fmt: reapplied formatting for the sse_transport module

# Conflicts:
#	docs/PHASE-1-IMPLEMENTATION-PLAN.md
#	src/cli/completer.rs
#	src/client/common.rs
#	src/config/agent.rs
#	src/config/input.rs
#	src/config/macros.rs
#	src/config/mod.rs
#	src/config/session.rs
#	src/function/mod.rs
#	src/function/supervisor.rs
#	src/function/todo.rs
#	src/function/user_interaction.rs
#	src/main.rs
#	src/mcp/mod.rs
#	src/rag/mod.rs
#	src/repl/mod.rs

.github/ISSUE_TEMPLATE/bug_report.yaml

@@ -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/release.yaml

@@ -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 = "'"$VERSION"'"|
             }
@@ -278,7 +278,7 @@ jobs:
       - name: Verify file
         shell: bash
         run: |
-          file target/${{ matrix.target }}/release/coyote
+          file target/${{ matrix.target }}/release/loki
 
       - name: Test
         if: matrix.target != 'aarch64-apple-darwin' && matrix.target != 'aarch64-pc-windows-msvc'
@@ -382,11 +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
@@ -402,23 +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

.gitignore

@@ -3,5 +3,5 @@
 /.env
 !cli/**
 .idea/
-/coyote.iml
+/loki.iml
 /.idea/

.loki-project.json

@@ -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

@@ -1,195 +1,3 @@
-## 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
@@ -213,7 +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
@@ -267,7 +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
@@ -327,8 +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

@@ -2,7 +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

@@ -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.
 
@@ -21,10 +21,10 @@ 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.
 

Cargo.toml

@@ -1,16 +1,16 @@
 [package]
-name = "coyote-ai"
-version = "0.6.0"
+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 = "MIT"
-rust-version = "1.95.0"
+rust-version = "1.89.0"
 exclude = [".github", "CONTRIBUTING.md"]
 
 [dependencies]
@@ -22,7 +22,7 @@ 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"
@@ -34,6 +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 = [
@@ -47,7 +51,7 @@ 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"] }
 shell-words = "1.1.0"
@@ -55,14 +59,20 @@ 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"
 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",
@@ -87,33 +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",
-] }
 
 [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
 
@@ -138,7 +140,7 @@ pretty_assertions = "1.4.0"
 serial_test = "3"
 
 [[bin]]
-name = "coyote"
+name = "loki"
 path = "src/main.rs"
 
 [profile.release]

README.md

@@ -1,114 +1,120 @@
-# 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)
+![Test](https://github.com/Dark-Alex-17/loki/actions/workflows/ci.yaml/badge.svg)
+[![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](https://raw.githubusercontent.com/wiki/Dark-Alex-17/loki/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](https://github.com/Dark-Alex-17/loki/wiki/AIChat-Migration) 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.
-* [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.
-* [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](https://github.com/Dark-Alex-17/loki/wiki/AIChat-Migration): 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](https://github.com/Dark-Alex-17/loki/wiki/REPL): Interactive Read-Eval-Print Loop for conversational interactions with LLMs and Loki.
+  * [Custom REPL Prompt](https://github.com/Dark-Alex-17/loki/wiki/REPL-Prompt): Customize the REPL prompt to provide useful contextual information.
+* [Vault](https://github.com/Dark-Alex-17/loki/wiki/Vault): Securely store and manage sensitive information such as API keys and credentials.
+* [Shell Integrations](https://github.com/Dark-Alex-17/loki/wiki/Shell-Integrations): Seamlessly integrate Loki with your shell environment for enhanced command-line assistance.
+* [Function Calling](https://github.com/Dark-Alex-17/loki/wiki/Tools): Leverage function calling capabilities to extend Loki's functionality with custom tools
+    * [Creating Custom Tools](https://github.com/Dark-Alex-17/loki/wiki/Custom-Tools): You can create your own custom tools to enhance Loki's capabilities.
+        * [Create Custom Python Tools](https://github.com/Dark-Alex-17/loki/wiki/Custom-Tools#custom-python-based-tools)
+        * [Create Custom TypeScript Tools](https://github.com/Dark-Alex-17/loki/wiki/Custom-Tools#custom-typescript-based-tools)
+        * [Create Custom Bash Tools](https://github.com/Dark-Alex-17/loki/wiki/Custom-Bash-Tools)
+            * [Bash Prompt Utilities](https://github.com/Dark-Alex-17/loki/wiki/Bash-Prompt-Helpers)
+* [First-Class MCP Server Support](https://github.com/Dark-Alex-17/loki/wiki/MCP-Servers): Easily connect and interact with MCP servers for advanced functionality.
+* [Macros](https://github.com/Dark-Alex-17/loki/wiki/Macros): Automate repetitive tasks and workflows with Loki "scripts" (macros).
+* [RAG](https://github.com/Dark-Alex-17/loki/wiki/RAG): Retrieval-Augmented Generation for enhanced information retrieval and generation.
+* [Sessions](https://github.com/Dark-Alex-17/loki/wiki/Sessions): Manage and persist conversational contexts and settings across multiple interactions.
+* [Roles](https://github.com/Dark-Alex-17/loki/wiki/Roles): Customize model behavior for specific tasks or domains.
+* [Agents](https://github.com/Dark-Alex-17/loki/wiki/Agents): Leverage AI agents to perform complex tasks and workflows, including sub-agent spawning, teammate messaging, and user interaction tools.
+    * [Todo System](https://github.com/Dark-Alex-17/loki/wiki/TODO-System): Built-in task tracking for improved agent reliability with smaller models.
+* [Environment Variables](https://github.com/Dark-Alex-17/loki/wiki/Environment-Variables): Override and customize your Loki configuration at runtime with environment variables.
+* [Client Configurations](https://github.com/Dark-Alex-17/loki/wiki/Clients): Configuration instructions for various LLM providers.
+    * [Authentication (API Key & OAuth)](https://github.com/Dark-Alex-17/loki/wiki/Clients#authentication): Authenticate with API keys or OAuth for subscription-based access.
+    * [Patching API Requests](https://github.com/Dark-Alex-17/loki/wiki/Patches): Learn how to patch API requests for advanced customization.
+* [Custom Themes](https://github.com/Dark-Alex-17/loki/wiki/Themes): 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`
 
-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
+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/main/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/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) |
 |----------------|-----------------|
@@ -119,58 +125,35 @@ 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](https://github.com/Dark-Alex-17/loki/wiki/Vault)). For providers that support OAuth (e.g. Claude Pro/Max 
 subscribers, Google Gemini), you can authenticate with your existing subscription instead:
 
 ```yaml
@@ -182,40 +165,40 @@ 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](https://github.com/Dark-Alex-17/loki/wiki/Clients#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
@@ -225,18 +208,18 @@ 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                                                                                                                                             |
@@ -246,34 +229,34 @@ 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](https://github.com/Dark-Alex-17/loki/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 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                                                                                                      |
@@ -285,7 +268,7 @@ 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.
 

assets/agents/.shared/utils.sh

@@ -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
 }
@@ -238,7 +238,7 @@ _detect_with_llm() {
 	)
 
   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)

assets/agents/code-reviewer/config.yaml

@@ -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
@@ -10,11 +11,6 @@ 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
@@ -22,7 +18,6 @@ variables:
 
 global_tools:
   - fs_read.sh
-  - fs_cat.sh
   - fs_grep.sh
   - fs_glob.sh
   - execute_command.sh
@@ -30,61 +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
 
@@ -152,7 +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

@@ -1,82 +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
 
-```
-analyze_request (llm + output_schema)   plan + complexity extraction
-        ↓
-route_complexity (script)               opt-out approval gate (complexity ≥ 7)
-        ↓
-gate_approval (approval, optional)
-        ↓
-implement (llm + fs tools)              actual file edits
-        ↓
-verify_build (script)
-        ↓
-verify_tests (script)
-        ↓
-fix_loop_gate (script)                  back-edge to implement (bounded)
-        ↓
-end_success / end_rejected / 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 nodes emit one of three sentinel outcomes for the caller:
+It can also be used as a standalone tool for direct coding assistance.
 
-- `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

@@ -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

@@ -1,375 +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:
-  - 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.
-
-      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: 30
-    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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -1,55 +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 // "."')
-
-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": "(no build/check command available for this project type)",
-    "_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

@@ -1,55 +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 // "."')
-
-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": "(no test command available for this project type)",
-    "_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

@@ -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

@@ -1,274 +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. `->` is the static route; a script node can also route
-dynamically via `_next`. The `▶▶` line is a parallel super-step —
-those branches run concurrently:
-
-```
-parse_request (script)              -> bootstrap_research   (or -> ask_topic if no topic)
-ask_topic (input)                   -> bootstrap_research
-bootstrap_research (script)         -> [plan, knowledge_lookup]   ▶▶ parallel
-plan (llm + output_schema)          -> research_each_question
-knowledge_lookup (rag)              -> research_each_question
-research_each_question (map)        -> combine_findings    (spawns one branch per question)
-  └─ research_one_question (llm)    (atomic; runs N×, joins at map)
-combine_findings (script)           -> vet_sources
-vet_sources (llm + custom tool)     -> critique
-critique (llm)                      -> reflexion_gate
-reflexion_gate (script)             -> synthesize  (or -> research_each_question: reflexion loop)
-synthesize (agent: report-writer)   -> verify_sources
-verify_sources (script)             -> approve
-approve (approval)                  -> end_accepted          ("accept")
-                                    -> end_rejected          ("reject")
-                                    -> incorporate_feedback   (any free-form answer)
-incorporate_feedback (script)       -> research_each_question (the human-feedback loop)
-```
-
-### 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

@@ -1,291 +0,0 @@
-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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -1,10 +1,7 @@
 name: explore
-description: Fast codebase exploration agent - finds patterns, structures, and relevant files. Designed to be fanned out 2-5 in parallel by orchestrators.
-version: 3.0.0
-
-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
@@ -15,99 +12,64 @@ mcp_servers:
   - ddg-search
 global_tools:
   - fs_read.sh
-  - fs_cat.sh
   - fs_grep.sh
   - fs_glob.sh
   - fs_ls.sh
 
 instructions: |
   You are a codebase explorer. Your job: Search, find, report. Nothing else.
+  
+  ## Your Mission
+  
+  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
+  
+  ## File Reading Strategy (IMPORTANT - minimize token usage)
 
-  ## Step 0: Load your skills
+  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
 
-  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:
-
-  - 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.
-
-  ## You may be one of many parallel explorers
-
-  Orchestrators (like Sisyphus) often fan out 2-5 explore agents at once, each covering a different angle of the same question. 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.
-
-  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.
-
-  ## Investigation methodology
-
-  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.
-
-  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)
-  - `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:
+  ## Available Actions
 
+  - `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
+  
+  ## Output Format
+  
+  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/config.yaml

@@ -1,11 +1,7 @@
 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
@@ -16,27 +12,18 @@ 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
 
@@ -65,13 +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
 
@@ -101,24 +87,27 @@ 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}}
   - CWD: {{__cwd__}}
-
+  
   ## Available Tools:
   {{__tools__}}

assets/agents/jira-helper/README.md

@@ -0,0 +1,14 @@
+# 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!

assets/agents/jira-helper/config.yaml

@@ -0,0 +1,37 @@
+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?

assets/agents/librarian/README.md

@@ -1,61 +0,0 @@
-# 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
-
-```
-search (llm + ddg-search)         identify 3-5 authoritative sources
-   ↓
-synthesize (llm + fetch_url_via_curl)   fetch, extract, cite, synthesize
-   ↓
-end_success / end_failure         LIBRARIAN_COMPLETE / LIBRARIAN_FAILED
-```
-
-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.

assets/agents/librarian/graph.yaml

@@ -1,380 +0,0 @@
-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.
-
-  Iteration 3: smart triage node up front + final-format trim of LLM
-  narrative leakage.
-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: []
-    temperature: 0.1
-    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
-    temperature: 0.1
-    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
-    temperature: 0.1
-    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
-    temperature: 0.1
-    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

@@ -1,3 +0,0 @@
-#!/usr/bin/env bash
-set -euo pipefail
-echo '{}'

assets/agents/librarian/scripts/final_format.sh

@@ -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

@@ -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

@@ -1,11 +1,7 @@
 name: oracle
-description: High-IQ advisor for architecture, debugging, and complex decisions. Blocking by design - the orchestrator is waiting on you.
-version: 2.0.0
-
-skills_enabled: true
-enabled_skills:
-  - code-review
-  - ai-slop-remover
+description: High-IQ advisor for architecture, debugging, and complex decisions
+version: 1.0.0
+temperature: 0.2
 
 variables:
   - name: project_dir
@@ -16,94 +12,71 @@ mcp_servers:
   - ddg-search
 global_tools:
   - 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
+  
+  You are READ-ONLY. You analyze, advise, and recommend. You do NOT implement.
+  
+  ## When You're Consulted
+  
+  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
+  
+  ## File Reading Strategy (IMPORTANT - minimize token usage)
 
-  ## Your role
+  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/`
 
-  You are READ-ONLY. You analyze, advise, recommend. You do NOT implement. Implementation is for the coder agent.
-
-  ## You are blocking by design
-
-  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.
-
-  Therefore:
-
-  - **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.
-
-  ## When you're consulted
-
-  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.
-
-  ## Skills available
-
-  Two skills are available to you. Load them 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).
-
-  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
+  ## 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
+  4. **Justify**: Explain your reasoning
+  
+  ## 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.]
-
-  ## Risks / Considerations
-  [What to watch out for during implementation. Known footguns. Edge cases.]
-
+  [Why this is the right approach]
+  
+  ## Risks/Considerations
+  [What to watch out for]
+  
   ORACLE_COMPLETE
   ```
-
+  
   ## 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

@@ -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

@@ -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

@@ -1,6 +1,6 @@
 # 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._
@@ -18,22 +18,23 @@ Sisyphus acts as the primary entry point, capable of handling complex tasks by c
 - 🛠️ **Tool Integration**: Seamlessly uses system tools for building, testing, and file manipulation.
 
 ## 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

@@ -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: 3.0.0
+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
@@ -13,17 +14,6 @@ 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
-
 variables:
   - name: project_dir
     description: Project directory to work in
@@ -39,345 +29,201 @@ global_tools:
   - 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:
+  ## Intent Classification (BEFORE every action)
 
-  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.
+  | Type | Signal | Action |
+  |------|--------|--------|
+  | Trivial | Single file, known location, typo fix | Do it yourself with tools |
+  | 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` |
 
-     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."
+  ### Oracle Triggers (MUST spawn oracle when you see these)
 
-     The verbalization anchors routing and makes reasoning transparent. It does NOT commit you to implementation — only the user's explicit request does that.
+  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"
 
-  2. **Classify** (after verbalizing):
+  **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.
 
