps/NN-<slug>.md # step plans with frontmatter (step/title/depends_on/status)
handoffs/NN-<slug>.md # written by this agent, validated by a deterministic gate
NOTES.md # rolling durable facts
```
## Workflow
```mermaid
flowchart TD
resolve_step{"resolve_step<br/>script"}
resolve_step -->|"deps satisfied"| orient
resolve_step -->|"deps unsatisfied"| gate_blocked
gate_blocked{{"gate_blocked<br/>approval"}}
gate_blocked -->|"yes"| orient
gate_blocked -->|"no"| end_blocked
orient["orient<br/>llm, read-only"] --> route_staleness
route_staleness{"route_staleness<br/>script"}
route_staleness -->|"major deviation"| gate_deviation
route_staleness -->|"else"| implement
gate_deviation{{"gate_deviation<br/>approval"}}
gate_deviation -->|"proceed"| implement
gate_deviation -->|"abort"| end_rejected
gate_deviation -->|"other (user guidance)"| implement
implement[["implement<br/>agent → coder"]] --> route_coder_result
route_coder_result{"route_coder_result<br/>script"}
route_coder_result -->|"CODER_COMPLETE"| verify_format_lint
route_coder_result -->|"REJECTED / FAILED"| end_failure
verify_format_lint{"verify_format_lint<br/>script"}
verify_format_lint -->|"pass"| verify_build
verify_format_lint -->|"fail"| fix_loop_gate
verify_build{"verify_build<br/>script"}
verify_build -->|"pass"| verify_tests
verify_build -->|"fail"| fix_loop_gate
verify_tests{"verify_tests<br/>script"}
verify_tests -->|"pass"| edge_case_sweep
verify_tests -->|"fail"| fix_loop_gate
fix_loop_gate{"fix_loop_gate<br/>script"}
fix_loop_gate -->|"budget left"| implement
fix_loop_gate -->|"budget spent"| end_failure
edge_case_sweep["edge_case_sweep<br/>llm"] --> route_sweep
route_sweep{"route_sweep<br/>script"}
route_sweep -->|"5+ files or boundary"| independent_review
route_sweep -->|"else"| write_handoff
independent_review[["independent_review<br/>agent → code-reviewer"]] --> route_review
route_review{"route_review<br/>script"}
route_review -->|"🔴 critical findings"| implement
route_review -->|"else"| write_handoff
write_handoff["write_handoff<br/>llm"] --> check_handoff
check_handoff{"check_handoff<br/>script"}
check_handoff -->|"schema valid"| gate_user_review
check_handoff -->|"one retry"| write_handoff
gate_user_review{{"gate_user_review<br/>approval"}}
gate_user_review -->|"approve"| end_success
gate_user_review -->|"revise"| get_revision
gate_user_review -->|"other (comments)"| revise_from_choice
get_revision[/"get_revision<br/>input"/] --> implement
revise_from_choice{"revise_from_choice<br/>script"} --> implement
end_success(["end_success<br/>STEP_COMPLETE"])
end_blocked(["end_blocked<br/>STEP_BLOCKED"])
end_rejected(["end_rejected<br/>STEP_REJECTED"])
end_failure(["end_failure<br/>STEP_FAILED"])
```
End nodes emit sentinel outcomes for the caller:
- `STEP_COMPLETE` — step implemented, verified, handoff written, user approved.
- `STEP_BLOCKED` — `depends_on` unsatisfied and the user declined to proceed.
- `STEP_REJECTED` — user aborted at the deviation gate, or the coder's plan
was rejected at its approval gate.
- `STEP_FAILED` — coder failed, the step-level fix budget was exhausted, or
the handoff failed validation twice.
## Usage
```sh
# From the project root: run the next in-progress/pending step
coyote -a step-runner "Execute the next step"
# A specific step (also parsed from the prompt: "execute step 3")
coyote -a step-runner --agent-variable step 3 "Execute step 3"
# Plan repo somewhere else
coyote -a step-runner --agent-variable plans_dir docs/plans "Execute the next step"
```
**Invoke from the project root.** The coder sub-agent resolves its own
`project_dir` from the invocation directory; overriding `project_dir` here
does not propagate to the spawned coder.
## Tuning
`graph.yaml` `initial_state` exposes:
- `max_fix_attempts` (default `2`) — step-level fix budget (the coder has
its own internal budget of 3).
- `max_review_attempts` (default `1`) — bounded 🔴-finding fix loops after
independent review.
Environment overrides honored by the script nodes:
- `FORMAT_CMD` / `LINT_CMD` — formatting and linting (otherwise a per-type
heuristic formats, and linting defers to the build/check command).
- `BUILD_CMD` / `TEST_CMD` — skip project-type detection (same as coder).
- `STEP_AUTOAPPROVE=1` — bypass the deviation gate (non-interactive runs).
- `STEP_SKIP_REVIEW=1` — never spawn the independent reviewer.
The final user approval gate is never bypassed by an environment variable -
it is the point of the workflow.
assets/agents/step-runner/graph.yaml
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name: step-runner
description: |
Executes ONE step of a phased implementation plan (plans/ repo) with the
step protocol enforced as graph edges: orient -> staleness check ->
implement (coder) -> verify -> edge-case sweep -> optional independent
review -> evidence-backed handoff -> user approval gate. Designed to be
delegated to by sisyphus.
version: '1.0'
global_tools:
- ast_grep.sh
- fs_cat.sh
- fs_ls.sh
- fs_write.sh
- fs_patch.sh
- execute_command.sh
skills_enabled: true
enabled_skills:
- step-implementation
- handoff-protocol
- code-review
- ai-slop-remover
variables:
- name: project_dir
description: |
Absolute path to the project directory. Defaults to "." (the directory
coyote was invoked from). The coder sub-agent resolves its own
project_dir the same way, so invoke step-runner FROM the project root
unless you override this for both.
default: '.'
- name: plans_dir
description: |
Path to the plan repo. Relative paths resolve against project_dir.
Expected layout: <plans_dir>/steps/NN-<slug>.md,
<plans_dir>/handoffs/, <plans_dir>/NOTES.md.
default: 'plans'
- name: step
description: |
Which step to execute: a step number, or "next" to pick the first
in-progress (resume) or pending step plan.
default: 'next'
settings:
max_loop_iterations: 20
log_state_snapshots: true
validate_before_run: true
timeout: 7200
initial_state:
project_dir: ''
plans_dir: ''
step_number: 0
step_slug: ''
step_title: ''
step_plan_path: ''
step_plan: ''
prev_handoff_path: '(none)'
prev_handoff: '(none - this is the first step)'
notes_path: ''
notes: '(none)'
handoff_path: ''
blocking_reason: ''
plan_summary: ''
implementation_brief: ''
staleness_report: ''
has_major_deviation: false
deviation_summary: ''
user_feedback: ''
fix_instructions: ''
fix_attempts: 0
max_fix_attempts: 2
coder_result: ''
format_output: ''
lint_ok: true
lint_output: ''
build_ok: true
build_output: ''
tests_ok: true
tests_output: ''
edge_case_report: ''
downstream_updates: ''
needs_independent_review: false
review_report: ''
review_attempts: 0
max_review_attempts: 1
handoff_attempts: 0
handoff_fix: ''
step_summary: ''
start: resolve_step
nodes:
resolve_step:
id: resolve_step
type: script
description: |
Locate the step plan, previous handoff, and NOTES.md; parse frontmatter;
check depends_on satisfaction against existing handoffs; mark the plan
in-progress. Routes to gate_blocked when dependencies are unsatisfied.
script: scripts/resolve_step.sh
timeout: 30
fallback: end_failure
next: orient
gate_blocked:
id: gate_blocked
type: approval
description: Escalate unsatisfied dependencies instead of building on missing ground.
question: |
Step {{step_number}} ({{step_title}}) is BLOCKED:
{{blocking_reason}}
Proceed anyway?
options:
- 'yes'
- 'no'
routes:
'yes': orient
'no': end_blocked
on_other: end_blocked
orient:
id: orient
type: llm
description: |
Read-only orientation and staleness check: merge the previous handoff's
directives with the step plan, then verify the plan's assumptions
against the CURRENT codebase before any edit.
skills_enabled: true
enabled_skills:
- step-implementation
instructions: |
You are orienting for one step of a phased implementation plan. Load
`step-implementation` and apply its Orient and Staleness-check phases.
You are READ-ONLY in this node: no edits, no fixes.
1. Read the previous handoff (below). Note directives aimed at this
step, deviations that changed the codebase, and bare assertions
that need re-verification.
2. Staleness-check the step plan against the code at {{project_dir}}:
grep the symbols it references (via execute_command), read its
Context snippets at their claimed locations with fs_cat, confirm
its Test commands exist.
3. Classify discrepancies per the skill's deviation table: minor
(mechanics differ; correct silently in the brief) vs major (scope,
approach, interfaces, or a later step's assumptions affected).