-     | 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` |
-
-  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.
-
-  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**.
-
-  ## Oracle Triggers (MUST spawn oracle when you see these)
-
-  - "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` |
-
-  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 2-5 in parallel |
-  | `librarian` | Find official docs, OSS examples, web best practices for EXTERNAL libraries | Read-only, returns citation-backed findings, fan out 1-3 in parallel |
-  | `coder` | Write/edit files, implement features | Graph agent: plan → approval → implement → verify build+tests → self_review → bounded fix-loop |
-  | `oracle` | Architecture, complex debugging, review | Advisory, blocking — never answer the user before collecting Oracle results |
+  | 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 2-5 `explore` agents in parallel, each scoped to a different angle. Each gets a NARROW slice.
-
-  ### 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.
-
-  ### 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.
+  User: "How should I structure the authentication for this app?"
 
-  ### When NOT to re-spawn code-reviewer
+  ```
+  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
+  ```
 
-  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.
+  ### Example 3: Vague/open-ended question (oracle directly)
 
-  ## File Operations (Direct Edits)
+  User: "What do you think of this codebase structure?"
 
-  When you write or modify files yourself (rather than delegating to coder):
+  ```
+  agent__spawn --agent oracle --prompt "Review the project structure and provide recommendations for improvement"
+  agent__collect --id <oracle_id>
+  ```
 
-  - **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
+  ## Rules
 
-    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.
+  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 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 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.
+  - Simple command execution
+  - Trivial changes (typos, renames)
+  - Quick file searches
 
-  ## Phase 7 - Failure Recovery
+  ## When to NEVER Do It Yourself
 
-  ### 3-strike rule
+  - 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
 
-  After 3 consecutive failed fix attempts on the same problem:
+  ## User Interaction (CRITICAL - get buy-in before major decisions)
 
-  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.
+  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.**
 
-  Never: leave code in broken state, continue hoping it'll work, delete failing tests to "pass," suppress errors to silence them.
+  ### When to Prompt the User
 
-  ## When to Do It Yourself vs Delegate
+  | 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 |
 
-  **Do yourself**: trivial typos/renames, single-file changes you've already read, simple command execution, quick file searches you can express in one grep.
+  ### Design Review Pattern
 
-  **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
+  For implementation tasks with design decisions, follow this pattern:
 
-  ## User Interaction (get buy-in before major decisions)
+  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
 
-  Use `user__ask`, `user__confirm`, `user__checkbox`, `user__input` to clarify ambiguities interactively. **Do NOT guess when you can ask.**
+  ### Rules for User Prompts
 
-  | 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/functions/mcp.json

@@ -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",

assets/functions/scripts/run-agent.py

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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

@@ -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/execute_command.sh

@@ -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

@@ -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_grep.sh

@@ -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
 
@@ -20,39 +19,33 @@ main() {
     local search_path="${argc_path:-.}"
     local include_filter="${argc_include:-}"
 
-    if [[ ! -e "$search_path" ]]; then
-        echo "Error: path not found: $search_path" >> "$LLM_OUTPUT"
+    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 "$search_path" ]]; then
-        # Use -r (not -R) so symlinks to directories are NOT followed - this avoids
-        # infinite loops on pathological symlink cycles (e.g. `ln -s . loop`).
-        grep_args+=(-r)
-        grep_args+=(
-            --exclude-dir='.git'
-            --exclude-dir='node_modules'
-            --exclude-dir='target'
-            --exclude-dir='dist'
-            --exclude-dir='build'
-            --exclude-dir='__pycache__'
-            --exclude-dir='vendor'
-            --exclude-dir='.build'
-            --exclude-dir='.next'
-            --exclude='*.min.js'
-            --exclude='*.min.css'
-            --exclude='*.map'
-            --exclude='*.lock'
-            --exclude='package-lock.json'
-        )
-        if [[ -n "$include_filter" ]]; then
-            grep_args+=("--include=$include_filter")
-        fi
+    grep_args+=(
+        --exclude-dir='.git'
+        --exclude-dir='node_modules'
+        --exclude-dir='target'
+        --exclude-dir='dist'
+        --exclude-dir='build'
+        --exclude-dir='__pycache__'
+        --exclude-dir='vendor'
+        --exclude-dir='.build'
+        --exclude-dir='.next'
+        --exclude='*.min.js'
+        --exclude='*.min.css'
+        --exclude='*.map'
+        --exclude='*.lock'
+        --exclude='package-lock.json'
+    )
+
+    if [[ -n "$include_filter" ]]; then
+        grep_args+=("--include=$include_filter")
     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_patch.sh

@@ -1,10 +1,8 @@
 #!/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.
+# @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 --contents! The patch to apply to the file
@@ -16,9 +14,6 @@ source "$LLM_PROMPT_UTILS_FILE"
 
 # shellcheck disable=SC2154
 main() {
-    argc_contents="$(jq -r '.contents' <<< "$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

@@ -1,10 +1,8 @@
 #!/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

assets/functions/tools/fs_write.sh

@@ -1,9 +1,7 @@
 #!/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 --contents! The full contents to write to the file
@@ -15,9 +13,6 @@ source "$LLM_PROMPT_UTILS_FILE"
 
 # shellcheck disable=SC2154
 main() {
-    argc_contents="$(jq -r '.contents' <<< "$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/send_mail.sh

@@ -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_loki.sh

@@ -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

@@ -506,16 +506,16 @@ open_link() {
 }
 
 guard_operation() {
-	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)"
+  if [[ -t 1 ]]; then
+  	if [[ -z "$AUTO_CONFIRM" && -z "$LLM_AGENT_VAR_AUTO_CONFIRM" ]]; then
+			ans="$(confirm "${1:-Are you sure you want to continue?}")"
 
-		if [[ "$ans" == 0 ]]; then
-			error "Operation aborted!" 2>&1
-			exit 1
+			if [[ "$ans" == 0 ]]; then
+				error "Operation aborted!" 2>&1
+				exit 1
+			fi
 		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:
@@ -655,18 +655,19 @@ guard_path() {
     exit 1
   fi
 
-	path="$(_to_real_path "$1")"
-	confirmation_prompt="$2"
+  if [[ -t 1 ]]; then
+    path="$(_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)"
+    if [[ ! "$path" == "$(pwd)"* && -z "$AUTO_CONFIRM" && -z "$LLM_AGENT_VAR_AUTO_CONFIRM" ]]; then
+			ans="$(confirm "$confirmation_prompt")"
 
-		if [[ "$ans" == 0 ]]; then
-			error "Operation aborted!" >&2
-			exit 1
-		fi
-	fi
+			if [[ "$ans" == 0 ]]; then
+				error "Operation aborted!" >&2
+				exit 1
+			fi
+    fi
+  fi
 }
 
 _to_real_path() {

assets/roles/atlassian.md

@@ -1,8 +0,0 @@
----
-enabled_mcp_servers: atlassian
----
-You are the librarian for the company's Confluence and Jira knowledge bases. Your job is to help users find and retrieve
-information from these platforms. Use all tools at your disposal to answer user queries.
-
-Available Tools:
-{{__tools__}}

assets/roles/create-prompt.md

@@ -1,6 +1,3 @@
----
-skills_enabled: false
----
 As a professional Prompt Engineer, your role is to create effective and innovative prompts for interacting with AI models.
 
 Your core skills include:

assets/roles/create-title.md

@@ -1,6 +1,3 @@
----
-skills_enabled: false
----
 Create a concise, 3-6 word title.
 
 **Notes**:

assets/roles/explain-shell.md

@@ -1,6 +1,3 @@
----
-skills_enabled: false
----
 Provide a terse, single sentence description of the given shell command.
 Describe each argument and option of the command.
 Provide short responses in about 80 words.

assets/roles/repo-analyzer.md

@@ -9,7 +9,7 @@ security/configuration settings. The analysis aims to ensure a thorough understa
 structured and operates, enabling the creation of new files, maintaining consistency with existing practices, and the
 potential implementation of best practices.
 
-Should the root directory contain a `COYOTE.md` file, this was generated by Coyote and should be used as a reference
+Should the root directory contain a `LOKI.md` file, this was generated by Loki and should be used as a reference
 point for all analysis, style questions, etc.
 
 **Objective:** Enable the AI to thoroughly analyze a software repository, providing detailed insights and guidelines on

assets/roles/shell.md

@@ -1,6 +1,3 @@
----
-skills_enabled: false
----
 Provide only {{__shell__}} commands for {{__os_distro__}} without any description.
 Ensure the output is a valid {{__shell__}} command.
 If there is a lack of details, provide most logical solution.

assets/roles/slack.md

@@ -1,5 +1,6 @@
 ---
 enabled_mcp_servers: slack
+temperature: 0.2
 ---
 You are an expert Slack assistant designed to assist with Slack workspaces via the slack MCP server. 
 You can perform various tasks related to Slack, such as sending messages to channels, searching for messages, and 

assets/skills/ai-slop-remover/SKILL.md

@@ -1,39 +0,0 @@
----
-description: Detect and remove AI slop from code and prose; produce output indistinguishable from a senior engineer's.
----
-You are reviewing or generating content. Apply these standards strictly. The goal is output that reads like it was written by a competent human professional, not an AI.
-
-## Code
-
-**No useless comments.** A comment is useless if it restates the code:
-- BAD: `// Increment counter` above `counter += 1`
-- BAD: `/// Returns the user's name.` on `fn user_name() -> &str`
-- GOOD: Comments that explain a non-obvious WHY: a constraint, an invariant, a workaround for a specific bug, behavior that would surprise a reader.
-
-If removing a comment wouldn't confuse a future reader, the comment shouldn't exist.
-
-**No emojis** unless the user explicitly asked for them.
-
-**No defensive handling for impossible cases.** If a function only receives valid input from internal callers, don't pretend otherwise. Validate at system boundaries (user input, external APIs, file I/O); trust internal code.
-
-**No over-engineering for hypothetical futures.** Three similar lines of code is fine. Premature abstractions are worse than duplication.
-
-**No backwards-compatibility cruft for unreleased code.** If a function isn't called yet, just change it. Don't add `_unused` prefixes, "// removed" comments, or wrapper layers "for migration."
-
-**Names should be honest.** A function called `get_user` should not mutate state. A field called `count` should not be a function. A method that can fail should return `Result`, not panic.
-
-## Prose
-
-**No flattery.** Don't start with "Great question!" or "That's a really good idea!" Just respond.
-
-**No filler.** "It's important to note that" — delete. "Let me explain" — just explain. "I'll go ahead and" — just do it.
-
-**No status updates.** "I'm going to help you with that" — just help.
-
-**Match the user's terseness.** Brief user, brief reply. Detailed user, detailed reply.
-
-**No multi-paragraph docstrings.** One short line max. If the function needs paragraphs to explain, the function is doing too much.
-
-## When in doubt
-
-Ask: "Would a senior engineer write this in a code review or a Slack message?" If not, cut it.

assets/skills/code-review/SKILL.md

@@ -1,124 +0,0 @@
----
-description: Conduct a thorough code review focused on correctness, clarity, tests, and footguns. Grants read-only filesystem access for inspecting code.
-enabled_tools: fs_read, fs_grep, fs_glob, fs_cat, fs_ls
----
-You are reviewing code. Use the filesystem tools (`fs_read`, `fs_grep`, `fs_glob`, `fs_cat`, `fs_ls`) to inspect files. Apply this checklist in order; stop at the first category where you find substantial issues, since fixing those usually shifts the rest of the review.
-
-## Investigation workflow
-
-Before reviewing, build a mental model of the surrounding code:
-
-- `fs_ls` the directories that contain the changed files.
-- `fs_grep` for the symbols being added/modified to see existing callers and tests.
-- `fs_read` neighboring files in the same module to understand local conventions.
-- `fs_glob` for test files that might cover this area.
-
-A review without context is just a syntax check.
-
-## Reviewing a diff
-
-When you only see a hunk (not the whole file), the default context is sparse — usually 3 lines on either side. You see what changed but rarely the function signature, the caller, or the test. Read deliberately to recover what the diff omits.
-
-### Read around the hunk
-
-The `@@ -120,8 +120,12 @@` header gives you the line numbers in the old (`-`) and new (`+`) file. Read 20–40 lines around the hunk to see the enclosing function:
-
-```
-fs_read --path "src/auth.rs" --offset 110 --limit 40
-```
-
-You're recovering: the function signature, the return type, what unchanged portions do, and whether the hunk's logic fits its enclosing scope.
-
-### Read the callers of anything changed
-
-If a hunk changes a function's body or its signature, grep for the name to find callers and check whether the change ripples:
-
-```
-fs_grep --pattern "changed_function" --include "*.rs"
-```
-
-Skip the test files in this search; do the test sweep next.
-
-### Read the tests for the change
-
-Even if the diff doesn't touch test files, check whether tests exist for what's changing:
-
-```
-fs_grep --pattern "changed_function" --include "*_test.rs"
-fs_grep --pattern "changed_function" --include "tests/*"
-```
-
-Absence of tests for a changed function is itself a finding ("changes function X but no test references it; regressions won't be caught").
-
-### Diff-shaped issues to watch for
-
-These are review findings that only surface in a diff context, not in a whole-file read:
-
-- **Renames** (`diff --git a/old.rs b/new.rs`) — `fs_grep` for the old path to find imports that need updating but weren't.
-- **Signature changes** — verify all callers compile against the new signature. Compiler-checked languages catch some of this; dynamic languages don't.
-- **New code path without new tests** — usually a missing test. Flag it.
-- **Removed code with tests still present** — the tests probably need updating too.
-- **The "dog that didn't bark"** — what's obvious by its ABSENCE? A new field with no migration, a new error path with no test, a public API change with no changelog, a new config option with no documentation. Flag these as missing pieces, not as things to add later.
-
-### Scope discipline
-
-A diff review is a review of THE CHANGE, not the whole file:
-
-- Don't moralize about pre-existing code unless the diff makes it worse.
-- Don't suggest refactors outside the scope of the change. ("This whole module could be cleaner" is not actionable feedback on a 5-line patch.)
-- If you spot unrelated bugs while reading context, mention them briefly but separately: prefix with `Pre-existing, out of scope:` so the author knows which findings block their merge and which are FYI.
-- The author's job is to ship THIS change. Your job is to catch what's wrong with THIS change.
-
-## 1. Correctness
-
-- Does the change actually do what it claims? Does it solve the stated problem?
-- Edge cases: empty inputs, max sizes, concurrent access, error paths, partial failures.
-- Off-by-one errors, type confusion, null/None handling, integer overflow.
-- Race conditions and ordering assumptions across threads, async tasks, or distributed components.
-- Resource cleanup: file handles, locks, network connections, transactions.
-
-## 2. Tests
-
-- Do the tests test BEHAVIOR, not implementation? (Tests of `private_helper()` are usually a smell.)
-- Will they fail when the code regresses? Or are they tautological (e.g., `assert!(x.is_empty() || !x.is_empty())`)?
-- Do they cover the unhappy paths, not just the happy ones?
-- Is there a missing test for the specific bug or feature being added? `fs_grep` for the function name in test files to check.
-
-## 3. Clarity
-
-- Are names accurate? `get_user` that mutates is a lie; rename or split.
-- Could a competent reader understand this without comments?
-- Is there a simpler way to express the same logic?
-- Is the function doing one thing, or several things glued together?
-
-## 4. Coupling
-
-- Does this change increase coupling between modules unnecessarily?
-- Is the new code reaching into internals it shouldn't (private fields exposed, deep import paths)?
-- Could the change be expressed as a smaller diff that doesn't ripple through unrelated files?
-
-## 5. Footguns
-
-- Could a future maintainer easily misuse this API?
-- Are invariants enforced by types, or just by convention?
-- Are error types specific enough to be actionable?
-- Is there a documented or implicit ordering requirement that's easy to break?
-
-## What to flag
-
-- Correctness bugs.
-- Missing error handling at trust boundaries.
-- Race conditions.
-- Tests that won't catch regressions.
-- Security issues (injection, auth, exposed secrets).
-
-## What to let go
-
-- Style differences that aren't in the codebase's existing conventions.
-- "I would have done it differently" preferences.
-- Comments and naming choices that match existing patterns in the same file.
-- Micro-optimizations in code that isn't on a hot path.
-
-## Tone
-
-Direct, specific, focused on the code. No flattery, no padding. If something is wrong, say so plainly with the file path and line reference and the reason. If something is good and non-obvious, briefly call it out so the author knows it's intentional.

assets/skills/delegation-protocol/SKILL.md

@@ -1,69 +0,0 @@
----
-description: Structured 6-section delegation template and session-continuity rules for orchestrating sub-agents. Load before spawning any agent.
----
-You are delegating work to a sub-agent. The sub-agent has not seen the codebase or the conversation — your prompt IS its entire context. Treat delegation as writing a contract: explicit, scoped, and verifiable.
-
-## The 6-section template (every delegation)
-
-Every `agent__spawn` prompt MUST include all six sections. Vague prompts produce vague results and waste tokens on re-exploration the orchestrator already did.
-
-```
-## TASK
-[One atomic goal. One verb. One outcome. No "and also".]
-
-## EXPECTED OUTCOME
-[Concrete deliverables and success criteria. "I will know this is done when ..."]
-
-## REQUIRED TOOLS
-[Explicit allowlist: fs_read, fs_grep, etc. Prevents tool sprawl.]
-
-## MUST DO
-[Exhaustive requirements. Leave nothing implicit. If you'd be annoyed by the agent not doing X, list X.]
-
-## MUST NOT DO
-[Forbidden actions. Anticipate rogue behavior. "Do not modify files outside src/auth/."]
-
-## CONTEXT
-[File paths, code snippets, existing patterns, constraints. Paste actual code lines from prior exploration — not just file paths.]
-```
-
-## Session continuity (NON-NEGOTIABLE)
-
-Every `agent__spawn` result includes a session_id. **Use it.**
-
-- Task failed/incomplete → resume with `session_id` + a tight "Fix: <error>" prompt.
-- Follow-up on a result → resume with `session_id` + "Also: <question>".
-- Multi-turn with the same agent → always resume. Never start fresh.
-
-Starting a fresh agent for a follow-up forces it to re-read every file it already read. That's 70%+ wasted tokens, plus the agent loses the reasoning it built up.
-
-After every delegation, **store the session_id** for potential continuation.
-
-## Skill nudges to delegates
-
-Sub-agents have their own skills. Nudge them in the CONTEXT section:
-
-> "Load `code-review` before evaluating the diff."
-> "Load `frontend-ui-ux` before editing component files."
-> "Load `git-master` before touching history."
-
-A one-line nudge saves the delegate a `skill__list` turn.
-
-## Verification after delegation
-
-A delegation is NOT complete when the sub-agent returns. It is complete when YOU have verified:
-
-1. Did it work as expected? (Did the file change? Did the test pass?)
-2. Did it follow existing codebase patterns?
-3. Did the EXPECTED OUTCOME actually materialize?
-4. Did it respect MUST DO and MUST NOT DO?
-
-If any answer is no → resume the session with a corrective prompt. Do not re-spawn from scratch.
-
-## Anti-patterns
-
-- "Follow existing patterns" with no snippet → agent guesses, often wrong
-- Multi-goal prompts → agent does the easy one, skips the rest
-- Missing MUST NOT DO → agent over-reaches into unrelated files
-- Discarding session_id on failure → forced re-exploration, wasted tokens
-- Re-spawning instead of resuming for a 1-line fix → 10x cost

assets/skills/frontend-ui-ux/SKILL.md

@@ -1,67 +0,0 @@
----
-description: Designer-turned-developer who crafts stunning UI/UX even without design mockups. Grants filesystem read/write access for editing component files.
-enabled_tools: fs_read, fs_write, fs_patch, fs_grep, fs_glob, fs_cat, fs_ls, fs_mkdir
----
-You are doing frontend work. Use the filesystem tools to read, write, and patch component files. Treat UI/UX as a discipline, not a polish step at the end.
-
-## Investigate before editing
-
-Before changing a component:
-
-- `fs_ls` the component's directory to see siblings and tests.
-- `fs_read` the component itself.
-- `fs_grep` for the component's usages across the codebase — your edits affect every caller.
-- `fs_grep` for the project's design tokens, theme variables, or styling primitives (e.g., `--color-`, `theme.spacing`, `tw-`).
-- Read existing similar components to match conventions.
-
-## Visual hierarchy
-
-Every screen has a focal point. Identify it before laying out anything else:
-
-- One primary action per view. Make it visually dominant.
-- Secondary actions are present but visibly subordinate.
-- Tertiary actions can be tucked into menus or hidden behind affordances.
-
-## Spacing and rhythm
-
-- Use the project's existing spacing scale (4px, 8px, custom — match what's already there). Don't introduce one-off values.
-- Larger spacing = stronger grouping break. Inside a card, tight; between cards, looser.
-- White space is not wasted space. It's the difference between "professional" and "cramped."
-
-## Typography
-
-- Two or three sizes per view, max. More than that is noise.
-- Line-height: 1.4-1.6 for body, tighter for headlines.
-- Don't center long paragraphs. Left-align (or right-align for RTL).
-
-## Color
-
-- Use the project's existing palette. If you need a color that isn't there, you're probably overdesigning.
-- Contrast matters: aim for WCAG AA at minimum (4.5:1 for body text, 3:1 for large text).
-- Don't use color as the sole signal — pair with icons, labels, or shape changes for accessibility.
-
-## Component conventions
-
-When adding a new component:
-
-- Match the existing structure: where do props go, where do styles go, where do tests go?
-- `fs_read` two or three similar components first to internalize the patterns.
-- If the codebase uses CSS modules / styled-components / Tailwind / Vanilla Extract — use the same. Don't introduce a new system.
-- Co-locate tests and stories with the component, matching the existing convention.
-
-## Forms
-
-- Label every input. Placeholder text is not a label.
-- Show validation errors near the field, not in a banner at the top.
-- Validate on blur, not on every keystroke. Show success states only after the user has interacted.
-- Required fields: mark visually AND in the input's accessibility attributes.
-
-## Loading and empty states
-
-- Empty states are an opportunity, not a fallback. Tell the user what they can do, not "no data."
-- Loading: show structure (skeletons) when you know what's coming. Spinners are for indeterminate waits.
-- Errors: explain WHAT failed and what the user can do about it. "Something went wrong" is useless.
-
-## When unsure
-
-Ship the boring version. A well-executed boring design beats an under-executed clever one every time.

assets/skills/git-master/SKILL.md

@@ -1,58 +0,0 @@
----
-description: Methodology for atomic commits, rebase surgery, and clean git history. Grants shell access for running git commands.
-enabled_tools: execute_command
----
-You are operating on a git repository. Apply these conventions strictly. Use the `execute_command` tool to run git commands.
-
-## Atomic commits
-
-Each commit represents one logical change. If the commit message needs the word "and," the change is too large; split it. Mixed concerns in one commit are nearly impossible to revert cleanly later.
-
-## Commit messages
-
-- Subject line: imperative mood, ≤50 characters, no trailing period.
-- Blank line.
-- Body: explain WHY, not WHAT. The diff shows what changed.
-- Reference issues by URL or canonical ID, not by free-form description.
-
-## Rebase, don't merge
-
-- `git rebase -i origin/main` before opening a PR.
-- Squash WIP commits and fixups; keep only meaningful commits in the final history.
-- Never rebase a branch others may have based work on. If unsure, ask.
-
-## Conflict resolution
-
-- Read both sides carefully before resolving. Don't reflexively take "ours" or "theirs."
-- After resolving, run tests before continuing the rebase.
-- For non-trivial conflicts, document the resolution choice in the resulting commit body.
-
-## Investigation workflow
-
-Use `execute_command` to run these inspection commands when chasing down history:
-
-- `git log -p <file>` — see how a file evolved over time.
-- `git log -S '<string>'` (pickaxe) — find when a string was added or removed.
-- `git log --all --grep '<pattern>'` — search commit messages.
-- `git blame -L <start>,<end> <file>` — current authorship for a line range.
-- `git diff <ref1>..<ref2> -- <path>` — narrow diffs to specific paths.
-- `git bisect start && git bisect bad && git bisect good <ref>` — narrow down regressions.
-
-## Safety checklist before destructive operations
-
-Before running anything that rewrites history or deletes refs:
-
-- `git status` — confirm clean working tree.
-- `git branch --show-current` — confirm which branch you're on.
-- `git log -3 --oneline` — confirm what's about to be moved.
-
-## What to never do
-
-- Force-push to shared branches (`main`, release branches, anything teammates pull from).
-- `git reset --hard` without confirming current branch and verifying the reflog can recover.
-- `git push --no-verify` to skip hooks — fix the underlying issue instead.
-- Commit secrets, even temporarily. Once pushed, treat as compromised; rotate.
-
-## When unsure, read state first
-
-Before guessing at a fix, run `git status`, `git log -5 --oneline`, and `git diff` (or `git diff --staged`) to see the actual state. Don't operate on assumptions.

assets/skills/oracle-protocol/SKILL.md

@@ -1,81 +0,0 @@
----
-description: Discipline for when and how to consult Oracle - blocking by design, never deliver an answer with Oracle pending, never bypass Oracle for design questions.
----
-Oracle is your read-only, high-IQ advisor. Using it correctly is the difference between shipping the right thing slowly and shipping the wrong thing fast.
-
-## When you MUST consult Oracle
-
-Spawn `oracle` (do NOT answer yourself) any time the user asks:
-
-- "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 — "improve this", "make this better", "clean this up"
-- After 2+ failed fix attempts on the same problem — complex debugging
-
-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.
-
-## Oracle is BLOCKING by design
-
-The orchestrator (you) has paused work and CANNOT proceed until Oracle returns. This is intentional. The cost of Oracle's latency is paid so YOU get a thorough, considered answer rather than rushing in a wrong direction.
-
-Therefore:
-
-- **Do NOT implement before Oracle returns** if your implementation depends on Oracle's recommendation.
-- **Do NOT deliver the final user-facing answer** while Oracle is still running.
-- **Do NOT "time out and continue anyway"** for Oracle-dependent tasks.
-- While waiting, do only NON-OVERLAPPING prep work (work that doesn't depend on Oracle's verdict).
-
-## How to consult Oracle effectively
-
-Oracle has not seen the codebase or the conversation. Give it enough context to think:
-
-```
-## Question
-[The decision you need help with, stated as a question]
-
-## Background
-[Why this question matters now. What constraint or trigger raised it.]
-
-## Code context
-[Paste the actual snippets from prior exploration — file paths alone are not enough]
-- From `path/to/file.ext`:
-  <relevant 5-20 lines>
-
-## What you've considered
-[Options you've already weighed and their tradeoffs as you see them]
-
-## What I'd love Oracle to evaluate
-[Specific aspects: correctness, performance, security, future flexibility, etc.]
-```
-
-A well-scoped Oracle consult returns a tighter answer faster.
-
-## After Oracle returns
-
-1. Read the recommendation, reasoning, and risks sections carefully.
-2. If the recommendation conflicts with your prior plan, update the plan — do not silently ignore Oracle.
-3. Pass Oracle's recommendation (and reasoning) to the implementer (e.g., coder) as CONTEXT in your delegation.
-4. If you disagree with Oracle's verdict, raise it with the user before implementing the alternative — don't act unilaterally against Oracle's advice.
-
-## When NOT to consult Oracle
-
-- Simple file operations you can do with direct tools
-- First attempt at any fix (try yourself first; consult after 2 failures)
-- Questions answerable from code you've already read
-- Trivial decisions (variable names in small functions, formatting)
-- Things you can infer from existing code patterns
-
-Over-consultation wastes Oracle's budget and slows the work. Reserve Oracle for genuinely hard or load-bearing decisions.
-
-## Anti-patterns (BLOCKING)
-
-- Answering an architecture question yourself "just this once"
-- Delivering a user-facing answer while Oracle is still running
-- Implementing the obvious approach without consulting Oracle on a tradeoff question
-- Ignoring Oracle's recommendation because it's inconvenient
-- Polling `agent__collect` on a running Oracle (end your response, wait for notification)

assets/skills/parallel-research/SKILL.md

@@ -1,70 +0,0 @@
----
-description: Fan-out exploration protocol — fire multiple research agents in parallel, wait for completion notifications, and never duplicate delegated work.
----
-You are entering a research phase. Exploration is parallelizable; serial reads leave throughput on the table.
-
-## Fan out, don't read serially
-
-For any non-trivial codebase question, fire 2-5 `explore` agents in parallel, each scoped to a different angle:
-
-- Auth implementation? → one for routes, one for middleware, one for token handling, one for error response shape.
-- Bug investigation? → one for the failing path, one for similar working paths, one for recent changes near the area.
-
-Each agent gets a NARROW slice. Narrow scope = fast, focused result. Broad scope = the agent over-reads and returns a wall of text.
-
-## The wait protocol
-
-After spawning background agents:
-
-1. If you have **non-overlapping** work to do (work that doesn't depend on the delegated research), do it now.
-2. If you don't, **end your response.** Do not call `agent__collect` immediately — the agent is still running.
-3. The system notifies you when the agent completes (`pending_escalations` or completion event).
-4. On notification, call `agent__collect` to retrieve results.
-
-Polling `agent__collect` on a still-running agent blocks your turn for nothing.
-
-## Anti-duplication rule (BLOCKING)
-
-Once you delegate a search to an `explore` agent, **do not perform that same search yourself.**
-
-Forbidden:
-- After firing `explore` for "auth middleware", running `fs_grep` for "auth middleware" yourself
-- "Just quickly checking" the same files the delegate is checking
-- Re-doing the research while waiting impatiently
-
-Allowed:
-- Non-overlapping work in a different module
-- Preparation work that doesn't depend on the delegated result
-- Ending your response and waiting
-
-Duplicate searches waste tokens, may contradict the delegate, and defeat the point of parallelism.
-
-## Stop conditions
-
-Stop searching when:
-
-- The same information appears across multiple sources
-- Two search iterations yield no new useful data
-- A direct answer was found
-- You have enough context to proceed confidently
-
-Over-exploration is as bad as under-exploration. Time spent searching is time not spent shipping.
-
-## Parallel + sequential composition
-
-It is fine to fire `explore` and then `oracle` when oracle needs the explore results — just sequence them:
-
-1. Fire explore(s) in parallel.
-2. End response, wait for completion.
-3. Synthesize findings, fire `oracle` with those findings as CONTEXT.
-4. End response, wait for oracle.
-5. Act on oracle's recommendation.
-
-Don't fire oracle blind to "save a turn" — it will give worse advice.
-
-## Anti-patterns
-
-- One huge "explore everything about X" agent → slow, unfocused result
-- Serial explores ("wait for first, then fire next") → unnecessary latency
-- Firing 8+ parallel agents → diminishing returns, harder to synthesize
-- Calling `agent__collect` immediately after spawn → wastes a turn