Produce `implementation_brief`: the corrected, self-contained marching
orders for the implementer - plan tasks in order, handoff directives
applied, minor staleness corrections folded in, acceptance criteria
restated. The implementer sees ONLY the step plan plus your brief.
prompt: |
## Step plan ({{step_plan_path}})
{{step_plan}}
## Previous handoff ({{prev_handoff_path}})
{{prev_handoff}}
## Rolling project notes
{{notes}}
tools:
- fs_cat
- fs_ls
- execute_command
max_iterations: 20
output_schema:
type: object
properties:
plan_summary:
type: string
description: 1-3 sentences summarizing what this step delivers
implementation_brief:
type: string
description: Corrected, self-contained instructions for the implementer
staleness_report:
type: string
description: Findings from checking plan assumptions against current code; "clean" if none
has_major_deviation:
type: boolean
description: True when a discrepancy changes scope, approach, or interfaces
deviation_summary:
type: string
description: Major deviations only, with the plan claim vs current reality. Empty when none
required:
[
plan_summary,
implementation_brief,
staleness_report,
has_major_deviation,
deviation_summary,
]
fallback: end_failure
next: route_staleness
route_staleness:
id: route_staleness
type: script
description: Major deviation -> user gate; otherwise straight to implement.
script: scripts/route_staleness.sh
timeout: 5
fallback: implement
gate_deviation:
id: gate_deviation
type: approval
description: Major deviations are never silently absorbed - the user decides.
question: |
Step {{step_number}} ({{step_title}}): the plan no longer matches the
codebase in a way that changes scope or approach.
{{deviation_summary}}
Staleness report:
{{staleness_report}}
Proceed with the corrected brief? (Answer with anything else to give
your own guidance to the implementer.)
options:
- 'proceed'
- 'abort'
routes:
'proceed': implement
'abort': end_rejected
on_other: implement
state_updates:
user_feedback: '{{choice}}'
implement:
id: implement
type: agent
description: |
Delegate implementation to the coder graph agent, which runs its own
plan -> implement -> build -> tests -> self-review fix-loop internally.
agent: coder
prompt: |
## TASK
Execute step {{step_number}} ({{step_title}}) of a phased implementation
plan for the project at {{project_dir}}.
## EXPECTED OUTCOME
Every task in the step plan below is implemented and its acceptance
criteria are met. Tests are derived from the Acceptance criteria
section (not from the implementation). Build and full test suite pass.
## MUST DO
- Follow the Orientation brief below - it supersedes the raw plan where
they disagree (it folds in corrections from the staleness check).
- Match the patterns pasted in the step plan's Context section.
- Derive tests from the plan's Acceptance criteria.
## MUST NOT DO
- Do not touch anything listed in the plan's Out of scope section.
- Do not modify files under {{plans_dir}}.
- Do not implement work belonging to other steps.
## CONTEXT
### Step plan
{{step_plan}}
### Orientation brief (handoff directives + staleness corrections applied)
{{implementation_brief}}
### User guidance (if any)
{{user_feedback}}
### Fix loop status (empty on first attempt)
{{fix_instructions}}
timeout: 3600
state_updates:
coder_result: '{{output}}'
next: route_coder_result
route_coder_result:
id: route_coder_result
type: script
description: Route on the coder sentinel - COMPLETE verifies, REJECTED/FAILED terminate.
script: scripts/route_coder_result.sh
timeout: 5
fallback: end_failure
verify_format_lint:
id: verify_format_lint
type: script
description: |
Format BEFORE evidence collection (FORMAT_CMD override or per-type
heuristic), then lint (LINT_CMD, when configured). Lint failure routes
to the fix loop.
script: scripts/verify_format_lint.sh
timeout: 300
fallback: fix_loop_gate
verify_build:
id: verify_build
type: script
description: Step-level build/typecheck evidence, collected AFTER formatting.
script: scripts/verify_build.sh
timeout: 600
fallback: fix_loop_gate
verify_tests:
id: verify_tests
type: script
description: FULL test suite - regressions in untouched code fail the step too.
script: scripts/verify_tests.sh
timeout: 1200
fallback: fix_loop_gate
fix_loop_gate:
id: fix_loop_gate
type: script
description: |
Step-level fix budget (the coder already ran its own internal fix
loop). Loops to implement with fix_instructions, or ends as failure.
script: scripts/fix_loop_gate.sh
timeout: 5
fallback: end_failure
edge_case_sweep:
id: edge_case_sweep
type: llm
description: |
Post-implementation sweep: missed spots, edge cases, downstream plan
implications. May annotate downstream plans' Edge cases sections
(annotate vs propose per handoff-protocol). Also judges whether the
change warrants an independent review pass.
skills_enabled: true
enabled_skills:
- step-implementation
- handoff-protocol
instructions: |
The implementation for this step just passed build and tests. Load
`step-implementation` (edge-case sweep phase) and `handoff-protocol`
(annotate-vs-propose rules), then:
1. Read the changed code (the coder result below names the files).
Look for edge cases the plan missed: empty inputs, error paths,
concurrency, partial failure, compat.
2. For each edge case belonging to a LATER step: check that step's
plan under {{plans_dir}}/steps/. If its Edge cases section already
covers it, done. If not, append an entry to that section via
fs_patch - touch NOTHING else in the file.
3. NEVER edit a later plan's Objective, Tasks, Acceptance criteria,
or Out of scope. Scope-affecting changes become proposed diffs in
`downstream_updates` instead.
4. Set needs_independent_review=true when the change touched 5+ files
or crosses architectural boundaries (auth, public APIs, schema,
security-sensitive paths).
Be terse. Findings, not prose.
prompt: |
## Coder result
{{coder_result}}
## Step plan
{{step_plan}}
## Staleness report from orientation
{{staleness_report}}
tools:
- fs_cat
- fs_ls
- fs_patch
- execute_command
max_iterations: 20
output_schema:
type: object
properties:
edge_case_report:
type: string
description: Edge cases discovered - both handled and punted, one per line. "none" if empty
downstream_updates:
type: string
description: Annotations made (plan file + section) and proposed diffs for scope-affecting changes. "none" if empty
needs_independent_review:
type: boolean
required: [edge_case_report, downstream_updates, needs_independent_review]
fallback: write_handoff
next: route_sweep
route_sweep:
id: route_sweep
type: script
description: Broad or boundary-crossing changes get an independent reviewer.
script: scripts/route_sweep.sh
timeout: 5
fallback: write_handoff
independent_review:
id: independent_review
type: agent
description: Independent review pass - the author's self-review cannot catch its own rationalizations.
agent: code-reviewer
prompt: |
Review the changes produced for step {{step_number}} ({{step_title}})
of a phased implementation plan in {{project_dir}}.
What the step was supposed to do:
{{plan_summary}}
Coder summary (names the modified/created files):
{{coder_result}}
Review the changed files against the step plan's acceptance criteria.
Preserve severity tags in your findings.
timeout: 1200
state_updates:
review_report: '{{output}}'
next: route_review
route_review:
id: route_review
type: script
description: Critical findings loop back to implement (bounded); otherwise proceed to handoff.
script: scripts/route_review.sh
timeout: 5
fallback: write_handoff
write_handoff:
id: write_handoff
type: llm
description: |
Write the evidence-backed handoff per handoff-protocol and append
durable facts to NOTES.md. The completion gate (check_handoff)
verifies the document afterward.
skills_enabled: true
enabled_skills:
- handoff-protocol
- ai-slop-remover
instructions: |
Load `handoff-protocol` and follow its writer schema EXACTLY: the
frontmatter (step, title, result) and all eight sections, writing
"None" rather than omitting a section.
Write the handoff to {{handoff_path}} with fs_write. Paste the
verification evidence below verbatim into the Evidence section -
commands, exit codes, decisive output lines. Deviations come from the
staleness report, gate decisions, and fix loop history. Downstream
plan updates come from the sweep results.
VERIFICATION HONESTY: evidence marked "GATE NOT RUN" means that gate
is UNVERIFIED — record it as not run; never paraphrase a skipped gate
as covered, passing, or handled elsewhere. A handoff that admits an
unverified gate is correct; one that dresses it up as verified poisons
every downstream reader.
Then append durable, step-independent facts (if any) to {{notes_path}}
- create the file if missing, never rewrite existing entries.
If "Gate feedback" below is non-empty, a previous handoff attempt
failed validation - fix exactly what it lists.
prompt: |
## Step
{{step_number}} ({{step_title}}) - plan at {{step_plan_path}}
## Plan summary
{{plan_summary}}
## Coder result
{{coder_result}}
## Staleness report / deviations
{{staleness_report}}
Major deviation summary (if any): {{deviation_summary}}
User guidance given (if any): {{user_feedback}}
Fix loop attempts used: {{fix_attempts}} of {{max_fix_attempts}}
## Edge cases discovered
{{edge_case_report}}
## Downstream plan updates
{{downstream_updates}}
## Independent review report (if any)
{{review_report}}
## Verification evidence (paste verbatim)
### Format
{{format_output}}
### Lint
{{lint_output}}
### Build
{{build_output}}
### Tests
{{tests_output}}
## Gate feedback
{{handoff_fix}}
tools:
- fs_cat
- fs_ls
- fs_write
- fs_patch
max_iterations: 15
output_schema:
type: object
properties:
step_summary:
type: string
description: 3-6 sentence summary of the step for the user's approval decision - what was done, deviations, anything needing their attention
required: [step_summary]
fallback: end_failure
next: check_handoff
check_handoff:
id: check_handoff
type: script
description: |
Deterministic completion gate - handoff exists with frontmatter and all
required sections. On success, marks the step plan status complete.