assets/skills/verification-gates/SKILL.md

@@ -1,66 +0,0 @@
----
-description: Evidence requirements before claiming completion — diagnostics, build exit code, tests. No completion without proof. Grants shell access for running build/test commands.
-enabled_tools: execute_command
----
-You are about to mark work complete. Before claiming "done," produce evidence. "I'm fairly confident it works" is not evidence.
-
-## Hard gates
-
-A task is NOT complete until:
-
-| Change kind | Required evidence |
-|---|---|
-| File edit | Read the file to confirm the change landed; output is clean (or only pre-existing issues, explicitly noted) |
-| Build command exists | `execute_command` the build; exit code 0 |
-| Test command exists | `execute_command` the tests; pass (or explicit note of pre-existing failures unrelated to this change) |
-| Delegation | The delegate's result was received AND verified against your acceptance criteria |
-
-**No evidence = not complete.** Marking a todo done without evidence is dishonest reporting.
-
-## The verification loop
-
-After every meaningful edit:
-
-1. Read the changed file region (confirm the change actually landed where intended).
-2. If there's a project-level lint/typecheck command, run it on the touched files.
-3. Run the project's build/check command if one exists.
-4. Run the project's test command if one exists.
-5. Only then mark the corresponding todo `completed`.
-
-If any step fails: do not mark complete. Fix the issue or surface it explicitly.
-
-## Build/test detection (fallback)
-
-If no build/test command is configured, try standard ones for the project:
-
-- Rust: `cargo check`, `cargo test`
-- Node/TS: `npm run build`, `npm test`, or `pnpm` / `yarn` equivalents
-- Python: `pytest`, `python -m mypy <pkg>`, `ruff check`
-- Go: `go build ./...`, `go test ./...`
-
-Run from the project root. Capture exit codes.
-
-## Distinguishing your failures from pre-existing failures
-
-If build or tests fail, identify the cause:
-
-- Caused by your change? → fix it before reporting complete.
-- Pre-existing (unrelated)? → note it explicitly: "Done. Build passes. Note: 3 lint errors pre-existing in unrelated files, not touched."
-
-Never silently leave broken state behind. Never delete a failing test to make CI green.
-
-## Anti-patterns (BLOCKING)
-
-- "It should work" without running anything
-- Marking a todo complete based on intent, not verified outcome
-- Suppressing errors with `@ts-ignore`, `as any`, `#[allow(...)]` on unfamiliar lints, empty catch blocks
-- Deleting failing tests to "pass"
-- Reporting "all green" when you only ran a subset
-
-## Reporting completion
-
-When the work is verifiably done, report in one sentence:
-
-> "Done. Build passes, 47 tests pass. Modified `auth.rs:42-58` to add JWT validation."
-
-Not a paragraph. Not a victory lap. Specific, terse, evidence-backed.

config.agent.example.yaml

@@ -1,5 +1,5 @@
 # Agent-specific configuration
-# Location `<coyote-config-dir>/agents/<agent-name>/config.yaml`
+# Location `<loki-config-dir>/agents/<agent-name>/config.yaml`
 #
 # Available Environment Variables:
 #   - <agent-name>_MODEL
@@ -17,18 +17,16 @@ agent_session: null              # Set a session to use when starting the agent.
 name: <agent-name>               # Name of the agent, used in the UI and logs
 description: <description>       # Description of the agent, used in the UI
 version: 1                       # Version of the agent
-# Auto-Continue (Todo System)
-# The auto-continue system provides built-in task tracking for improved reliability.
-# When enabled, the model can create todo lists and the system will automatically
-# prompt it to continue when incomplete tasks remain.
-# See the [Todo System documentation](https://github.com/Dark-Alex-17/coyote/wiki/TODO-System) for more information
+# Todo System & Auto-Continuation
+# These settings help smaller models handle multi-step tasks more reliably.
+# See docs/TODO-SYSTEM.md for detailed documentation.
 auto_continue: false             # Enable automatic continuation when incomplete todos remain
 max_auto_continues: 10           # Maximum number of automatic continuations before stopping
 inject_todo_instructions: true   # Inject the default todo tool usage instructions into the agent's system prompt
 continuation_prompt: null        # Custom prompt used when auto-continuing (optional; uses default if null)
 # Sub-Agent Spawning System
 # Enable this agent to spawn and manage child agents in parallel.
-# See https://github.com/Dark-Alex-17/coyote/wiki/Agents for detailed documentation.
+# See docs/AGENTS.md for detailed documentation.
 can_spawn_agents: false          # Enable the agent to spawn child agents
 max_concurrent_agents: 4         # Maximum number of agents that can run simultaneously
 max_agent_depth: 3               # Maximum nesting depth for sub-agents (prevents runaway spawning)
@@ -37,21 +35,11 @@ summarization_model: null        # Model to use for summarizing sub-agent output
 summarization_threshold: 4000    # Character threshold above which sub-agent output is summarized before returning to parent
 escalation_timeout: 300          # Seconds a sub-agent waits for a user interaction response before timing out (default: 5 minutes)
 mcp_servers:                     # Optional list of MCP servers that the agent utilizes
-  - github                       # Corresponds to the name of an MCP server in the `<coyote-config-dir>/functions/mcp.json` file
+  - github                       # Corresponds to the name of an MCP server in the `<loki-config-dir>/functions/mcp.json` file
 global_tools:                    # Optional list of additional global tools to enable for the agent; i.e. not tools specific to the agent
   - web_search
   - fs
   - python
-skills_enabled: true             # Master switch for skills in this agent (default: inherit from global).
-                                 # Skills also require `function_calling_support: true` in the global config.
-enabled_skills:                  # Optional list of skills available when this agent runs.
-                                 # Must be a subset of global `visible_skills`. Omit to inherit the global default.
-  - git-master
-  - ai-slop-remover
-inject_skill_instructions: true  # Inject a short hint pointing the model at `skill__list` when skills are enabled
-                                 # (default: true). Suppressed automatically when no skills are available.
-skill_instructions: null         # Custom text for the skill hint (optional; uses built-in default if null)
-
 dynamic_instructions: false      # Whether to use dynamic instructions for the agent; if false, static instructions are used
 instructions: |                  # Static instructions for the agent; ignored if dynamic instructions are used
   You are a AI agent designed to demonstrate agent capabilities.
@@ -90,10 +78,10 @@ conversation_starters:          # Optional conversation starters for the agent
   - What is the best way to exercise?
   - How do I manage my time effectively?
 documents:                     # Optional documents to load for the agent
-  - git:/some/repo             # Explicitly tell Coyote to use the 'git' document loader using an absolute path
-  - pdf:some-pdf-file.pdf      # Explicitly tell Coyote to use the 'pdf' document loader using a relative path
+  - git:/some/repo             # Explicitly tell Loki to use the 'git' document loader using an absolute path
+  - pdf:some-pdf-file.pdf      # Explicitly tell Loki to use the 'pdf' document loader using a relative path
   - https://some-website.com/some-page
-  - some-file.pdf              # File with relative path to the <coyote-config-dir>/agents/<agent-name> directory; i.e. file in the same directory as this config file
+  - some-file.pdf              # File with relative path to the <loki-config-dir>/agents/<agent-name> directory; i.e. file in the same directory as this config file
   - ~/some-file.txt            # File in the user's home directory
   - /absolute/path/to/some-file.md  # File with absolute path
   - /absolute/path/**/NAME.txt    # Find all NAME.txt files in the specified directory and all its subdirectories

config.example.yaml

@@ -18,78 +18,31 @@ agent_session: null              # Set a session to use when starting an agent (
 
 # ---- Appearance ----
 highlight: true                  # Controls syntax highlighting
-light_theme: false               # Activates a light color theme when true. env: COYOTE_LIGHT_THEME
+light_theme: false               # Activates a light color theme when true. env: LOKI_LIGHT_THEME
 
 # ---- Miscellaneous ----
-user_agent: null                 # Set User-Agent HTTP header, use `auto` for coyote/<current-version>
+user_agent: null                 # Set User-Agent HTTP header, use `auto` for loki/<current-version>
 save_shell_history: true         # Whether to save shell execution command to the history file
 sync_models_url: >               # URL to sync model changes from
-  https://raw.githubusercontent.com/Dark-Alex-17/coyote/refs/heads/main/models.yaml
+  https://raw.githubusercontent.com/Dark-Alex-17/loki/refs/heads/main/models.yaml
 
 # ---- REPL Prompt ----
-# Custom REPL left/right prompts; see the [REPL Prompt Documentation](https://github.com/Dark-Alex-17/coyote/wiki/REPL-Prompt) for more information
+# Custom REPL left/right prompts; see the [REPL Prompt Documentation](./docs/REPL-PROMPT.md) for more information
 left_prompt:
   '{color.red}{model}){color.green}{?session {?agent {agent}>}{session}{?role /}}{!session {?agent {agent}>}}{role}{?rag @{rag}}{color.cyan}{?session )}{!session >}{color.reset} '
 right_prompt:
   '{color.purple}{?session {?consume_tokens {consume_tokens}({consume_percent}%)}{!consume_tokens {consume_tokens}}}{color.reset}'
 
 # ---- Vault ----
-# See the [Vault documentation](https://github.com/Dark-Alex-17/coyote/wiki/Vault) for more information on the Coyote vault.
-#
-# The secrets_provider tells Coyote where to read and write secrets referenced via {{SECRET_NAME}} syntax.
-#
-# Shorthand: set vault_password_file to enable the local provider with that password file.
-vault_password_file: null        # Path to a file containing the password for the Coyote vault (cannot be a secret template)
-#
-# Explicit: set secrets_provider to one of the supported types below. When secrets_provider is set,
-# vault_password_file is ignored. Note: secrets_provider itself cannot use {{SECRET}} template syntax.
-# The vault must be initialized before any secrets can be resolved.
-#
-# Local (same as the shorthand above):
-# secrets_provider:
-#   type: local
-#   password_file: ~/.coyote_password
-#
-# AWS Secrets Manager (requires an authenticated AWS CLI; see `aws sso login` or `aws configure`):
-# secrets_provider:
-#   type: aws_secrets_manager
-#   aws_profile: default
-#   aws_region: us-east-1
-#
-# GCP Secret Manager (requires `gcloud auth application-default login`):
-# secrets_provider:
-#   type: gcp_secret_manager
-#   gcp_project_id: my-project-id
-#
-# Azure Key Vault (requires `az login`):
-# secrets_provider:
-#   type: azure_key_vault
-#   vault_name: my-vault-name
-#
-# gopass (requires the `gopass` CLI to be installed and initialized):
-# secrets_provider:
-#   type: gopass
-#   store: my-store              # Optional; omit to use the default store
-#
-# 1Password (requires the `op` CLI to be installed and signed in via `op signin`):
-# secrets_provider:
-#   type: one_password
-#   vault: Production            # Optional; omit to use the default vault
-#   account: my.1password.com    # Optional; omit to use the default account
+# See the [Vault documentation](./docs/VAULT.md) for more information on the Loki vault
+vault_password_file: null        # Path to a file containing the password for the Loki vault (cannot be a secret template)
 
 # ---- Function Calling ----
-# See the [Tools documentation](https://github.com/Dark-Alex-17/coyote/wiki/Tools) for more details
-function_calling_support: true           # Enables or disables function calling (Globally).
+# See the [Tools documentation](./docs/function-calling/TOOLS.md) for more details
+function_calling: true           # Enables or disables function calling (Globally).
 mapping_tools:                   # Alias for a tool or toolset
   fs: 'fs_cat,fs_ls,fs_mkdir,fs_rm,fs_write,fs_read,fs_glob,fs_grep'
-enabled_tools: null              # Which tools to enable by default.
-                                 # Accepts either a YAML list or a comma-separated string. Use 'all' to enable everything.
-                                 # Example (list form):
-                                 #   enabled_tools:
-                                 #     - fs
-                                 #     - web_search_coyote
-                                 # Example (comma-separated form):
-                                 #   enabled_tools: fs,web_search_coyote
+enabled_tools: null              # Which tools to enable by default. (e.g. 'fs,web_search_loki')
 visible_tools:                   # Which tools are visible to be compiled (and are thus able to be defined in 'enabled_tools')
 #  - demo_py.py
 #  - demo_sh.sh
@@ -111,64 +64,25 @@ visible_tools:                   # Which tools are visible to be compiled (and a
 #  - get_current_weather.py
 #  - get_current_weather.ts
   - get_current_weather.sh
+  - query_jira_issues.sh
 #  - search_arxiv.sh
 #  - search_wikipedia.sh
 #  - search_wolframalpha.sh
 #  - send_mail.sh
 #  - send_twilio.sh
-#  - web_search_coyote.sh
+#  - web_search_loki.sh
 #  - web_search_perplexity.sh
 #  - web_search_tavily.sh
 
 # ---- MCP Servers ----
-# See the [MCP Servers documentation](https://github.com/Dark-Alex-17/coyote/wiki/MCP-Servers) for more details
+# See the [MCP Servers documentation](./docs/MCP-SERVERS.md) for more details
 mcp_server_support: true         # Enables or disables MCP servers (globally).
 mapping_mcp_servers:             # Alias for an MCP server or set of servers
   git: github,gitmcp
-enabled_mcp_servers: null        # Which MCP servers to enable by default.
-                                 # Accepts either a YAML list or a comma-separated string. Use 'all' to enable everything.
-                                 # Example (list form):
-                                 #   enabled_mcp_servers:
-                                 #     - github
-                                 #     - slack
-                                 # Example (comma-separated form):
-                                 #   enabled_mcp_servers: github,slack,ddg-search
-
-# ---- Skills ----
-# Skills are modular knowledge or capability packs the LLM can load and unload mid-conversation.
-# See the [Skills documentation](https://github.com/Dark-Alex-17/coyote/wiki/Skills) for more details.
-skills_enabled: true              # Master switch. Set to false to hide all skill management tools from the model.
-                                  # Skills also require `function_calling_support: true` above to work at all.
-visible_skills:                   # The universe of skills allowed to be enabled in any context. Omit (null) for "all installed".
-  - ai-slop-remover
-  - code-review
-  - frontend-ui-ux
-  - git-master
-enabled_skills: null              # Which skills are available by default (no role/agent/session active). null = all visible.
-                                  # Accepts either a YAML list or a comma-separated string.
-                                  # Example (list form):
-                                  #   enabled_skills:
-                                  #     - git-master
-                                  #     - ai-slop-remover
-                                  # Example (comma-separated form):
-                                  #   enabled_skills: git-master,ai-slop-remover
-inject_skill_instructions: true   # Inject a short hint pointing the model at `skill__list` when skills are enabled in
-                                  # this context. Only injected if `function_calling_support`, `skills_enabled`, and the
-                                  # effective enabled skill set is non-empty (default: true).
-skill_instructions: null          # Custom text used for the skill hint when injected. If null, uses built-in default.
-
-# ---- Auto-Continue (Todo System) ----
-# The auto-continue system provides built-in task tracking for improved reliability.
-# When enabled, the model can create todo lists and the system will automatically
-# prompt it to continue when incomplete tasks remain.
-# See the [Todo System documentation](https://github.com/Dark-Alex-17/coyote/wiki/TODO-System) for more information
-auto_continue: false              # Enable automatic continuation when incomplete todos remain (default: false)
-max_auto_continues: 10            # Maximum number of automatic continuations before stopping (default: 10)
-inject_todo_instructions: true    # Inject default todo usage instructions into the system prompt (default: true)
-continuation_prompt: null         # Custom prompt used when auto-continuing. If null, uses built-in default
+enabled_mcp_servers: null        # Which MCP servers to enable by default (e.g. 'github,slack,ddg-search')
 
 # ---- Session ----
-# See the [Session documentation](https://github.com/Dark-Alex-17/coyote/wiki/Sessions) for more information
+# See the [Session documentation](./docs/SESSIONS.md) for more information
 save_session: null               # Controls the persistence of the session. If true, auto save; if false, don't auto-save save; if null, ask the user what to do
 compression_threshold: 4000      # Compress the session when the token count reaches or exceeds this threshold
 summarization_prompt: >          # The text prompt used for creating a concise summary of session message
@@ -177,9 +91,9 @@ summary_context_prompt: >        # The text prompt used for including the summar
   'This is a summary of the chat history as a recap: '
 
 # ---- RAG ----
-# See the [RAG Docs](https://github.com/Dark-Alex-17/coyote/wiki/RAG) for more details.
+# See the [RAG Docs](./docs/RAG.md) for more details.
 rag_embedding_model: null        # Specifies the embedding model used for context retrieval
-rag_reranker_model: null         # Specifies the reranker model used for sorting retrieved documents; Coyote uses Reciprocal Rank Fusion by default
+rag_reranker_model: null         # Specifies the reranker model used for sorting retrieved documents; Loki uses Reciprocal Rank Fusion by default
 rag_top_k: 5                     # Specifies the number of documents to retrieve for answering queries
 rag_chunk_size: null             # Defines the size of chunks for document processing in characters
 rag_chunk_overlap: null          # Defines the overlap between chunks
@@ -218,12 +132,12 @@ document_loaders:
   docx: 'pandoc --to plain $1'                                                          # Use pandoc to convert a .docx file to text
   # (see https://pandoc.org for details on how to install pandoc)
   jina: 'curl -fsSL https://r.jina.ai/$1 -H "Authorization: Bearer {{JINA_API_KEY}}'    # Use Jina to translate a website into text;
-  # Requires a Jina API key to be added to the Coyote vault
+  # Requires a Jina API key to be added to the Loki vault
   git: >                                                                                # Use yek to load a git repository into the knowledgebase (https://github.com/bodo-run/yek)
     sh -c "yek $1 --json | jq 'map({ path: .filename, contents: .content })'"
 
 # ---- Clients ----
-# See the [Clients documentation](https://github.com/Dark-Alex-17/coyote/wiki/Clients) for more details
+# See the [Clients documentation](./docs/clients/CLIENTS.md) for more details
 clients:
   # All clients have the following configuration:
   # - type: xxxx
@@ -254,14 +168,14 @@ clients:
   # See https://platform.openai.com/docs/quickstart
   - type: openai
     api_base: https://api.openai.com/v1               # Optional
-    api_key: '{{OPENAI_API_KEY}}'                     # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{OPENAI_API_KEY}}'                     # You can either hard-code or inject secrets from the Loki vault
     organization_id: org-xxx                          # Optional
 
   # For any platform compatible with OpenAI's API
   - type: openai-compatible
     name: ollama
     api_base: http://localhost:11434/v1
-    api_key: '{{OLLAMA_API_KEY}}'                     # Optional; You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{OLLAMA_API_KEY}}'                     # Optional; You can either hard-code or inject secrets from the Loki vault
     models:
       - name: deepseek-r1
         max_input_tokens: 131072
@@ -279,9 +193,9 @@ clients:
   # See https://ai.google.dev/docs
   - type: gemini
     api_base: https://generativelanguage.googleapis.com/v1beta
-    api_key: '{{GEMINI_API_KEY}}'                       # You can either hard-code or inject secrets from the Coyote vault
-    auth: null                                          # When set to 'oauth', Coyote will use OAuth instead of an API key
-                                                        # Authenticate with `coyote --authenticate` or `.authenticate` in the REPL
+    api_key: '{{GEMINI_API_KEY}}'                       # You can either hard-code or inject secrets from the Loki vault
+    auth: null                                          # When set to 'oauth', Loki will use OAuth instead of an API key
+                                                        # Authenticate with `loki --authenticate` or `.authenticate` in the REPL
     patch:
       chat_completions:
         '.*':
@@ -299,49 +213,49 @@ clients:
   # See https://docs.anthropic.com/claude/reference/getting-started-with-the-api
   - type: claude
     api_base: https://api.anthropic.com/v1              # Optional
-    api_key: '{{ANTHROPIC_API_KEY}}'                    # You can either hard-code or inject secrets from the Coyote vault
-    auth: null                                          # When set to 'oauth', Coyote will use OAuth instead of an API key
-                                                        # Authenticate with `coyote --authenticate` or `.authenticate` in the REPL
+    api_key: '{{ANTHROPIC_API_KEY}}'                    # You can either hard-code or inject secrets from the Loki vault
+    auth: null                                          # When set to 'oauth', Loki will use OAuth instead of an API key
+                                                        # Authenticate with `loki --authenticate` or `.authenticate` in the REPL
 
   # See https://docs.mistral.ai/
   - type: openai-compatible
     name: mistral
     api_base: https://api.mistral.ai/v1
-    api_key: '{{MISTRAL_API_KEY}}'                      # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{MISTRAL_API_KEY}}'                      # You can either hard-code or inject secrets from the Loki vault
 
   # See https://docs.x.ai/docs
   - type: openai-compatible
     name: xai
     api_base: https://api.x.ai/v1
-    api_key: '{{XAI_API_KEY}}'                          # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{XAI_API_KEY}}'                          # You can either hard-code or inject secrets from the Loki vault
 
   # See https://docs.ai21.com/docs/overview
   - type: openai-compatible
     name: ai12
     api_base: https://api.ai21.com/studio/v1
-    api_key: '{{AI21_API_KEY}}'                         # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{AI21_API_KEY}}'                         # You can either hard-code or inject secrets from the Loki vault
 
   # See https://docs.cohere.com/docs/the-cohere-platform
   - type: cohere
     api_base: https://api.cohere.ai/v2                  # Optional
-    api_key: '{{COHERE_API_KEY}}'                       # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{COHERE_API_KEY}}'                       # You can either hard-code or inject secrets from the Loki vault
 
   # See https://docs.perplexity.ai/getting-started/overview
   - type: openai-compatible
     name: perplexity
     api_base: https://api.perplexity.ai
-    api_key: '{{PERPLEXITY_API_KEY}}'                   # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{PERPLEXITY_API_KEY}}'                   # You can either hard-code or inject secrets from the Loki vault
 
   # See https://console.groq.com/docs/quickstart
   - type: openai-compatible
     name: groq
     api_base: https://api.groq.com/openai/v1
-    api_key: '{{GROQ_API_KEY}}'                         # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{GROQ_API_KEY}}'                         # You can either hard-code or inject secrets from the Loki vault
 
   # See https://learn.microsoft.com/en-us/azure/ai-services/openai/chatgpt-quickstart
   - type: azure-openai
     api_base: https://{RESOURCE}.openai.azure.com
-    api_key: '{{AZURE_OPENAI_API_KEY}}'                 # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{AZURE_OPENAI_API_KEY}}'                 # You can either hard-code or inject secrets from the Loki vault
     models:
       - name: gpt-4o                                    # Model deployment name
         max_input_tokens: 128000
@@ -372,8 +286,8 @@ clients:
 
   # See https://docs.aws.amazon.com/bedrock/latest/userguide/
   - type: bedrock
-    access_key_id: '{{AWS_ACCESS_KEY_ID}}'              # You can either hard-code or inject secrets from the Coyote vault
-    secret_access_key: '{{AWS_SECRET_ACCESS_KEY}}'      # You can either hard-code or inject secrets from the Coyote vault
+    access_key_id: '{{AWS_ACCESS_KEY_ID}}'              # You can either hard-code or inject secrets from the Loki vault
+    secret_access_key: '{{AWS_SECRET_ACCESS_KEY}}'      # You can either hard-code or inject secrets from the Loki vault
     region: xxx
     session_token: xxx                                  # Optional, only needed for temporary credentials
 
@@ -381,67 +295,67 @@ clients:
   - type: openai-compatible
     name: cloudflare
     api_base: https://api.cloudflare.com/client/v4/accounts/{ACCOUNT_ID}/ai/v1
-    api_key: '{{CLOUDFLARE_API_KEY}}'                    # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{CLOUDFLARE_API_KEY}}'                    # You can either hard-code or inject secrets from the Loki vault
 
   # See https://cloud.baidu.com/doc/WENXINWORKSHOP/index.html
   - type: openai-compatible
     name: ernie
     api_base: https://qianfan.baidubce.com/v2
-    api_key: '{{BAIDU_API_KEY}}'                        # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{BAIDU_API_KEY}}'                        # You can either hard-code or inject secrets from the Loki vault
 
   # See https://dashscope.aliyun.com/
   - type: openai-compatible
     name: qianwen
     api_base: https://dashscope.aliyuncs.com/compatible-mode/v1
-    api_key: '{{ALIYUN_API_KEY}}'                       # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{ALIYUN_API_KEY}}'                       # You can either hard-code or inject secrets from the Loki vault
 
   # See https://cloud.tencent.com/product/hunyuan
   - type: openai-compatible
     name: hunyuan
     api_base: https://api.hunyuan.cloud.tencent.com/v1
-    api_key: '{{TENCENT_API_KEY}}'                      # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{TENCENT_API_KEY}}'                      # You can either hard-code or inject secrets from the Loki vault
 
   # See https://platform.moonshot.cn/docs/intro
   - type: openai-compatible
     name: moonshot
     api_base: https://api.moonshot.cn/v1
-    api_key: '{{MOONSHOT_API_KEY}}'                     # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{MOONSHOT_API_KEY}}'                     # You can either hard-code or inject secrets from the Loki vault
 
   # See https://platform.deepseek.com/api-docs/
   - type: openai-compatible
     name: deepseek
     api_base: https://api.deepseek.com
-    api_key: '{{DEEPSEEK_API_KEY}}'                     # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{DEEPSEEK_API_KEY}}'                     # You can either hard-code or inject secrets from the Loki vault
 
   # See https://open.bigmodel.cn/dev/howuse/introduction
   - type: openai-compatible
     name: zhipuai
     api_base: https://open.bigmodel.cn/api/paas/v4
-    api_key: '{{ZHIPUAI_API_KEY}}'                      # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{ZHIPUAI_API_KEY}}'                      # You can either hard-code or inject secrets from the Loki vault
 
   # See https://platform.minimaxi.com/document/Fast%20access
   - type: openai-compatible
     name: minimax
     api_base: https://api.minimax.chat/v1
-    api_key: '{{MINIMAX_API_KEY}}'                      # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{MINIMAX_API_KEY}}'                      # You can either hard-code or inject secrets from the Loki vault
 
   # See https://openrouter.ai/docs#quick-start
   - type: openai-compatible
     name: openrouter
     api_base: https://openrouter.ai/api/v1
-    api_key: '{{OPENROUTER_API_KEY}}'                   # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{OPENROUTER_API_KEY}}'                   # You can either hard-code or inject secrets from the Loki vault
 
   # See https://github.com/marketplace/models
   - type: openai-compatible
     name: github
     api_base: https://models.inference.ai.azure.com
-    api_key: '{{GITHUB_API_KEY}}'                       # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{GITHUB_API_KEY}}'                       # You can either hard-code or inject secrets from the Loki vault
 
   # See https://deepinfra.com/docs
   - type: openai-compatible
     name: deepinfra
     api_base: https://api.deepinfra.com/v1/openai
-    api_key: '{{DEEPINFRA_API_KEY}}'                    # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{DEEPINFRA_API_KEY}}'                    # You can either hard-code or inject secrets from the Loki vault
 
 
   # ----- RAG dedicated -----
@@ -450,10 +364,10 @@ clients:
   - type: openai-compatible
     name: jina
     api_base: https://api.jina.ai/v1
-    api_key: '{{JINA_API_KEY}}'                         # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{JINA_API_KEY}}'                         # You can either hard-code or inject secrets from the Loki vault
 
   # See https://docs.voyageai.com/docs/introduction
   - type: openai-compatible
     name: voyageai
     api_base: https://api.voyageai.com/v1
-    api_key: '{{VOYAGEAI_API_KEY}}'                     # You can either hard-code or inject secrets from the Coyote vault
+    api_key: '{{VOYAGEAI_API_KEY}}'                     # You can either hard-code or inject secrets from the Loki vault

config.role.example.md

@@ -1,38 +1,12 @@
 ---
-############################################
-## Everything in this section is optional ##
-############################################
-
-# Role Configuration
+# Everything in this section is optional
 name: <role-name>                     # The name of the role
 model: openai:gpt-4o                  # The model to use for this role
 temperature: 0.2                      # The temperature to use for this role when querying the model
 top_p: 0                              # The top_p to use for this role when querying the model
-enabled_tools:                        # Tools to enable for this role. Accepts a YAML list (preferred)
-  - fs_ls                             # or a comma-separated string (e.g. `enabled_tools: fs_ls,fs_cat`).
-  - fs_cat                            # Use `all` to enable every visible tool.
-enabled_mcp_servers:                  # MCP servers to enable for this role. Accepts a YAML list (preferred)
-  - github                            # or a comma-separated string (e.g. `enabled_mcp_servers: github,gitmcp`).
-  - gitmcp                            # Use `all` to enable every configured MCP server.
-skills_enabled: true                  # Master switch for skills in this role (default: inherit from global).
-                                      # Skills also require `function_calling_support: true` in the global config.
-enabled_skills:                       # Skills available when this role is active. Accepts a YAML list (preferred)
-  - git-master                        # or a comma-separated string (e.g. `enabled_skills: git-master,ai-slop-remover`).
-  - ai-slop-remover                   # Must be a subset of global `visible_skills`. Omit to inherit the global default.
-inject_skill_instructions: true       # Inject a short hint pointing the model at `skill__list` when skills are enabled 
-                                      # (default: true). Suppressed automatically when no skills are available.
-skill_instructions: null              # Custom text for the skill hint (optional; uses built-in default if null)
-
+enabled_tools: fs_ls,fs_cat           # A comma-separated list of tools to enable for this role
+enabled_mcp_servers: github,gitmcp    # A comma-separated list of MCP servers to enable for this role
 prompt: null                          # A custom prompt to use for this role that will immediately query
                                       # the model for output instead of using the instructions below
-# Auto-Continue (Todo System)
-# The auto-continue system provides built-in task tracking for improved reliability.
-# When enabled, the model can create todo lists and the system will automatically
-# prompt it to continue when incomplete tasks remain.
-# See the [Todo System documentation](https://github.com/Dark-Alex-17/coyote/wiki/TODO-System) for more information
-auto_continue: false                  # Enable automatic continuation when incomplete todos remain (default: false)
-max_auto_continues: 10                # Maximum number of automatic continuations before stopping (default: 10)
-inject_todo_instructions: true        # Inject default todo tool usage instructions into the system prompt (default: true)
-continuation_prompt: null             # Custom prompt used when auto-continuing. If null, uses built-in default
 ---
 You are an expert at doing things. This is where you write the instructions for the role.