One retry back to write_handoff, then failure.
script: scripts/check_handoff.sh
timeout: 10
fallback: end_failure
gate_user_review:
id: gate_user_review
type: approval
description: The hard stop - the next step never starts without explicit approval.
question: |
## Step {{step_number}} ({{step_title}}) - ready for review
{{step_summary}}
Handoff: {{handoff_path}}
Build: {{build_ok}} | Tests: {{tests_ok}} | Fix attempts: {{fix_attempts}}/{{max_fix_attempts}}
Approve this step? (Answer with anything else to send revision
instructions straight to the implementer.)
options:
- 'approve'
- 'revise'
routes:
'approve': end_success
'revise': get_revision
on_other: revise_from_choice
state_updates:
user_feedback: '{{choice}}'
get_revision:
id: get_revision
type: input
description: Collect revision instructions, then loop back through implement -> verify -> handoff.
question: 'What should change? Your comments go to the implementer verbatim.'
validation: 'len(input) > 0'
state_updates:
fix_instructions: '{{input}}'
next: implement
revise_from_choice:
id: revise_from_choice
type: script
description: Free-form approval answers are treated as revision instructions.
script: scripts/revise_from_choice.sh
timeout: 5
fallback: get_revision
end_success:
id: end_success
type: end
output: |
STEP_COMPLETE
Step: {{step_number}} ({{step_title}})
Plan: {{step_plan_path}}
Handoff: {{handoff_path}}
Build: passed | Tests: passed | Fix attempts: {{fix_attempts}}/{{max_fix_attempts}}
{{step_summary}}
Downstream plan updates:
{{downstream_updates}}
end_blocked:
id: end_blocked
type: end
output: |
STEP_BLOCKED
Step: {{step_number}} ({{step_title}})
Reason:
{{blocking_reason}}
end_rejected:
id: end_rejected
type: end
output: |
STEP_REJECTED
Step: {{step_number}} ({{step_title}})
Rejected at: deviation gate or coder approval gate.
Deviation summary:
{{deviation_summary}}
Coder result (if it ran):
{{coder_result}}
end_failure:
id: end_failure
type: end
output: |
STEP_FAILED
Step: {{step_number}} ({{step_title}})
Fix attempts: {{fix_attempts}}/{{max_fix_attempts}}
Blocking reason (if resolution failed): {{blocking_reason}}
Coder result:
{{coder_result}}
Last build output:
{{build_output}}
Last tests output:
{{tests_output}}
assets/agents/step-runner/scripts/check_handoff.sh
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@@ -1,54 +0,0 @@
#!/usr/bin/env bash
set -uo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
handoff_path=$(echo "$state" | jq -r '.handoff_path // ""')
step_plan_path=$(echo "$state" | jq -r '.step_plan_path // ""')
handoff_attempts=$(echo "$state" | jq -r '.handoff_attempts // 0')
problems=""
if [[ ! -f "$handoff_path" ]]; then
problems="- handoff file does not exist at $handoff_path"$'\n'
else
content=$(cat "$handoff_path")
grep -qE '^result:[[:space:]]*(complete|partial|blocked)' <<< "$content" \
|| problems+="- frontmatter is missing 'result: complete|partial|blocked'"$'\n'
for section in "Summary" "Completed" "Not completed" "Deviations" "Downstream plan updates" "Edge cases discovered" "Evidence" "Notes for next step"; do
grep -qE "^##[[:space:]]+${section}" <<< "$content" \
|| problems+="- missing required section: ## ${section}"$'\n'
done
fi
if [[ -z "$problems" ]]; then
if [[ -f "$step_plan_path" ]]; then
tmp=$(mktemp)
awk 'BEGIN{n=0} /^---[[:space:]]*$/{n++; print; next} n==1 && /^status:/{print "status: complete"; next} {print}' "$step_plan_path" > "$tmp" && mv "$tmp" "$step_plan_path"
fi
jq -nc '{"handoff_fix": "", "_next": "gate_user_review"}'
exit 0
fi
if (( handoff_attempts >= 1 )); then
jq -nc \
--arg br "Handoff failed validation twice. Problems:
$problems" \
'{"blocking_reason": $br, "_next": "end_failure"}'
exit 0
fi
jq -nc \
--arg hf "The previous handoff attempt failed validation. Fix exactly these problems:
$problems" \
'{
"handoff_attempts": 1,
"handoff_fix": $hf,
"_next": "write_handoff"
}'
assets/agents/step-runner/scripts/fix_loop_gate.sh
-60
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@@ -1,60 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
fix_attempts=$(echo "$state" | jq -r '.fix_attempts // 0')
max_fix_attempts=$(echo "$state" | jq -r '.max_fix_attempts // 2')
lint_ok=$(echo "$state" | jq -r '.lint_ok | if . == null then "true" else (. | tostring) end')
build_ok=$(echo "$state" | jq -r '.build_ok | if . == null then "true" else (. | tostring) end')
tests_ok=$(echo "$state" | jq -r '.tests_ok | if . == null then "true" else (. | tostring) end')
lint_output=$(echo "$state" | jq -r '.lint_output // ""')
build_output=$(echo "$state" | jq -r '.build_output // ""')
tests_output=$(echo "$state" | jq -r '.tests_output // ""')
if (( fix_attempts >= max_fix_attempts )); then
jq -nc \
--argjson n "$fix_attempts" \
'{
"fix_attempts": $n,
"_next": "end_failure"
}'
exit 0
fi
next_attempts=$((fix_attempts + 1))
if [[ "$lint_ok" != "true" ]]; then
stage="lint"
output="$lint_output"
elif [[ "$build_ok" != "true" ]]; then
stage="build"
output="$build_output"
elif [[ "$tests_ok" != "true" ]]; then
stage="full test suite"
output="$tests_output"
else
stage="verification"
output="fix_loop_gate was reached but no failing stage was recorded. Re-run verification."
fi
fix_instructions=$(printf '## Fix loop status (step-level attempt %d of %d)\n\nThe implementation passed the coder'"'"'s internal checks but failed step-level verification at the %s stage.\n\nOutput:\n```\n%s\n```\n\nIdentify the minimal fix and apply it. Do not refactor. Regressions in untouched code caused by this change are in scope.' \
"$next_attempts" "$max_fix_attempts" "$stage" "$output")
jq -nc \
--argjson n "$next_attempts" \
--arg 'fi' "$fix_instructions" \
'{
"fix_attempts": $n,
"fix_instructions": $fi,
"lint_ok": true,
"build_ok": true,
"tests_ok": true,
"_next": "implement"
}'
assets/agents/step-runner/scripts/resolve_step.sh
-152
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@@ -1,152 +0,0 @@
#!/usr/bin/env bash
set -uo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
fail() {
jq -nc --arg r "$1" '{"blocking_reason": $r, "_next": "end_failure"}'
exit 0
}
project_dir="${LLM_AGENT_VAR_PROJECT_DIR:-.}"
project_dir=$(cd "$project_dir" 2>/dev/null && pwd) || fail "project_dir does not exist: $project_dir"
plans_dir="${LLM_AGENT_VAR_PLANS_DIR:-plans}"
[[ "$plans_dir" != /* ]] && plans_dir="$project_dir/$plans_dir"
steps_dir="$plans_dir/steps"
handoffs_dir="$plans_dir/handoffs"
notes_path="$plans_dir/NOTES.md"
[[ -d "$steps_dir" ]] || fail "No step plans directory at $steps_dir (expected <plans_dir>/steps/NN-<slug>.md)"
frontmatter() {
awk '/^---[[:space:]]*$/{n++; next} n==1{print} n>=2{exit}' "$1"
}
fm_value() {
echo "$1" | grep -E "^$2:" | head -1 | sed -E "s/^$2:[[:space:]]*//" | sed -E 's/^["'"'"']|["'"'"']$//g'
}
step="${LLM_AGENT_VAR_STEP:-next}"
if [[ "$step" == "next" ]]; then
prompt_step=$(echo "$state" | jq -r '.initial_prompt // ""' | grep -oiE 'step[[:space:]#:]*[0-9]+' | head -1 | grep -oE '[0-9]+' || true)
[[ -n "$prompt_step" ]] && step="$prompt_step"
fi
plan_file=""
if [[ "$step" == "next" ]]; then
first_pending=""
while IFS= read -r f; do
st=$(fm_value "$(frontmatter "$f")" "status")
if [[ "$st" == "in-progress" ]]; then
plan_file="$f"
break
fi
[[ -z "$first_pending" && ( "$st" == "pending" || -z "$st" ) ]] && first_pending="$f"
done < <(find "$steps_dir" -maxdepth 1 -name '*.md' | sort)
[[ -z "$plan_file" ]] && plan_file="$first_pending"
[[ -z "$plan_file" ]] && fail "No in-progress or pending step plans in $steps_dir"
else
[[ "$step" =~ ^[0-9]+$ ]] || fail "step must be a number or 'next'; got: $step"
padded=$(printf '%02d' "$((10#$step))")
plan_file=$(find "$steps_dir" -maxdepth 1 \( -name "${padded}-*.md" -o -name "${step}-*.md" \) | sort | head -1)
[[ -n "$plan_file" ]] || fail "No step plan matching step $step in $steps_dir"
fi
bn=$(basename "$plan_file" .md)
num_part="${bn%%-*}"
[[ "$num_part" =~ ^[0-9]+$ ]] || fail "Step plan filename must start with a number: $bn"