deployment/homebrew/coyote.rb.template

@@ -1,23 +0,0 @@
-# Documentation: https://docs.brew.sh/Formula-Cookbook
-#                https://rubydoc.brew.sh/Formula
-class Coyote < Formula
-  desc "All-in-one, batteries included LLM CLI tool"
-  homepage "https://github.com/Dark-Alex-17/coyote"
-  if OS.mac? and Hardware::CPU.arm?
-    url "https://github.com/Dark-Alex-17/coyote/releases/download/v$version/coyote-aarch64-apple-darwin.tar.gz"
-    sha256 "$hash_mac_arm"
-  elsif OS.mac? and Hardware::CPU.intel?
-    url "https://github.com/Dark-Alex-17/coyote/releases/download/v$version/coyote-x86_64-apple-darwin.tar.gz"
-    sha256 "$hash_mac"
-  else
-    url "https://github.com/Dark-Alex-17/coyote/releases/download/v$version/coyote-x86_64-unknown-linux-musl.tar.gz"
-    sha256 "$hash_linux"
-  end
-  version "$version"
-  license "MIT"
-
-  def install
-    bin.install "coyote"
-    ohai "You're done! Get started with \"coyote --help\""
-  end
-end

deployment/homebrew/loki.rb.template

@@ -0,0 +1,23 @@
+# Documentation: https://docs.brew.sh/Formula-Cookbook
+#                https://rubydoc.brew.sh/Formula
+class Loki < Formula
+  desc "All-in-one, batteries included LLM CLI tool"
+  homepage "https://github.com/Dark-Alex-17/loki"
+  if OS.mac? and Hardware::CPU.arm?
+    url "https://github.com/Dark-Alex-17/loki/releases/download/v$version/loki-aarch64-apple-darwin.tar.gz"
+    sha256 "$hash_mac_arm"
+  elsif OS.mac? and Hardware::CPU.intel?
+    url "https://github.com/Dark-Alex-17/loki/releases/download/v$version/loki-x86_64-apple-darwin.tar.gz"
+    sha256 "$hash_mac"
+  else
+    url "https://github.com/Dark-Alex-17/loki/releases/download/v$version/loki-x86_64-unknown-linux-musl.tar.gz"
+    sha256 "$hash_linux"
+  end
+  version "$version"
+  license "MIT"
+
+  def install
+    bin.install "loki"
+    ohai "You're done! Get started with \"loki --help\""
+  end
+end

graph.example.yaml

@@ -1,466 +0,0 @@
-# Graph-based agent definition (full-featured reference)
-# Location: <coyote-config-dir>/agents/<agent-name>/graph.yaml
-#
-# A graph agent is defined by this file alone. An agent directory contains
-# either a config.yaml (a normal LLM-loop agent) or a graph.yaml (a graph
-# agent), never both. The presence of graph.yaml is what makes the agent
-# a graph agent.
-#
-# This file is a reference: it documents every available field, themed
-# around a deep web research workflow with parallel retrieval. It is not
-# a runnable agent as-is. The `agent:`, `script:`, and `documents:` values
-# point at things that would need to exist for a real agent. For a real,
-# runnable deep-research graph agent, see assets/agents/deep-research/.
-#
-# Full documentation:
-#   https://github.com/Dark-Alex-17/coyote/wiki/Graph-Agents
-
-# ---------------------------------------------------------------------------
-# Identity
-# ---------------------------------------------------------------------------
-name: deep-research-example        # Agent name (should match the directory name)
-description: |                     # Free-form prose describing the workflow
-  A reference workflow: triage a research request, retrieve local
-  context, branch on a script decision, run either a sub-agent or an
-  LLM research step, then gate the result behind human approval.
-version: "1.0"                     # Graph schema version. Only "1.0" is accepted.
-
-# ---------------------------------------------------------------------------
-# Agent-level config (all optional)
-# The same knobs a normal agent's config.yaml carries. In a graph agent they
-# live here instead of in a config.yaml.
-# ---------------------------------------------------------------------------
-model: claude:claude-sonnet-4-6    # Default model for `llm` nodes that don't override it
-temperature: 0.0                   # Default sampling temperature for `llm` nodes
-top_p: null                        # Default sampling top-p for `llm` nodes
-
-global_tools:                      # Tool universe an `llm` node's `tools:` whitelist draws from
-  - web_search_coyote.sh
-  - fetch_url_via_curl.sh
-
-mcp_servers:                       # MCP servers an `llm` node may reference via `mcp:<server>`
-  - ddg-search
-
-# ---------------------------------------------------------------------------
-# Skills policy (optional)
-# Skills only attach to `llm` nodes inside a graph. Both fields are optional.
-#
-#   skills_enabled:  master switch for skills across every `llm` node in the
-#                    graph. false here turns skills off entirely, regardless of
-#                    per-node settings. Omitting it inherits the agent / global
-#                    cascade (default true).
-#   enabled_skills:  the *universe* of skill names any `llm` node in this graph
-#                    may reference in its own `enabled_skills`. The validator
-#                    rejects per-node entries outside this list at load time.
-#                    Omit to inherit the agent / global cascade.
-#
-# Per-node usage is documented on the `triage` llm node below. There is no
-# auto-load: the model uses `skill__list` / `skill__load` / `skill__unload` to
-# bring skills in as it needs them, exactly like in normal-agent contexts.
-# ---------------------------------------------------------------------------
-skills_enabled: true
-enabled_skills:
-  - code-review
-  - git-master
-  - ai-slop-remover
-inject_skill_instructions: true   # Inject a hint pointing the model at `skill__list`. Defaults to true; suppressed
-                                  # automatically when no skills are available.
-skill_instructions: null          # Custom text for the skill hint (optional; uses the built-in default if omitted).
-
-conversation_starters:             # Suggested prompts surfaced in the UI
-  - "Research the current state of WebAssembly outside the browser"
-
-# ---------------------------------------------------------------------------
-# Agent variables (optional)
-# Declared the same way as a normal agent's config.yaml `variables:` block.
-# Each variable becomes available to:
-#   - LLM nodes via the template form `{{name}}` once seeded into state
-#     (see initial_state below).
-#   - Script nodes via the env var `LLM_AGENT_VAR_<UPPER_NAME>`.
-# Values may be overridden at runtime with
-#   `coyote -a <agent> --agent-variable <name> <value> "..."`.
-# ---------------------------------------------------------------------------
-variables:
-  - name: project_dir
-    description: |
-      Absolute path to the project directory.
-    default: "."
-
-# ---------------------------------------------------------------------------
-# Execution settings (all optional)
-# ---------------------------------------------------------------------------
-settings:
-  max_loop_iterations: 100   # Per-node visit cap. If one node id is entered more
-                             # than this many times, execution aborts. Default 100.
-  timeout: 600               # Optional wall-clock cap (seconds) on the whole run,
-                             # checked between node transitions.
-  log_state_snapshots: true  # Log state before each node (debug/trace). Default true.
-  validate_before_run: true  # Run the graph validator at startup. Default true.
-  max_concurrency: 4         # Cap on simultaneously running branches in any
-                             # super-step (static fan-out OR a `map` node).
-                             # Default 4. Per-`map` overrides this. See Parallel
-                             # Execution below.
-
-# ---------------------------------------------------------------------------
-# Reducers (optional, required whenever two parallel branches write the same
-# state key in the same super-step; otherwise the validator errors at load).
-#
-# A reducer says how two values for the same key get merged. Built-ins:
-#   append    list += [value]              (single value appended to a list)
-#   extend    list += value (a list)       (list-of-lists flattened by one level)
-#   concat    "a\nb"                       (string join with newline separator)
-#   sum       a + b                        (numeric add; ints stay ints)
-#   max       max(a, b)
-#   min       min(a, b)
-#   merge     {**a, **b}                   (dict union, RHS wins on key collision)
-#   overwrite last-write-wins              (explicit opt-in; B's value replaces A's)
-#
-# Keys not listed here have an implicit "single writer per super-step" rule:
-# the validator rejects any graph where two parallel branches both write a
-# key with no reducer.
-# ---------------------------------------------------------------------------
-reducers:
-  sources: append             # The diamond below writes `sources` from both
-                              # branches; append accumulates them into a list.
-  context: concat             # Each branch contributes prose; concat joins them.
-
-# ---------------------------------------------------------------------------
-# Seed state (optional)
-# Values placed into graph state before any node runs; reference anywhere via
-# {{key}}.
-#
-# Note: `initial_prompt` is seeded automatically by Coyote with the
-# caller's prompt. So there's no need to set it here.
-# ---------------------------------------------------------------------------
-initial_state:
-  audience: "general reader"
-  # Seed an empty default for any key that a strict field (a node prompt /
-  # instructions / question / End output) references but that is only set on
-  # some paths. `refinement` is set only if the `refine` input node runs;
-  # seeding it "" keeps `finalize`'s strict prompt from failing on the
-  # approve-directly path.
-  refinement: ""
-
-# ---------------------------------------------------------------------------
-# Entry point
-# ---------------------------------------------------------------------------
-start: triage                # ID of the first node to run (must exist in `nodes`)
-
-# ---------------------------------------------------------------------------
-# Nodes
-# Each node is keyed by its id. The `id:` inside a node must match its key
-# (it may also be omitted and thus Coyote fills it in from the key).
-#
-# Node types: agent | script | approval | input | llm | rag | map | end
-# ---------------------------------------------------------------------------
-nodes:
-
-  # --- llm node -----------------------------------------------------------
-  # A one-shot LLM call (with an optional bounded tool-call loop). Runs in a
-  # fresh isolated context. Tools are strictly opt-in (see `tools`).
-  triage:
-    id: triage
-    type: llm
-    description: Classify the research request and extract its topic.
-    instructions: |            # Optional system prompt (templated against state)
-      You triage research requests for a {{audience}} audience.
-    prompt: |                  # Required user prompt (templated against state)
-      Classify this request and extract the core research topic:
-      {{initial_prompt}}
-    tools: []                  # Tool whitelist. Omitted or [] = no tools at all.
-                               # A list narrows to exactly those entries.
-    # --- Skills on llm nodes (optional) ------------------------------------
-    # `enabled_skills` narrows what this node's model can see / load via the
-    # built-in `skill__list` / `skill__load` / `skill__unload` meta-tools.
-    # Must be a subset of the graph-level `enabled_skills` (the validator
-    # catches violations at load time). `skills_enabled: false` would
-    # disable skills entirely for this node (no meta-tools exposed).
-    # Nothing is auto-loaded: the model decides when to load a skill.
-    skills_enabled: true       # Whether skills are enabled on this llm node; defaults to 'true'
-    enabled_skills:
-      - ai-slop-remover
-    inject_skill_instructions: true   # Override skill-hint injection for just this node. Falls back to
-                                      # agent/graph/global default when omitted.
-    skill_instructions: null          # Per-node skill-hint text override; uses the built-in default when omitted.
-    output_schema:             # Optional JSON Schema. The output is parsed to JSON
-      type: object             # and its top-level object keys auto-merge into state
-      properties:              # (so `topic` / `needs_deep_dive` become {{topic}} etc).
-        topic: { type: string }
-        needs_deep_dive: { type: boolean }
-      required: [topic, needs_deep_dive]
-    state_updates:             # {{output}} = this node's result (here, the parsed object)
-      triage_result: "{{output}}"
-    # --- Polymorphic `next` -----------------------------------------------
-    # A single string runs the next node sequentially (e.g. `next: retrieve`).
-    # A list runs all listed nodes in parallel as one BSP super-step
-    # (for more info on BSP, see https://en.wikipedia.org/wiki/Bulk_synchronous_parallel).
-    # Their writes are merged via `reducers:` at the join. Branches converge
-    # implicitly when they all route to the same downstream node (here,
-    # `synthesize`). See the diamond:
-    #
-    #          triage
-    #          /     \
-    #     retrieve  web_search   (run concurrently)
-    #          \     /
-    #         synthesize         (join; fires once after both finish)
-    next: [retrieve, web_search]
-
-  # --- rag node (parallel branch 1 of the diamond) ------------------------
-  # Hybrid (vector + keyword) retrieval against a per-node knowledge base.
-  # The knowledge base is built once, at agent load time, into
-  # <agent-dir>/retrieve.yaml (named after this node's id).
-  retrieve:
-    id: retrieve
-    type: rag
-    documents:                 # Required. Files, directories, URLs, loader paths.
-      - ./knowledge/           #   relative paths resolve against the agent directory
-      - https://example.com/reference
-    query: "{{topic}}"         # Retrieval query (templated). Default: {{initial_prompt}}.
-    top_k: 5                   # Chunks to retrieve. Default = the KB's own top_k.
-    timeout: 120               # Retrieval timeout in seconds. Default 120.
-    # Knowledge-base build config (optional; used only when the KB is first
-    # built). When embedding_model + chunk_size + chunk_overlap are all set,
-    # the KB builds with no interactive prompts (works in non-interactive runs).
-    embedding_model: openai:text-embedding-3-small
-    chunk_size: 1000
-    chunk_overlap: 100
-    reranker_model: null       # Optional reranker for hybrid-search results
-    batch_size: 100            # Optional embedding-request batch size
-    state_updates:             # {{output}} = { context: <str>, sources: [<path>, ...] }
-      context: "{{output.context}}"   # writes `context` -> `reducers.context = concat`
-      sources: "{{output.sources}}"   # writes `sources` -> `reducers.sources = append`
-    next: synthesize           # Joins with web_search at `synthesize`.
-
-  # --- llm node (parallel branch 2 of the diamond) ------------------------
-  # Runs concurrently with `retrieve`. Both branches write `context` and
-  # `sources`; the validator confirms both keys have a reducer declared, and
-  # the BSP scheduler merges them at the join.
-  web_search:
-    id: web_search
-    type: llm
-    instructions: "You are a web researcher. Cite every claim."
-    prompt: "Web research: {{topic}}. Return findings and sources."
-    tools:
-      - web_search_coyote
-      - mcp:ddg-search
-    output_schema:
-      type: object
-      properties:
-        context: { type: string }
-        sources:
-          type: array
-          items: { type: string }
-      required: [context, sources]
-    # When `output_schema` is set, top-level keys auto-merge into state, so
-    # `context` and `sources` are produced without needing `state_updates`.
-    next: synthesize           # Joins with retrieve at `synthesize`.
-
-  # --- script node (the diamond's join; also dispatches) -----------------
-  # Runs a .sh / .py / .ts script. The script receives state via the
-  # GRAPH_STATE env var (inline JSON) or GRAPH_STATE_FILE (path to a JSON
-  # file, used when state exceeds 32 KiB). Exactly one is set. It must print
-  # a single JSON object on stdout: keys merge into state, and the reserved
-  # `_next` key (if present) overrides routing.
-  #
-  # The script also receives these env vars (parity with bash tools called
-  # from normal agents):
-  #   GRAPH_STATE / GRAPH_STATE_FILE  state payload (one of the two is set)
-  #   LLM_ROOT_DIR                    coyote config dir
-  #   LLM_PROMPT_UTILS_FILE           path to .shared/prompt-utils.sh
-  #   LLM_AGENT_DATA_DIR              this agent's data directory
-  #   LLM_AGENT_VAR_<NAME>            one per declared `variables:` entry
-  #   PATH                            with coyote's functions bin dir prepended
-  #   CLICOLOR_FORCE / FORCE_COLOR    so child tools emit ANSI colors
-  # The script's working directory is coyote's invocation CWD (not the agent
-  # directory), matching the behavior of bash tools.
-  #
-  # This node fires once: after both `retrieve` and `web_search` finish.
-  # The BSP scheduler dedups the two incoming edges into a single frontier
-  # entry, applies the staged branch writes through the reducers, then runs
-  # this node against the merged state. Inside the script, `context` is the
-  # concatenated text of both branches and `sources` is the combined list.
-  synthesize:
-    id: synthesize
-    type: script
-    script: scripts/synthesize.py  # Path relative to the agent directory
-    timeout: 30                # Seconds. Default 30.
-    state_updates:             # Applied after the stdout JSON is merged
-      decided_for: "{{topic}}"
-    next: summarize            # Default route if the script emits no `_next`
-    fallback: summarize        # Route taken if the script fails (crash / bad JSON)
-    # This script is expected to emit `_next: deep_dive` (or `_next: subjects_map`
-    # to demonstrate the map node below), or no `_next` (then `next` is used).
-    # Targets reached only via the script's dynamic `_next` get an
-    # "unreachable" warning from the validator. This is expected for `_next`-routed
-    # targets.
-
-  # --- agent node ---------------------------------------------------------
-  # Spawns a full Coyote sub-agent and waits for it. The child uses its own
-  # tool stack. Agent nodes have no `tools:` field. No schema hint is
-  # injected even when `output_schema` is set (unlike llm nodes).
-  deep_dive:
-    id: deep_dive
-    type: agent
-    agent: deep-research       # Name of an existing Coyote agent to spawn
-    prompt: |                  # User message sent to the child (templated)
-      Research {{topic}} in depth. Existing context:
-      {{context}}
-    timeout: 600               # Optional wall-clock cap, seconds. Default 300.
-    output_schema:             # Optional. Same extraction as llm nodes
-      type: object
-      properties:
-        summary: { type: string }
-        findings:
-          type: array
-          items: { type: string }
-      required: [summary, findings]
-    state_updates:
-      research: "{{output}}"
-    next: review               # Required for agent nodes
-
-  # --- map node (Dynamic fan-out. Think: LangGraph's `Send` API) ----------------
-  # Spawns one parallel sub-branch per item in `over`. Each sub-branch runs
-  # the node referenced by `branch:` with the item bound to `as:`. Outputs
-  # collect into the array named by `collect_into:`, preserving input order.
-  #
-  # Reach via `synthesize`'s `_next: subjects_map`. The producer is expected
-  # to have written a list at `subjects` (e.g. an upstream LLM node with an
-  # `output_schema` returning {"subjects": ["a", "b", "c"]}).
-  subjects_map:
-    id: subjects_map
-    type: map
-    over: "{{subjects}}"        # Required. List expression resolved from state.
-                                # Empty list is allowed. It means no branches spawn,
-                                # and thus `collect_into` is written as [].
-    as: subject                 # Required. Per-branch state key holding the
-                                # current item. Read with {{subject}} inside
-                                # the branch node's prompt.
-    branch: research_subject    # Required. Node id to invoke per item.
-                                # Must point to an llm | agent | rag | script
-                                # node satisfying the map branch contract:
-                                #   - no `next:` (atomic, joined at map exit)
-                                #   - no `state_updates:` other than via the
-                                #     map's `collect_into` channel
-                                #   - no `output_schema:` (top-level merge
-                                #     would clash with collect_into)
-                                # Validator enforces all three.
-    collect_into: subject_findings  # Required. State key for the array of
-                                    # per-branch outputs, in input order
-                                    # (not spawn-finish order).
-    max_concurrency: 3          # Optional per-map cap. Defaults to
-                                # settings.max_concurrency above.
-    output_key: output          # Optional. State key the branch's output
-                                # appears under. Default "output". Useful
-                                # only if the branch reads its own bound
-                                # name back (rare).
-    next: aggregate_subjects    # Where to go after all sub-branches finish.
-
-  # Branch node for subjects_map. Each invocation receives a different
-  # `subject` in state. The branch is "atomic", meaning it cannot route on
-  # its own; the surrounding `map` joins after all invocations finish.
-  research_subject:
-    id: research_subject
-    type: llm
-    instructions: "Research one subject deeply for a {{audience}} audience."
-    prompt: "Research {{subject}}: pull the key facts and one citation."
-    tools:
-      - web_search_coyote
-    # No `next:`, `state_updates:`, or `output_schema:` here. Map branches
-    # have a strict contract (see `subjects_map.branch` comment).
-
-  # Aggregator that runs after the map joins. Reads the collected list.
-  aggregate_subjects:
-    id: aggregate_subjects
-    type: llm
-    instructions: "Combine N per-subject reports into one cohesive summary."
-    prompt: |
-      Per-subject reports (in original input order):
-      {{subject_findings}}
-    state_updates:
-      research: "{{output}}"
-    next: review
-
-  # --- llm node with a narrowed tool whitelist ----------------------------
-  summarize:
-    id: summarize
-    type: llm
-    instructions: "You write concise research summaries for a {{audience}} audience."
-    prompt: "Summarize the topic {{topic}}, using your tools as needed."
-    tools:                     # Narrow whitelist: exactly these entries, nothing else
-      - web_search_coyote        #   an exact global-tool / custom-tool name
-      - mcp:ddg-search         #   `mcp:<server>` includes that server's functions
-    model: claude:claude-haiku-4-5  # Optional per-node model override
-    temperature: 0.3           # Optional per-node sampling override
-    max_attempts: 2            # Retry count on transient errors only. Default 1.
-    max_iterations: 10         # Tool-call-loop turn cap. Default 10.
-    fallback: review           # Route here if all attempts fail
-    timeout: 300               # Optional node wall-clock cap, seconds (unset = no timeout)
-    state_updates:
-      research: "{{output}}"
-    next: review               # Required for llm nodes: the success route
-
-  # --- approval node ------------------------------------------------------
-  # Human-in-the-loop checkpoint. `user__ask` always offers a free-form
-  # "type your own answer" option, so `on_other` is required.
-  review:
-    id: review
-    type: approval
-    question: |
-      Proposed research result for {{topic}}:
-      {{research}}
-
-      Approve?
-    options:                   # The listed choices shown to the user
-      - "yes"
-      - "no"
-    routes:                    # Map each listed option to its next node
-      "yes": finalize
-      "no": rejected_end
-    on_other: refine           # Required: route for ANY answer not in `routes`
-    state_updates:
-      decision: "{{choice}}"   # {{choice}} = the chosen option or the free-form text
-
-  # --- input node ---------------------------------------------------------
-  # Collects a free-form string from the user.
-  refine:
-    id: refine
-    type: input
-    question: "What should be changed about the research result?"
-    default: "tighten the summary"  # Optional: used if the user submits empty input.
-                                    # Note: a substituted default is not re-validated,
-                                    # so make sure it would satisfy `validation`.
-    validation: "len(input) > 0"   # Optional length predicate: len(input) <op> N,
-                                   # <op> in > >= < <= == . Length only -- no regex.
-    state_updates:
-      refinement: "{{input}}"  # {{input}} = the user's text
-    next: finalize             # Required for input nodes: the success route
-
-  # --- llm node (final synthesis) -----------------------------------------
-  finalize:
-    id: finalize
-    type: llm
-    prompt: |
-      Produce the final research report for {{topic}}.
-      Result so far: {{research}}
-      Requested refinement (if any): {{refinement}}
-    state_updates:
-      final_report: "{{output}}"
-    next: done
-
-  # --- end nodes ----------------------------------------------------------
-  # Terminate the graph. `output` (templated, lenient interpolation) becomes
-  # the graph's final result. A graph needs at least one `end` node.
-  done:
-    id: done
-    type: end
-    state_updates:             # Optional: applied before `output` is rendered
-      status: "completed"
-    output: |
-      [{{status}}] {{final_report}}
-
-      Sources: {{sources}}
-
-  rejected_end:
-    id: rejected_end
-    type: end
-    output: "Research on {{topic}} was not approved."