step_number=$((10#$num_part))
step_slug="${bn#*-}"
fm=$(frontmatter "$plan_file")
step_title=$(fm_value "$fm" "title")
[[ -z "$step_title" ]] && step_title="$step_slug"
deps=$(echo "$fm" | awk '/^depends_on:/{f=1; print; next} f && /^[[:space:]]*-/{print; next} f{exit}' | grep -oE '[0-9]+' || true)
unsatisfied=""
for dep in $deps; do
dep_padded=$(printf '%02d' "$((10#$dep))")
dep_handoff=$(find "$handoffs_dir" -maxdepth 1 \( -name "${dep_padded}-*.md" -o -name "${dep}-*.md" \) 2>/dev/null | sort | head -1)
if [[ -z "$dep_handoff" ]]; then
unsatisfied+="- step $dep: no handoff found (step not executed?)"$'\n'
continue
fi
dep_result=$(fm_value "$(frontmatter "$dep_handoff")" "result")
if [[ "$dep_result" != "complete" ]]; then
unsatisfied+="- step $dep: handoff result is '$dep_result' (not complete): $dep_handoff"$'\n'
fi
done
prev_handoff_path="(none)"
prev_handoff="(none - this is the first step)"
prev_file=""
prev_num=0
while IFS= read -r h; do
hn="${h##*/}"
hn="${hn%%-*}"
[[ "$hn" =~ ^[0-9]+$ ]] || continue
n=$((10#$hn))
if (( n < step_number && n >= prev_num )); then
prev_num=$n
prev_file="$h"
fi
done < <(find "$handoffs_dir" -maxdepth 1 -name '*.md' 2>/dev/null | sort)
if [[ -n "$prev_file" ]]; then
prev_handoff_path="$prev_file"
prev_handoff=$(head -c 16000 "$prev_file")
fi
notes="(none)"
[[ -f "$notes_path" ]] && notes=$(head -c 8000 "$notes_path")
step_plan=$(head -c 24000 "$plan_file")
handoff_path="$handoffs_dir/$(basename "$plan_file")"
tmp=$(mktemp)
awk 'BEGIN{n=0} /^---[[:space:]]*$/{n++; print; next} n==1 && /^status:/{print "status: in-progress"; next} {print}' "$plan_file" > "$tmp" && mv "$tmp" "$plan_file"
next_node="orient"
blocking_reason=""
if [[ -n "$unsatisfied" ]]; then
next_node="gate_blocked"
blocking_reason="Unsatisfied dependencies:"$'\n'"$unsatisfied"
fi
jq -nc \
--arg pd "$project_dir" \
--arg pl "$plans_dir" \
--argjson sn "$step_number" \
--arg ss "$step_slug" \
--arg st "$step_title" \
--arg spp "$plan_file" \
--arg sp "$step_plan" \
--arg php "$prev_handoff_path" \
--arg ph "$prev_handoff" \
--arg np "$notes_path" \
--arg no "$notes" \
--arg hp "$handoff_path" \
--arg br "$blocking_reason" \
--arg nx "$next_node" \
'{
"project_dir": $pd,
"plans_dir": $pl,
"step_number": $sn,
"step_slug": $ss,
"step_title": $st,
"step_plan_path": $spp,
"step_plan": $sp,
"prev_handoff_path": $php,
"prev_handoff": $ph,
"notes_path": $np,
"notes": $no,
"handoff_path": $hp,
"blocking_reason": $br,
"_next": $nx
}'
assets/agents/step-runner/scripts/revise_from_choice.sh
-27
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@@ -1,27 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
feedback=$(echo "$state" | jq -r '.user_feedback // ""')
if [[ -z "$feedback" ]]; then
jq -nc '{"_next": "get_revision"}'
exit 0
fi
fix_instructions=$(printf '## Revision requested by the user at the step approval gate\n\nAddress these comments with minimal edits, then the step re-verifies and the handoff is rewritten:\n\n%s' \
"$feedback")
jq -nc \
--arg 'fi' "$fix_instructions" \
'{
"fix_instructions": $fi,
"_next": "implement"
}'
assets/agents/step-runner/scripts/route_coder_result.sh
-27
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@@ -1,27 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
coder_result=$(echo "$state" | jq -r '.coder_result // ""')
case "$coder_result" in
*CODER_COMPLETE*)
jq -nc '{"_next": "verify_format_lint"}'
;;
*CODER_REJECTED*)
jq -nc '{"_next": "end_rejected"}'
;;
*CODER_FAILED*)
jq -nc '{"blocking_reason": "coder fix-loop exhausted; see coder result", "_next": "end_failure"}'
;;
*)
jq -nc '{"blocking_reason": "coder returned no recognizable sentinel (expected CODER_COMPLETE / CODER_REJECTED / CODER_FAILED)", "_next": "end_failure"}'
;;
esac
assets/agents/step-runner/scripts/route_review.sh
-38
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@@ -1,38 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
review_report=$(echo "$state" | jq -r '.review_report // ""')
review_attempts=$(echo "$state" | jq -r '.review_attempts // 0')
max_review_attempts=$(echo "$state" | jq -r '.max_review_attempts // 1')
if ! grep -qF "🔴" <<< "$review_report"; then
jq -nc '{"_next": "write_handoff"}'
exit 0
fi
if (( review_attempts >= max_review_attempts )); then
jq -nc '{"_next": "write_handoff"}'
exit 0
fi
next_review=$((review_attempts + 1))
fix_instructions=$(printf '## Independent review findings (attempt %d of %d)\n\nAn independent reviewer flagged CRITICAL (🔴) findings. Address ONLY the 🔴 findings with minimal edits. Do not refactor unrelated code.\n\n%s' \
"$next_review" "$max_review_attempts" "$review_report")
jq -nc \
--argjson n "$next_review" \
--arg 'fi' "$fix_instructions" \
'{
"review_attempts": $n,
"fix_instructions": $fi,
"needs_independent_review": false,
"_next": "implement"
}'
assets/agents/step-runner/scripts/route_staleness.sh
-23
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@@ -1,23 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
has_major=$(echo "$state" | jq -r '.has_major_deviation // false')
if [[ "${STEP_AUTOAPPROVE:-0}" == "1" ]]; then
jq -nc '{"_next": "implement"}'
exit 0
fi
if [[ "$has_major" == "true" ]]; then
jq -nc '{"_next": "gate_deviation"}'
else
jq -nc '{"_next": "implement"}'
fi
assets/agents/step-runner/scripts/route_sweep.sh
-23
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@@ -1,23 +0,0 @@
#!/usr/bin/env bash
set -euo pipefail
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
needs_review=$(echo "$state" | jq -r '.needs_independent_review // false')
if [[ "${STEP_SKIP_REVIEW:-0}" == "1" ]]; then
jq -nc '{"_next": "write_handoff"}'
exit 0
fi
if [[ "$needs_review" == "true" ]]; then
jq -nc '{"_next": "independent_review"}'
else
jq -nc '{"_next": "write_handoff"}'
fi
assets/agents/step-runner/scripts/verify_build.sh
-58
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@@ -1,58 +0,0 @@
#!/usr/bin/env bash
set -uo pipefail
# shellcheck disable=SC1091
source "$(dirname "$0")/../../.shared/utils.sh"
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
project_dir=$(echo "$state" | jq -r '.project_dir // "."')
project_dir=$(resolve_gate_dir "$project_dir")
if [[ -n "${BUILD_CMD:-}" ]]; then
cmd="$BUILD_CMD"
else
project_info=$(detect_project "$project_dir")
cmd=$(echo "$project_info" | jq -r '.check // .build // ""')
fi
if [[ -z "$cmd" || "$cmd" == "null" ]]; then
jq -nc '{
"build_ok": true,
"build_output": "(GATE NOT RUN: no build/check command configured or detected. This is NOT evidence that the build passed — set BUILD_CMD, and never report the build as verified.)",
"_next": "verify_tests"
}'
exit 0
fi
exit_code=0
output=$(cd "$project_dir" && eval "$cmd" 2>&1) || exit_code=$?
if (( exit_code == 0 )); then
jq -nc \
--arg out "Ran: $cmd
$output" \
'{
"build_ok": true,
"build_output": $out,
"_next": "verify_tests"
}'
else
jq -nc \
--arg out "Ran: $cmd
Exit code: $exit_code
$output" \
'{
"build_ok": false,
"build_output": $out,
"_next": "fix_loop_gate"
}'
fi
assets/agents/step-runner/scripts/verify_format_lint.sh
-84
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@@ -1,84 +0,0 @@
#!/usr/bin/env bash
set -uo pipefail
# shellcheck disable=SC1091
source "$(dirname "$0")/../../.shared/utils.sh"
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
project_dir=$(echo "$state" | jq -r '.project_dir // "."')
project_dir=$(resolve_gate_dir "$project_dir")
project_info=$(detect_project "$project_dir")
project_type=$(echo "$project_info" | jq -r '.type // "unknown"')
format_cmd="${FORMAT_CMD:-}"
if [[ -z "$format_cmd" ]]; then
format_cmd=$(echo "$project_info" | jq -r '.fmt // ""')
fi
if [[ "$format_cmd" == "null" ]]; then format_cmd=""; fi
if [[ -z "$format_cmd" ]]; then
format_output="(GATE NOT RUN: no format command configured or detected for project type '$project_type'. This is NOT evidence that formatting is clean. Set FORMAT_CMD to enable.)"
else
fmt_rc=0
fmt_out=$(cd "$project_dir" && eval "$format_cmd" 2>&1) || fmt_rc=$?
format_output="Ran: $format_cmd
Exit code: $fmt_rc
$fmt_out"
fi
lint_cmd="${LINT_CMD:-}"
if [[ -z "$lint_cmd" ]]; then
lint_cmd=$(echo "$project_info" | jq -r '.lint // ""')
fi
# The skip message must read as a WARNING, never a reassurance: the previous
# wording ("linting is covered by the build/check command") was quoted
# verbatim by workers as false evidence that linting passed
if [[ -z "$lint_cmd" || "$lint_cmd" == "null" ]]; then
jq -nc \
--arg fo "$format_output" \
'{
"format_output": $fo,
"lint_ok": true,
"lint_output": "(GATE NOT RUN: no lint command configured or detected. This is NOT evidence that linting passed — set LINT_CMD or add a Taskfile lint target, and never report linting as covered.)",
"_next": "verify_build"
}'
exit 0
fi
lint_rc=0
lint_out=$(cd "$project_dir" && eval "$lint_cmd" 2>&1) || lint_rc=$?
if (( lint_rc == 0 )); then
jq -nc \
--arg fo "$format_output" \
--arg lo "Ran: $lint_cmd
$lint_out" \
'{
"format_output": $fo,
"lint_ok": true,
"lint_output": $lo,
"_next": "verify_build"
}'
else
jq -nc \
--arg fo "$format_output" \
--arg lo "Ran: $lint_cmd
Exit code: $lint_rc
$lint_out" \
'{
"format_output": $fo,
"lint_ok": false,
"lint_output": $lo,
"_next": "fix_loop_gate"
}'
fi
assets/agents/step-runner/scripts/verify_tests.sh
-58
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@@ -1,58 +0,0 @@
#!/usr/bin/env bash
set -uo pipefail
# shellcheck disable=SC1091
source "$(dirname "$0")/../../.shared/utils.sh"
if [[ -n "${GRAPH_STATE_FILE:-}" ]]; then
state=$(cat "$GRAPH_STATE_FILE")
elif [[ -n "${GRAPH_STATE:-}" ]]; then
state="$GRAPH_STATE"
else
state='{}'
fi
project_dir=$(echo "$state" | jq -r '.project_dir // "."')
project_dir=$(resolve_gate_dir "$project_dir")
if [[ -n "${TEST_CMD:-}" ]]; then
cmd="$TEST_CMD"
else
project_info=$(detect_project "$project_dir")
cmd=$(echo "$project_info" | jq -r '.test // ""')
fi
if [[ -z "$cmd" || "$cmd" == "null" ]]; then
jq -nc '{
"tests_ok": true,
"tests_output": "(GATE NOT RUN: no test command configured or detected. This is NOT evidence that tests passed — set TEST_CMD, and never report the suite as green.)",
"_next": "edge_case_sweep"
}'
exit 0
fi
exit_code=0
output=$(cd "$project_dir" && eval "$cmd" 2>&1) || exit_code=$?
if (( exit_code == 0 )); then
jq -nc \
--arg out "Ran: $cmd
$output" \
'{
"tests_ok": true,
"tests_output": $out,
"_next": "edge_case_sweep"
}'
else
jq -nc \
--arg out "Ran: $cmd
Exit code: $exit_code
$output" \
'{
"tests_ok": false,
"tests_output": $out,
"_next": "fix_loop_gate"
}'
fi
assets/arena.html
+1106
View File
File diff suppressed because it is too large Load Diff
assets/functions/mcp.json
+14 -8
View File
@@ -1,13 +1,24 @@
{
"mcpServers": {
"github": {
"type": "http",
"url": "https://api.githubcopilot.com/mcp"
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"GITHUB_PERSONAL_ACCESS_TOKEN",
"ghcr.io/github/github-mcp-server"
],
"env": {
"GITHUB_PERSONAL_ACCESS_TOKEN": "YOUR_GITHUB_TOKEN"
}
},
"atlassian": {
"type": "stdio",
"command": "npx",
"args": ["-y", "mcp-remote@latest", "https://mcp.atlassian.com/v1/mcp"]
"args": ["-y", "mcp-remote@0.1.13", "https://mcp.atlassian.com/v1/mcp"]
},
"docker": {
"type": "stdio",
@@ -18,11 +29,6 @@
"type": "stdio",
"command": "uvx",
"args": ["duckduckgo-mcp-server"]
},
"iwe": {
"type": "stdio",
"command": "iwec",
"args": ["--project", "."]
}
}
}
assets/functions/sbx-mixin.yaml
-44
View File
@@ -1,44 +0,0 @@
schemaVersion: '2'
kind: mixin
name: built-in-tools
description: >
Installs binaries and allows network domains required by Coyote's built-in
global tools and the default MCP server set. Auto-applied by Coyote's sbx
mixin discovery when running `coyote --sandbox`.
permissions:
network:
allow:
# fetch_url_via_jina + jina reader fallback
- 'r.jina.ai'
# get_current_weather (.sh, .py, .ts)
- 'wttr.in'
# search_arxiv (the .sh tool still uses http://, so :80 is required until fixed)
- 'export.arxiv.org'
- 'export.arxiv.org:80'
# search_arxiv + search_wikipedia may follow DOI redirects
- 'doi.org'
# search_wikipedia
- 'en.wikipedia.org'
# search_wolframalpha
- 'api.wolframalpha.com'
# web_search_perplexity
- 'api.perplexity.ai'
# web_search_tavily
- 'api.tavily.com'
# send_twilio
- 'api.twilio.com'
# MCP: github (built-in mcp.json: api.githubcopilot.com)
- 'api.githubcopilot.com'
# MCP: atlassian (built-in mcp.json: mcp-remote -> mcp.atlassian.com)
- 'mcp.atlassian.com'
# MCP: ddg-search (built-in mcp.json: uvx duckduckgo-mcp-server)
- 'duckduckgo.com'
- 'html.duckduckgo.com'
- 'lite.duckduckgo.com'
# MCP: npx-based servers (mcp-remote) pull from npm
- 'registry.npmjs.org'
# MCP: docker server may pull images from common registries
- 'ghcr.io'
- 'registry-1.docker.io'
- 'auth.docker.io'
assets/functions/scripts/run-agent.py
+2 -3
View File
@@ -32,7 +32,7 @@ def main():
agent_data = parse_raw_data(raw_data)
root_dir = "{config_dir}"
setup_env(root_dir, agent_func, raw_data)
setup_env(root_dir, agent_func)
agent_tools_path = os.path.join(root_dir, "agents/{agent_name}/tools.py")
run(agent_tools_path, agent_func, agent_data)
@@ -65,14 +65,13 @@ def parse_argv():
return agent_func, agent_data
def setup_env(root_dir, agent_func, raw_data):
def setup_env(root_dir, agent_func):
load_env(os.path.join(root_dir, ".env"))
os.environ["LLM_ROOT_DIR"] = root_dir
os.environ["LLM_AGENT_NAME"] = "{agent_name}"
os.environ["LLM_AGENT_FUNC"] = agent_func
os.environ["LLM_AGENT_ROOT_DIR"] = os.path.join(root_dir, "agents", "{agent_name}")
os.environ["LLM_AGENT_CACHE_DIR"] = os.path.join(root_dir, "cache", "{agent_name}")
os.environ["LLM_AGENT_RAW_JSON"] = raw_data
def load_env(file_path):
assets/functions/scripts/run-agent.sh
+2 -3
View File
@@ -32,7 +32,6 @@ setup_env() {
export LLM_AGENT_ROOT_DIR="$LLM_ROOT_DIR/agents/{agent_name}"
export LLM_AGENT_CACHE_DIR="$LLM_ROOT_DIR/cache/{agent_name}"
export LLM_PROMPT_UTILS_FILE="{prompt_utils_file}"
export LLM_AGENT_RAW_JSON="$agent_data"
}
load_env() {
@@ -74,11 +73,11 @@ def to_args:
to_entries | .[] |
(.key | split("_") | join("-")) as $key |
if .value | type == "array" then
.value | .[] | "--\($key)=\(. | escape_shell_word)"
.value | .[] | "--\($key) \(. | escape_shell_word)"
elif .value | type == "boolean" then
if .value then "--\($key)" else "" end
else
"--\($key)=\(.value | escape_shell_word)"
"--\($key) \(.value | escape_shell_word)"
end;
[ to_args ] | join(" ")
EOF
assets/functions/scripts/run-agent.ts
+2 -3
View File
@@ -11,7 +11,7 @@ async function main(): Promise<void> {
const agentData = parseRawData(rawData);
const configDir = "{config_dir}";
setupEnv(configDir, agentFunc, rawData);
setupEnv(configDir, agentFunc);
const agentToolsPath = join(configDir, "agents", "{agent_name}", "tools.ts");
await run(agentToolsPath, agentFunc, agentData);
@@ -48,14 +48,13 @@ function parseArgv(): { agentFunc: string; rawData: string } {
return { agentFunc, rawData: agentData };
}
function setupEnv(configDir: string, agentFunc: string, rawData: string): void {