justfile

@@ -18,7 +18,7 @@ fmt:
 	cargo fmt --all
 
 # Build the project for the current system architecture
-# (Gets stored at ./target/[debug|release]/coyote)
+# (Gets stored at ./target/[debug|release]/loki)
 [group: 'build']
 [arg('build_type', pattern="debug|release")]
 build build_type='debug':

models.yaml

@@ -3,62 +3,6 @@
 #  - https://platform.openai.com/docs/api-reference/chat
 - provider: openai
   models:
-    - name: gpt-5.5
-      max_input_tokens: 1050000
-      max_output_tokens: 128000
-      input_price: 5
-      output_price: 30
-      supports_vision: true
-      supports_function_calling: true
-    - name: gpt-5.5-pro
-      max_input_tokens: 1050000
-      max_output_tokens: 128000
-      input_price: 30
-      output_price: 180
-      supports_vision: true
-      supports_function_calling: true
-    - name: gpt-5.4
-      max_input_tokens: 1050000
-      max_output_tokens: 128000
-      input_price: 2.5
-      output_price: 15
-      supports_vision: true
-      supports_function_calling: true
-    - name: gpt-5.4-pro
-      max_input_tokens: 1050000
-      max_output_tokens: 128000
-      input_price: 30
-      output_price: 180
-      supports_vision: true
-      supports_function_calling: true
-    - name: gpt-5.4-mini
-      max_input_tokens: 400000
-      max_output_tokens: 128000
-      input_price: 0.75
-      output_price: 4.5
-      supports_vision: true
-      supports_function_calling: true
-    - name: gpt-5.4-nano
-      max_input_tokens: 400000
-      max_output_tokens: 128000
-      input_price: 0.2
-      output_price: 1.25
-      supports_vision: true
-      supports_function_calling: true
-    - name: gpt-5.3-codex
-      max_input_tokens: 400000
-      max_output_tokens: 128000
-      input_price: 1.75
-      output_price: 14
-      supports_vision: true
-      supports_function_calling: true
-    - name: chat-latest
-      max_input_tokens: 400000
-      max_output_tokens: 128000
-      input_price: 5
-      output_price: 30
-      supports_vision: true
-      supports_function_calling: true
     - name: gpt-5.2
       max_input_tokens: 400000
       max_output_tokens: 128000
@@ -258,24 +202,6 @@
 #  - https://ai.google.dev/api/rest/v1beta/models/streamGenerateContent
 - provider: gemini
   models:
-    - name: gemini-3.5-flash
-      max_input_tokens: 1048576
-      max_output_tokens: 65536
-      input_price: 0.2
-      output_price: 1.5
-      supports_function_calling: true
-    - name: gemini-3-flash-preview
-      max_input_tokens: 1048576
-      max_output_tokens: 65536
-      input_price: 0.2
-      output_price: 1.5
-      supports_function_calling: true
-    - name: gemini-3.1-flash-lite
-      max_input_tokens: 1048576
-      max_output_tokens: 65536
-      input_price: 0.2
-      output_price: 1.5
-      supports_function_calling: true
     - name: gemini-3.1-pro-preview
       max_input_tokens: 1048576
       max_output_tokens: 65535
@@ -312,6 +238,20 @@
       max_input_tokens: 1048576
       supports_vision: true
       supports_function_calling: true
+    - name: gemini-2.0-flash
+      max_input_tokens: 1048576
+      max_output_tokens: 8192
+      input_price: 0
+      output_price: 0
+      supports_vision: true
+      supports_function_calling: true
+    - name: gemini-2.0-flash-lite
+      max_input_tokens: 1048576
+      max_output_tokens: 8192
+      input_price: 0
+      output_price: 0
+      supports_vision: true
+      supports_function_calling: true
     - name: gemma-3-27b-it
       max_input_tokens: 131072
       max_output_tokens: 8192
@@ -329,22 +269,6 @@
 #  - https://docs.anthropic.com/en/api/messages
 - provider: claude
   models:
-    - name: claude-opus-4-8
-      max_input_tokens: 1000000
-      max_output_tokens: 128000
-      require_max_tokens: true
-      input_price: 5
-      output_price: 25
-      supports_vision: true
-      supports_function_calling: true
-    - name: claude-opus-4-7
-      max_input_tokens: 1000000
-      max_output_tokens: 128000
-      require_max_tokens: true
-      input_price: 5
-      output_price: 25
-      supports_vision: true
-      supports_function_calling: true
     - name: claude-opus-4-6
       max_input_tokens: 200000
       max_output_tokens: 8192
@@ -563,6 +487,14 @@
           thinking:
             type: enabled
             budget_tokens: 16000
+    - name: claude-3-5-haiku-20241022
+      max_input_tokens: 200000
+      max_output_tokens: 8192
+      require_max_tokens: true
+      input_price: 0.8
+      output_price: 4
+      supports_vision: true
+      supports_function_calling: true
 