function setupEnv(configDir: string, agentFunc: string): void {
loadEnv(join(configDir, ".env"));
process.env["LLM_ROOT_DIR"] = configDir;
process.env["LLM_AGENT_NAME"] = "{agent_name}";
process.env["LLM_AGENT_FUNC"] = agentFunc;
process.env["LLM_AGENT_ROOT_DIR"] = join(configDir, "agents", "{agent_name}");
process.env["LLM_AGENT_CACHE_DIR"] = join(configDir, "cache", "{agent_name}");
process.env["LLM_AGENT_RAW_JSON"] = rawData;
}
function loadEnv(filePath: string): void {
assets/functions/scripts/run-tool.py
+2 -3
View File
@@ -32,7 +32,7 @@ def main():
tool_data = parse_raw_data(raw_data)
root_dir = "{root_dir}"
setup_env(root_dir, raw_data)
setup_env(root_dir)
tool_path = "{tool_path}.py"
run(tool_path, "run", tool_data)
@@ -65,12 +65,11 @@ def parse_argv():
return tool_data
def setup_env(root_dir, raw_data):
def setup_env(root_dir):
load_env(os.path.join(root_dir, ".env"))
os.environ["LLM_ROOT_DIR"] = root_dir
os.environ["LLM_TOOL_NAME"] = "{function_name}"
os.environ["LLM_TOOL_CACHE_DIR"] = os.path.join(root_dir, "cache", "{function_name}")
os.environ["LLM_TOOL_RAW_JSON"] = raw_data
def load_env(file_path):
assets/functions/scripts/run-tool.sh
+2 -3
View File
@@ -29,7 +29,6 @@ setup_env() {
export LLM_TOOL_NAME="{function_name}"
export LLM_TOOL_CACHE_DIR="$LLM_ROOT_DIR/cache/{function_name}"
export LLM_PROMPT_UTILS_FILE="{prompt_utils_file}"
export LLM_TOOL_RAW_JSON="$tool_data"
}
load_env() {
@@ -71,11 +70,11 @@ def to_args:
to_entries | .[] |
(.key | split("_") | join("-")) as $key |
if .value | type == "array" then
.value | .[] | "--\($key)=\(. | escape_shell_word)"
.value | .[] | "--\($key) \(. | escape_shell_word)"
elif .value | type == "boolean" then
if .value then "--\($key)" else "" end
else
"--\($key)=\(.value | escape_shell_word)"
"--\($key) \(.value | escape_shell_word)"
end;
[ to_args ] | join(" ")
EOF
assets/functions/scripts/run-tool.ts
+2 -3
View File
@@ -11,7 +11,7 @@ async function main(): Promise<void> {
const toolData = parseRawData(rawData);
const rootDir = "{root_dir}";
setupEnv(rootDir, rawData);
setupEnv(rootDir);
const toolPath = "{tool_path}.ts";
await run(toolPath, "run", toolData);
@@ -45,12 +45,11 @@ function parseArgv(): string {
return toolData;
}
function setupEnv(rootDir: string, rawData: string): void {
function setupEnv(rootDir: string): void {
loadEnv(join(rootDir, ".env"));
process.env["LLM_ROOT_DIR"] = rootDir;
process.env["LLM_TOOL_NAME"] = "{function_name}";
process.env["LLM_TOOL_CACHE_DIR"] = join(rootDir, "cache", "{function_name}");
process.env["LLM_TOOL_RAW_JSON"] = rawData;
}
function loadEnv(filePath: string): void {
assets/functions/tools/ast_grep.sh
-81
View File
@@ -1,81 +0,0 @@
#!/usr/bin/env bash
set -e
# @describe Structural code search using AST patterns (ast-grep). Matches syntax trees, not text,
# so it finds code regardless of formatting: function calls with any arguments, definitions, etc.
# Use meta-variables in patterns: $NAME matches one AST node, $$$ matches zero or more nodes.
# Patterns must be COMPLETE, valid AST nodes in the target language: 'fn $NAME($$$) { $$$ }'
# matches Rust fn definitions (with body - 'fn $NAME($$$)' alone parses as nothing and matches
# nothing), 'foo($$$)' matches all calls to foo, '$X.unwrap()' matches all unwrap calls.
# Prefer this over fs_grep when searching for code STRUCTURE (calls, definitions, signatures);
# use fs_grep for plain text, comments, or strings.
# @option --pattern! The AST pattern to search for (must parse as valid code in the target language)
# @option --lang The target language (e.g. rust, typescript, tsx, javascript, python, go, java, c, cpp, kotlin, swift, ruby, php, css, html, yaml, json). Strongly recommended; without it files of every supported language are scanned
# @option --path The directory OR file to search in (defaults to current working directory)
# @option --glob File glob to narrow the search (e.g. "src/**/*.rs", "!**/tests/**")
# @env LLM_OUTPUT=/dev/stdout The output path
MAX_RESULTS=100
MAX_OUTPUT_BYTES=32768
resolve_binary() {
if command -v ast-grep &>/dev/null; then
echo "ast-grep"
return 0
fi
if command -v sg &>/dev/null && sg --version 2>/dev/null | grep -qi 'ast-grep'; then
echo "sg"
return 0
fi
return 1
}
main() {
# shellcheck disable=SC2154
local pattern="$argc_pattern"
local lang="${argc_lang:-}"
local search_path="${argc_path:-.}"
local glob="${argc_glob:-}"
local bin
if ! bin=$(resolve_binary); then
printf 'ast-grep is not installed. Fall back to fs_grep for this search.\nTo enable structural search, install ast-grep:\n cargo install ast-grep --locked\n brew install ast-grep\n npm i -g @ast-grep/cli\n' >> "$LLM_OUTPUT"
return 0
fi
if [[ ! -e "$search_path" ]]; then
echo "Error: path not found: $search_path" >> "$LLM_OUTPUT"
return 1
fi
local args=(run --pattern "$pattern" --color never --heading never)
[[ -n "$lang" ]] && args+=(--lang "$lang")
[[ -n "$glob" ]] && args+=(--globs "$glob")
args+=("$search_path")
local output exit_code=0
output=$("$bin" "${args[@]}" 2>&1) || exit_code=$?
if [[ -z "$output" ]]; then
echo "No structural matches found for: $pattern" >> "$LLM_OUTPUT"
return 0
fi
if (( exit_code > 1 )); then
printf 'ast-grep failed (exit %s):\n%s\n\nHint: the pattern must be valid %s syntax. Meta-variables: $NAME (one node), $$$ (zero or more).\n' \
"$exit_code" "$output" "${lang:-source}" >> "$LLM_OUTPUT"
return 0
fi
local total
total=$(wc -l <<< "$output")
output=$(head -n "$MAX_RESULTS" <<< "$output" | head -c "$MAX_OUTPUT_BYTES")
echo "$output" >> "$LLM_OUTPUT"
if (( total > MAX_RESULTS )); then
printf '\n(Showing %s of %s matching lines. Narrow with --glob, --lang, or a more specific pattern.)\n' \
"$MAX_RESULTS" "$total" >> "$LLM_OUTPUT"
fi
}
assets/functions/tools/execute_command.sh
+2 -10
View File
@@ -1,7 +1,7 @@
#!/usr/bin/env bash
set -e
# @describe Execute the shell command. DO NOT use this to write files — use fs_write (new files) or fs_patch (edits) instead. Shell-based file writes (cat >, echo >, printf >, tee, heredocs, python -c "open(...)") break on multi-line content, special characters, quoted strings, and nested language blocks.
# @describe Execute the shell command.
# @option --command! The command to execute.
# @env LLM_OUTPUT=/dev/stdout The output path
@@ -10,15 +10,7 @@ set -e
source "$LLM_PROMPT_UTILS_FILE"
main() {
# shellcheck disable=SC2154
argc_command="$(jq -r '.command' <<< "$LLM_TOOL_RAW_JSON")"
guard_operation
local script
script="$(mktemp)"
# shellcheck disable=SC2064
trap "rm -f '$script'" EXIT
# shellcheck disable=SC2154
printf '%s\n' "$argc_command" > "$script"
bash -e -o pipefail "$script" >> "$LLM_OUTPUT"
eval "$argc_command" >> "$LLM_OUTPUT"
}
assets/functions/tools/execute_sql_code.sh
-2
View File
@@ -14,8 +14,6 @@ source "$LLM_PROMPT_UTILS_FILE"
# shellcheck disable=SC2154
main() {
argc_code="$(jq -r '.code' <<< "$LLM_TOOL_RAW_JSON")"
if ! grep -qi '^select' <<<"$argc_code"; then
guard_operation ""
fi
assets/functions/tools/fs_cat.sh
+1 -9
View File
@@ -10,13 +10,5 @@ set -e
main() {
# shellcheck disable=SC2154
local path="$argc_path"
# An empty result is shown to the model as the opaque literal "DONE"; emit a note instead.
if [[ -f "$path" && ! -s "$path" ]]; then
echo "(empty file: $path)" >> "$LLM_OUTPUT"
return 0
fi
cat "$path" >> "$LLM_OUTPUT" 2>&1 || echo "No such file or path: $path" >> "$LLM_OUTPUT"
cat "$argc_path" >> "$LLM_OUTPUT" 2>&1 || echo "No such file or path: $argc_path" >> "$LLM_OUTPUT"
}
assets/functions/tools/fs_glob.sh
+3 -14
View File
@@ -17,8 +17,8 @@ main() {
local search_path="${argc_path:-.}"
if [[ ! -d "$search_path" ]]; then
echo "Error: directory not found: $search_path" >&2
exit 1
echo "Error: directory not found: $search_path" >> "$LLM_OUTPUT"
return 1
fi
local results
@@ -33,18 +33,7 @@ main() {
--exclude '.build' \
2>/dev/null | head -n "$MAX_RESULTS") || true
else
local name_pattern dir_prefix effective_search
name_pattern="${glob_pattern##*/}"
[[ -z "$name_pattern" || "$name_pattern" == "**" ]] && name_pattern="*"
if [[ "$glob_pattern" == */* ]]; then
dir_prefix="${glob_pattern%%\**}"
dir_prefix="${dir_prefix%/}"
effective_search="${search_path}${dir_prefix:+/$dir_prefix}"
else
effective_search="$search_path"
fi
[[ -d "$effective_search" ]] || effective_search="$search_path"
results=$(find "$effective_search" -type f -name "$name_pattern" \
results=$(find "$search_path" -type f -name "$glob_pattern" \
-not -path '*/.git/*' \
-not -path '*/node_modules/*' \
-not -path '*/target/*' \
assets/functions/tools/fs_grep.sh
+7 -14
View File
@@ -3,11 +3,10 @@ set -e
# @describe Search file contents using regular expressions. Returns matching file paths and lines.
# Use this to find relevant code before reading files. Much faster than reading files to search.
# --path accepts either a directory (recursive search with exclude rules applied) or a single file.
# @option --pattern! The regex pattern to search for in file contents
# @option --path The directory OR file to search in (defaults to current working directory)
# @option --include File pattern to filter by (e.g. "*.rs", "*.{ts,tsx}", "*.py"). Ignored when --path is a single file.
# @option --path The directory to search in (defaults to current working directory)
# @option --include File pattern to filter by (e.g. "*.rs", "*.{ts,tsx}", "*.py")
# @env LLM_OUTPUT=/dev/stdout The output path
@@ -20,17 +19,13 @@ main() {
local search_path="${argc_path:-.}"
local include_filter="${argc_include:-}"
if [[ ! -e "$search_path" ]]; then
echo "Error: path not found: $search_path" >&2
exit 1
if [[ ! -d "$search_path" ]]; then
echo "Error: directory not found: $search_path" >> "$LLM_OUTPUT"
return 1
fi
local grep_args=(-nH --color=never)
local grep_args=(-rn --color=never)
if [[ -d "$search_path" ]]; then
# Use -r (not -R) so symlinks to directories are NOT followed - this avoids
# infinite loops on pathological symlink cycles (e.g. `ln -s . loop`).
grep_args+=(-r)
grep_args+=(
--exclude-dir='.git'
--exclude-dir='node_modules'
@@ -47,12 +42,10 @@ main() {
--exclude='*.lock'
--exclude='package-lock.json'
)
if [[ -n "$include_filter" ]]; then
grep_args+=("--include=$include_filter")
fi
fi
# If --path is a single file, --include and the exclude rules are ignored
# (they only matter when recursing into a directory tree).
local results
results=$(grep "${grep_args[@]}" -E "$search_pattern" "$search_path" 2>/dev/null | head -n "$MAX_RESULTS") || true
assets/functions/tools/fs_ls.sh
+1 -14
View File
@@ -9,18 +9,5 @@ set -e
main() {
# shellcheck disable=SC2154
local path="$argc_path"
local output
if ! output=$(ls -1 "$path" 2>&1); then
echo "$output" >> "$LLM_OUTPUT"
return 0
fi
# An empty result is shown to the model as the opaque literal "DONE"; emit a note instead.
if [[ -z "$output" ]]; then
echo "(empty directory: $path)" >> "$LLM_OUTPUT"
else
echo "$output" >> "$LLM_OUTPUT"
fi
ls -1 "$argc_path" >> "$LLM_OUTPUT" 2>&1 || echo "No such path: $argc_path" >> "$LLM_OUTPUT"
}
assets/functions/tools/fs_patch.sh
+3 -25
View File
@@ -1,30 +1,11 @@
#!/usr/bin/env bash
set -e
# @describe Apply a unified-diff patch to a file at the specified path. Use this for editing an existing file. It's the
# PREFERRED way to modify a file. Prefer this over fs_write whenever the file already exists: it sends less data,
# preserves unchanged content automatically, and is less prone to accidental data loss from full rewrites.
# Use fs_write only when you are creating a new file or doing a complete rewrite where most of the content changes.
#
# CRITICAL — the patch is matched byte-for-byte. There is no fuzzy matching, no whitespace tolerance, and no context shift:
# - Context lines (prefixed with a single space) and removed lines (prefixed with '-') must equal the file content exactly.
# If unsure, fs_cat the file first and copy the bytes verbatim into your patch.
# - JSON-escape the contents string ONCE. Each literal backslash in the file becomes \\ in the JSON contents string. So a
# shell line containing s|\\"|"|g must appear in JSON as s|\\\\\"|\"|g — NOT s|\\\\\\\"|\\\"|g. Over-escaping backslashes
# is the most common cause of "unable to apply patch" failures, especially in files with sed/jq/regex pipelines or
# embedded Python with quoted strings.
# - Hunks are applied in order; the first hunk that fails aborts the whole patch — later hunks are NOT attempted.
# - If you've edited this file in earlier tool calls, fs_cat it again before composing the patch. A stale view of the file
# produces context lines that no longer match.
# - On failure the error message names the failing hunk and shows the expected-vs-actual line. Fix that specific line and
# retry — do not blindly resend a near-identical patch.
#
# For files with heavy escaping (sed/jq/regex pipelines, shell with embedded heredocs, deeply quoted strings), prefer
# fs_write over chained fs_patch hunks to replace the entire file with the full new contents (i.e. original content +
# your changes).
# @describe Apply a patch to a file at the specified path.
# This can be used to edit a file without having to rewrite the whole file.
# @option --path! The path of the file to apply the patch to
# @option --content! The patch to apply to the file
# @option --contents! The patch to apply to the file
# @env LLM_OUTPUT=/dev/stdout The output path
@@ -33,9 +14,6 @@ source "$LLM_PROMPT_UTILS_FILE"
# shellcheck disable=SC2154
main() {
argc_contents="$(jq -r '.content' <<< "$LLM_TOOL_RAW_JSON")"
argc_path="$(jq -r '.path' <<< "$LLM_TOOL_RAW_JSON")"
if [[ ! -f "$argc_path" ]]; then
error "Unable to find the specified file: $argc_path"
exit 1
assets/functions/tools/fs_read.sh
+8 -22
View File
@@ -1,15 +1,13 @@
#!/usr/bin/env bash
set -e
# @describe Read a TRUNCATED view of a file with line numbers, offset, and limit. For directories, lists entries.
# IMPORTANT: This tool truncates output — lines over 2000 chars are cut off, and output is capped at 2000 lines by default.
# If you need the FULL, untruncated contents of a file, use fs_cat instead.
# Use this tool when you want line numbers, want to read a specific section via --offset/--limit, or are scanning a large file.
# @describe Read a file with line numbers, offset, and limit. For directories, lists entries.
# Prefer this over fs_cat for controlled reading. Use offset/limit to read specific sections.
# Use the grep tool to find specific content before reading, then read with offset to target the relevant section.
# @option --path! The absolute path to the file or directory to read
# @option --offset <INT> The line number to start reading from (1-indexed, default: 1)
# @option --limit <INT> The maximum number of lines to read (default: 2000)
# @option --offset The line number to start reading from (1-indexed, default: 1)
# @option --limit The maximum number of lines to read (default: 2000)
# @env LLM_OUTPUT=/dev/stdout The output path
@@ -23,8 +21,8 @@ main() {
local limit="${argc_limit:-2000}"
if [[ ! -e "$target" ]]; then
echo "Error: path not found: $target" >&2
exit 1
echo "Error: path not found: $target" >> "$LLM_OUTPUT"
return 1
fi
if [[ -d "$target" ]]; then
@@ -33,20 +31,9 @@ main() {
fi
local total_lines file_bytes
# awk counts a final line that lacks a trailing newline; wc -l would undercount it by one.
total_lines=$(awk 'END { print NR }' "$target" 2>/dev/null || echo 0)
total_lines=$(wc -l < "$target" 2>/dev/null || echo 0)
file_bytes=$(wc -c < "$target" 2>/dev/null || echo 0)
if [[ "$total_lines" -eq 0 ]]; then
echo "(file is empty: $target)" >> "$LLM_OUTPUT"
return 0
fi
if [[ "$offset" -gt "$total_lines" ]]; then
echo "(offset $offset is past the end of the file, which has $total_lines lines)" >> "$LLM_OUTPUT"
return 0
fi
if [[ "$file_bytes" -gt "$MAX_BYTES" ]] && [[ "$offset" -eq 1 ]] && [[ "$limit" -ge 2000 ]]; then
{
echo "Warning: Large file (${file_bytes} bytes, ${total_lines} lines). Showing first ${limit} lines."
@@ -59,8 +46,7 @@ main() {
sed -n "${offset},${end_line}p" "$target" 2>/dev/null | {
local line_num=$offset
# `|| [[ -n "$line" ]]` keeps the final line when the file has no trailing newline.
while IFS= read -r line || [[ -n "$line" ]]; do
while IFS= read -r line; do
if [[ ${#line} -gt $MAX_LINE_LENGTH ]]; then
line="${line:0:$MAX_LINE_LENGTH}... (truncated)"
fi
assets/functions/tools/fs_write.sh
+2 -7
View File
@@ -1,12 +1,10 @@
#!/usr/bin/env bash
set -e
# @describe Write the FULL file contents to a file at the specified path. Use this for NEW files or COMPLETE rewrites
# only. For editing an existing file, prefer fs_patch. It's a surgical edit that preserves unchanged content, requires
# sending less data, and is less prone to accidental data loss.
# @describe Write the full file contents to a file at the specified path.
# @option --path! The path of the file to write to
# @option --content! The full contents to write to the file
# @option --contents! The full contents to write to the file
# @env LLM_OUTPUT=/dev/stdout The output path
@@ -15,9 +13,6 @@ source "$LLM_PROMPT_UTILS_FILE"
# shellcheck disable=SC2154
main() {
argc_contents="$(jq -r '.content' <<< "$LLM_TOOL_RAW_JSON")"
argc_path="$(jq -r '.path' <<< "$LLM_TOOL_RAW_JSON")"
if [[ -f "$argc_path" ]]; then
printf "%s" "$argc_contents" | git diff --no-index "$argc_path" - || true
guard_operation "Apply changes?"
assets/functions/tools/query_jira_issues.sh
Executable
+11
View File
@@ -0,0 +1,11 @@
#!/usr/bin/env bash
set -e
# @meta require-tools jira
# @describe Query for jira issues using a Jira Query Language (JQL) query
# @option --jql-query! The Jira Query Language query to execute
# @env LLM_OUTPUT=/dev/stdout The output path
main() {
jira issue ls -q "$argc_jql_query" --plain >> "$LLM_OUTPUT"
}
assets/functions/tools/send_mail.sh
-4
View File
@@ -14,10 +14,6 @@ set -e
# shellcheck disable=SC2154
main() {
argc_recipient="$(jq -r '.recipient' <<< "$LLM_TOOL_RAW_JSON")"
argc_subject="$(jq -r '.subject' <<< "$LLM_TOOL_RAW_JSON")"
argc_body="$(jq -r '.body' <<< "$LLM_TOOL_RAW_JSON")"
sender_name="${EMAIL_SENDER_NAME:-$(echo "$EMAIL_SMTP_USER" | awk -F'@' '{print $1}')}"
printf "%s\n" "From: $sender_name <$EMAIL_SMTP_USER>
To: $argc_recipient
assets/functions/tools/web_search_coyote.sh → assets/functions/tools/web_search_loki.sh
+6 -6
View File
@@ -6,11 +6,11 @@ set -e
# @option --query! The search query.
# @meta require-tools coyote
# @meta require-tools loki
# @env WEB_SEARCH_MODEL=gemini:gemini-2.5-flash The model for web-searching.
#
# supported coyote models:
# supported loki models:
# - gemini:gemini-2.0-*
# - vertexai:gemini-*
# - perplexity:*
@@ -22,15 +22,15 @@ main() {
client="${WEB_SEARCH_MODEL%%:*}"
if [[ "$client" == "gemini" ]]; then
export COYOTE_PATCH_GEMINI_CHAT_COMPLETIONS='{".*":{"body":{"tools":[{"google_search":{}}]}}}'
export LOKI_PATCH_GEMINI_CHAT_COMPLETIONS='{".*":{"body":{"tools":[{"google_search":{}}]}}}'
elif [[ "$client" == "vertexai" ]]; then
export COYOTE_PATCH_VERTEXAI_CHAT_COMPLETIONS='{
export LOKI_PATCH_VERTEXAI_CHAT_COMPLETIONS='{
"gemini-1.5-.*":{"body":{"tools":[{"googleSearchRetrieval":{}}]}},
"gemini-2.0-.*":{"body":{"tools":[{"google_search":{}}]}}
}'
elif [[ "$client" == "ernie" ]]; then
export COYOTE_PATCH_ERNIE_CHAT_COMPLETIONS='{".*":{"body":{"web_search":{"enable":true}}}}'
export LOKI_PATCH_ERNIE_CHAT_COMPLETIONS='{".*":{"body":{"web_search":{"enable":true}}}}'
fi
coyote -m "$WEB_SEARCH_MODEL" "$argc_query" >> "$LLM_OUTPUT"
loki -m "$WEB_SEARCH_MODEL" "$argc_query" >> "$LLM_OUTPUT"
}
assets/functions/utils/prompt-utils.sh
+6 -42
View File
@@ -506,16 +506,16 @@ open_link() {
}
guard_operation() {
if [[ -t 1 ]]; then
if [[ -z "$AUTO_CONFIRM" && -z "$LLM_AGENT_VAR_AUTO_CONFIRM" ]]; then
# 2>/dev/tty: keep the prompt off the host-captured stderr pipe so it
# can't leak into tool_call_error JSON when the wrapped command fails.
ans="$(confirm "${1:-Are you sure you want to continue?}" 2>/dev/tty)"
ans="$(confirm "${1:-Are you sure you want to continue?}")"
if [[ "$ans" == 0 ]]; then
error "Operation aborted!" 2>&1
exit 1
fi
fi
fi
}
# Here is an example of a patch block that can be applied to modify the file to request the user's name:
@@ -585,10 +585,6 @@ patch_file() {
if (hunkIndex == 0) {
print "error: no patch" > "/dev/stderr"
print "" > "/dev/stderr"
print "No hunk header was found. Each hunk must start with a line beginning \"@@\"" > "/dev/stderr"
print "(for example \"@@ ... @@\" or \"@@ -1,4 +1,4 @@\"). Inside a hunk, context lines" > "/dev/stderr"
print "start with a single space, removed lines with \"-\", and added lines with \"+\"." > "/dev/stderr"
exit 1
}
@@ -604,14 +600,6 @@ patch_file() {
for (i = 2; i <= hunkTotalOriginalLines[hunkIndex]; i++) {
if (lines[nextLineIndex] != hunkOriginalLines[hunkIndex,i]) {
if (i - 1 > bestPartialLen[hunkIndex]) {
bestPartialLen[hunkIndex] = i - 1
bestPartialAnchorLine[hunkIndex] = lineIndex
bestPartialHunkPos[hunkIndex] = i
bestPartialDivergeLine[hunkIndex] = nextLineIndex
bestPartialExpected[hunkIndex] = hunkOriginalLines[hunkIndex,i]
bestPartialActual[hunkIndex] = lines[nextLineIndex]
}
nextLineIndex = 0
break
}
@@ -633,32 +621,7 @@ patch_file() {
}
if (hunkIndex != totalHunks + 1) {
failingHunk = hunkIndex
print "error: unable to apply patch" > "/dev/stderr"
print "" > "/dev/stderr"
print "Hunk " failingHunk " of " totalHunks " did not match the file." > "/dev/stderr"
if (bestPartialLen[failingHunk] == 0) {
print "" > "/dev/stderr"
print "The first context/removed line of hunk " failingHunk " was not found anywhere in the file:" > "/dev/stderr"
print " expected: " hunkOriginalLines[failingHunk, 1] > "/dev/stderr"
} else {
print "" > "/dev/stderr"
print "Closest match: anchored at file line " bestPartialAnchorLine[failingHunk] ", matched " bestPartialLen[failingHunk] " of " hunkTotalOriginalLines[failingHunk] " original lines before diverging." > "/dev/stderr"
print "" > "/dev/stderr"
print "At file line " bestPartialDivergeLine[failingHunk] " (hunk original line " bestPartialHunkPos[failingHunk] "):" > "/dev/stderr"
print " expected: " bestPartialExpected[failingHunk] > "/dev/stderr"
print " actual: " bestPartialActual[failingHunk] > "/dev/stderr"
}
print "" > "/dev/stderr"
print "Lines must match byte-for-byte (no fuzzy matching). Check escaping, whitespace, and quoting." > "/dev/stderr"
if (failingHunk < totalHunks) {
print "" > "/dev/stderr"
print (totalHunks - failingHunk) " subsequent hunk(s) were not attempted (patcher aborts on first failure)." > "/dev/stderr"
}
exit 1
}
}
@@ -692,18 +655,19 @@ guard_path() {
exit 1
fi
if [[ -t 1 ]]; then
path="$(_to_real_path "$1")"
confirmation_prompt="$2"
if [[ ! "$path" == "$(pwd)"* && -z "$AUTO_CONFIRM" && -z "$LLM_AGENT_VAR_AUTO_CONFIRM" ]]; then
# 2>/dev/tty: see guard_operation — prevents prompt text leaking via captured stderr.
ans="$(confirm "$confirmation_prompt" 2>/dev/tty)"
ans="$(confirm "$confirmation_prompt")"
if [[ "$ans" == 0 ]]; then
error "Operation aborted!" >&2
exit 1
fi
fi
fi
}
_to_real_path() {

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