 # Links:
 #  - https://docs.mistral.ai/getting-started/models/models_overview/
@@ -813,24 +745,6 @@
 #  - https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/gemini
 - provider: vertexai
   models:
-    - name: gemini-3.5-flash
-      max_input_tokens: 1048576
-      max_output_tokens: 65536
-      input_price: 0.2
-      output_price: 1.5
-      supports_function_calling: true
-    - name: gemini-3-flash-preview
-      max_input_tokens: 1048576
-      max_output_tokens: 65536
-      input_price: 0.2
-      output_price: 1.5
-      supports_function_calling: true
-    - name: gemini-3.1-flash-lite
-      max_input_tokens: 1048576
-      max_output_tokens: 65536
-      input_price: 0.2
-      output_price: 1.5
-      supports_function_calling: true
     - name: gemini-3.1-pro-preview
       max_input_tokens: 1048576
       max_output_tokens: 65536
@@ -867,20 +781,18 @@
       max_input_tokens: 1048576
       supports_vision: true
       supports_function_calling: true
-    - name: claude-opus-4-8
-      max_input_tokens: 1000000
-      max_output_tokens: 128000
-      require_max_tokens: true
-      input_price: 5
-      output_price: 25
+    - name: gemini-2.0-flash-001
+      max_input_tokens: 1048576
+      max_output_tokens: 8192
+      input_price: 0.15
+      output_price: 0.6
       supports_vision: true
       supports_function_calling: true
-    - name: claude-opus-4-7
-      max_input_tokens: 1000000
-      max_output_tokens: 128000
-      require_max_tokens: true
-      input_price: 5
-      output_price: 25
+    - name: gemini-2.0-flash-lite-001
+      max_input_tokens: 1048576
+      max_output_tokens: 8192
+      input_price: 0.075
+      output_price: 0.3
       supports_vision: true
       supports_function_calling: true
     - name: claude-opus-4-6
@@ -1038,22 +950,6 @@
 #  - https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference-call.html
 - provider: bedrock
   models:
-    - name: us.anthropic.claude-opus-4-8
-      max_input_tokens: 1000000
-      max_output_tokens: 128000
-      require_max_tokens: true
-      input_price: 5
-      output_price: 25
-      supports_vision: true
-      supports_function_calling: true
-    - name: us.anthropic.claude-opus-4-7
-      max_input_tokens: 1000000
-      max_output_tokens: 128000
-      require_max_tokens: true
-      input_price: 5
-      output_price: 25
-      supports_vision: true
-      supports_function_calling: true
     - name: us.anthropic.claude-opus-4-6-v1
       max_input_tokens: 200000
       max_output_tokens: 8192
@@ -1596,55 +1492,6 @@
 #  - https://openrouter.ai/docs/api-reference/chat-completion
 - provider: openrouter
   models:
-    - name: openai/gpt-5.5
-      max_input_tokens: 1050000
-      max_output_tokens: 128000
-      input_price: 5
-      output_price: 30
-      supports_vision: true
-      supports_function_calling: true
-    - name: openai/gpt-5.5-pro
-      max_input_tokens: 1050000
-      max_output_tokens: 128000
-      input_price: 30
-      output_price: 180
-      supports_vision: true
-      supports_function_calling: true
-    - name: openai/gpt-5.4
-      max_input_tokens: 1050000
-      max_output_tokens: 128000
-      input_price: 2.5
-      output_price: 15
-      supports_vision: true
-      supports_function_calling: true
-    - name: openai/gpt-5.4-pro
-      max_input_tokens: 1050000
-      max_output_tokens: 128000
-      input_price: 30
-      output_price: 180
-      supports_vision: true
-      supports_function_calling: true
-    - name: openai/gpt-5.4-mini
-      max_input_tokens: 400000
-      max_output_tokens: 128000
-      input_price: 0.75
-      output_price: 4.5
-      supports_vision: true
-      supports_function_calling: true
-    - name: openai/gpt-5.4-nano
-      max_input_tokens: 400000
-      max_output_tokens: 128000
-      input_price: 0.2
-      output_price: 1.25
-      supports_vision: true
-      supports_function_calling: true
-    - name: openai/gpt-5.3-codex
-      max_input_tokens: 400000
-      max_output_tokens: 128000
-      input_price: 1.75
-      output_price: 14
-      supports_vision: true
-      supports_function_calling: true
     - name: openai/gpt-5.2
       max_input_tokens: 400000
       max_output_tokens: 128000
@@ -1729,22 +1576,6 @@
       max_input_tokens: 131072
       input_price: 0.1
       output_price: 0.2
-    - name: anthropic/claude-opus-4-8
-      max_input_tokens: 1000000
-      max_output_tokens: 128000
-      require_max_tokens: true
-      input_price: 5
-      output_price: 25
-      supports_vision: true
-      supports_function_calling: true
-    - name: anthropic/claude-opus-4-7
-      max_input_tokens: 1000000
-      max_output_tokens: 128000
-      require_max_tokens: true
-      input_price: 5
-      output_price: 25
-      supports_vision: true
-      supports_function_calling: true
     - name: anthropic/claude-opus-4.6
       max_input_tokens: 200000
       max_output_tokens: 8192

package-lock.json

@@ -1,5 +1,5 @@
 {
-  "name": "coyote",
+  "name": "loki",
   "lockfileVersion": 3,
   "requires": true,
   "packages": {}

scripts/install_loki.ps1

@@ -1,24 +1,24 @@
 <#
-coyote installer (Windows/PowerShell 5+ and PowerShell 7)
+loki installer (Windows/PowerShell 5+ and PowerShell 7)
 
 Examples:
-  powershell -NoProfile -ExecutionPolicy Bypass -Command "iwr -useb https://raw.githubusercontent.com/Dark-Alex-17/coyote/main/scripts/install_coyote.ps1 | iex"
-  pwsh -c "irm https://raw.githubusercontent.com/Dark-Alex-17/coyote/main/scripts/install_coyote.ps1 | iex -Version vX.Y.Z"
+  powershell -NoProfile -ExecutionPolicy Bypass -Command "iwr -useb https://raw.githubusercontent.com/Dark-Alex-17/loki/main/scripts/install_loki.ps1 | iex"
+  pwsh -c "irm https://raw.githubusercontent.com/Dark-Alex-17/loki/main/scripts/install_loki.ps1 | iex -Version vX.Y.Z"
 
 Parameters:
   -Version   <tag>         (default: latest)
-  -BinDir    <path>        (default: %LOCALAPPDATA%\coyote\bin on Windows; ~/.local/bin on *nix PowerShell)
+  -BinDir    <path>        (default: %LOCALAPPDATA%\loki\bin on Windows; ~/.local/bin on *nix PowerShell)
 #>
 
 [CmdletBinding()]
 param(
-  [string]$Version = $env:COYOTE_VERSION,
+  [string]$Version = $env:LOKI_VERSION,
   [string]$BinDir = $env:BIN_DIR
 )
 
-$Repo = 'Dark-Alex-17/coyote'
+$Repo = 'Dark-Alex-17/loki'
 
-function Write-Info($msg) { Write-Host "[coyote-install] $msg" }
+function Write-Info($msg) { Write-Host "[loki-install] $msg" }
 function Fail($msg) { Write-Error $msg; exit 1 }
 
 Add-Type -AssemblyName System.Runtime
@@ -38,7 +38,7 @@ switch ([System.Runtime.InteropServices.RuntimeInformation]::OSArchitecture) {
 }
 
 if (-not $BinDir) {
-  if ($isWin) { $BinDir = Join-Path $env:LOCALAPPDATA 'coyote\bin' }
+  if ($isWin) { $BinDir = Join-Path $env:LOCALAPPDATA 'loki\bin' }
   else { $home = $env:HOME; if (-not $home) { $home = (Get-Item -Path ~).FullName }; $BinDir = Join-Path $home '.local/bin' }
 }
 New-Item -ItemType Directory -Force -Path $BinDir | Out-Null
@@ -49,23 +49,23 @@ $apiBase = "https://api.github.com/repos/$Repo/releases"
 $relUrl = if ($Version) { "$apiBase/tags/$Version" } else { "$apiBase/latest" }
 Write-Info "Fetching release: $relUrl"
 try {
-  $release = Invoke-RestMethod -UseBasicParsing -Headers @{ 'User-Agent' = 'coyote-installer' } -Uri $relUrl -Method GET
+  $release = Invoke-RestMethod -UseBasicParsing -Headers @{ 'User-Agent' = 'loki-installer' } -Uri $relUrl -Method GET
 } catch { Fail "Failed to fetch release metadata. $_" }
 if (-not $release.assets) { Fail "No assets found in the release." }
 
 $candidates = @()
 if ($os -eq 'windows') {
-  if ($arch -eq 'x86_64') { $candidates += 'coyote-x86_64-pc-windows-msvc.zip' }
-  else { $candidates += 'coyote-aarch64-pc-windows-msvc.zip' }
+  if ($arch -eq 'x86_64') { $candidates += 'loki-x86_64-pc-windows-msvc.zip' }
+  else { $candidates += 'loki-aarch64-pc-windows-msvc.zip' }
 } elseif ($os -eq 'darwin') {
-  if ($arch -eq 'x86_64') { $candidates += 'coyote-x86_64-apple-darwin.tar.gz' }
-  else { $candidates += 'coyote-aarch64-apple-darwin.tar.gz' }
+  if ($arch -eq 'x86_64') { $candidates += 'loki-x86_64-apple-darwin.tar.gz' }
+  else { $candidates += 'loki-aarch64-apple-darwin.tar.gz' }
 } elseif ($os -eq 'linux') {
   if ($arch -eq 'x86_64') {
-    $candidates += 'coyote-x86_64-unknown-linux-gnu.tar.gz'
-    $candidates += 'coyote-x86_64-unknown-linux-musl.tar.gz'
+    $candidates += 'loki-x86_64-unknown-linux-gnu.tar.gz'
+    $candidates += 'loki-x86_64-unknown-linux-musl.tar.gz'
   } else {
-    $candidates += 'coyote-aarch64-unknown-linux-musl.tar.gz'
+    $candidates += 'loki-aarch64-unknown-linux-musl.tar.gz'
   }
 } else {
   Fail "Unsupported OS for this installer: $os"
@@ -84,9 +84,9 @@ if (-not $asset) {
 Write-Info "Selected asset: $($asset.name)"
 Write-Info "Download URL:  $($asset.browser_download_url)"
 
-$tmp = New-Item -ItemType Directory -Force -Path ([IO.Path]::Combine([IO.Path]::GetTempPath(), "coyote-$(Get-Random)"))
+$tmp = New-Item -ItemType Directory -Force -Path ([IO.Path]::Combine([IO.Path]::GetTempPath(), "loki-$(Get-Random)"))
 $archive = Join-Path $tmp.FullName 'asset'
-try { Invoke-WebRequest -UseBasicParsing -Headers @{ 'User-Agent' = 'coyote-installer' } -Uri $asset.browser_download_url -OutFile $archive } catch { Fail "Failed to download asset. $_" }
+try { Invoke-WebRequest -UseBasicParsing -Headers @{ 'User-Agent' = 'loki-installer' } -Uri $asset.browser_download_url -OutFile $archive } catch { Fail "Failed to download asset. $_" }
 
 $extractDir = Join-Path $tmp.FullName 'extract'; New-Item -ItemType Directory -Force -Path $extractDir | Out-Null
 
@@ -107,14 +107,14 @@ if ($asset.name -match '\.zip$') {
 
 $bin = $null
 Get-ChildItem -Recurse -File $extractDir | ForEach-Object {
-  if ($isWin) { if ($_.Name -ieq 'coyote.exe') { $bin = $_.FullName } }
-  else { if ($_.Name -ieq 'coyote') { $bin = $_.FullName } }
+  if ($isWin) { if ($_.Name -ieq 'loki.exe') { $bin = $_.FullName } }
+  else { if ($_.Name -ieq 'loki') { $bin = $_.FullName } }
 }
-if (-not $bin) { Fail "Could not find coyote binary inside the archive." }
+if (-not $bin) { Fail "Could not find loki binary inside the archive." }
 
 if (-not $isWin) { try { & chmod +x -- $bin } catch {} }
 
-$exec = if ($isWin) { 'coyote.exe'} else { 'coyote' }
+$exec = if ($isWin) { 'loki.exe'} else { 'loki' }
 $dest = Join-Path $BinDir $exec
 Copy-Item -Force $bin $dest
 Write-Info "Installed: $dest"
@@ -135,5 +135,5 @@ if ($isWin) {
   }
 }
 
-Write-Info "Done. Try: coyote --help"
+Write-Info "Done. Try: loki --help"
 

scripts/install_loki.sh

@@ -1,23 +1,23 @@
 #!/usr/bin/env bash
 set -euo pipefail
 
-# coyote installer (Linux/macOS)
+# loki installer (Linux/macOS)
 #
 # Usage examples:
-#   curl -fsSL https://raw.githubusercontent.com/Dark-Alex-17/coyote/main/scripts/install_coyote.sh | bash
-#   curl -fsSL https://raw.githubusercontent.com/Dark-Alex-17/coyote/main/scripts/install_coyote.sh | bash -s -- --version vX.Y.Z
-#   BIN_DIR="$HOME/.local/bin" bash scripts/install_coyote.sh
+#   curl -fsSL https://raw.githubusercontent.com/Dark-Alex-17/loki/main/scripts/install_loki.sh | bash
+#   curl -fsSL https://raw.githubusercontent.com/Dark-Alex-17/loki/main/scripts/install_loki.sh | bash -s -- --version vX.Y.Z
+#   BIN_DIR="$HOME/.local/bin" bash scripts/install_loki.sh
 #
 # Flags / Env:
-#   --version <tag>   Release tag (default: latest). Or set COYOTE_VERSION.
+#   --version <tag>   Release tag (default: latest). Or set LOKI_VERSION.
 #   --bin-dir <dir>   Install directory (default: /usr/local/bin or ~/.local/bin). Or set BIN_DIR.
 
-REPO="Dark-Alex-17/coyote"
-VERSION="${COYOTE_VERSION:-}"
+REPO="Dark-Alex-17/loki"
+VERSION="${LOKI_VERSION:-}"
 BIN_DIR="${BIN_DIR:-}"
 
 usage() {
-  echo "coyote installer (Linux/macOS)"
+  echo "loki installer (Linux/macOS)"
   echo
   echo "Options:"
   echo "  --version <tag>         Release tag (default: latest)"
@@ -44,7 +44,7 @@ fi
 mkdir -p "${BIN_DIR}"
 
 log() {
-	echo "[coyote-install] $*"
+	echo "[loki-install] $*"
 }
 
 need_cmd() {
@@ -92,9 +92,9 @@ fi
 
 http_get() {
   if [[ "$DL" == "curl" ]]; then
-    curl -fsSL -H 'User-Agent: coyote-installer' "$1"
+    curl -fsSL -H 'User-Agent: loki-installer' "$1"
   else
-    wget -qO- --header='User-Agent: coyote-installer' "$1"
+    wget -qO- --header='User-Agent: loki-installer' "$1"
   fi
 }
 
@@ -111,9 +111,9 @@ fi
 ASSET_CANDIDATES=()
 if [[ "$OS" == "darwin" ]]; then
   if [[ "$ARCH" == "x86_64" ]]; then
-    ASSET_CANDIDATES+=("coyote-x86_64-apple-darwin.tar.gz")
+    ASSET_CANDIDATES+=("loki-x86_64-apple-darwin.tar.gz")
   else
-    ASSET_CANDIDATES+=("coyote-aarch64-apple-darwin.tar.gz")
+    ASSET_CANDIDATES+=("loki-aarch64-apple-darwin.tar.gz")
   fi
 elif [[ "$OS" == "linux" ]]; then
   if [[ "$ARCH" == "x86_64" ]]; then
@@ -122,12 +122,12 @@ elif [[ "$OS" == "linux" ]]; then
     if ldd --version 2>&1 | grep -qi glibc; then LIBC="gnu"; fi
 
     if [[ "$LIBC" == "gnu" ]]; then
-      ASSET_CANDIDATES+=("coyote-x86_64-unknown-linux-gnu.tar.gz")
+      ASSET_CANDIDATES+=("loki-x86_64-unknown-linux-gnu.tar.gz")
     fi
 
-    ASSET_CANDIDATES+=("coyote-x86_64-unknown-linux-musl.tar.gz")
+    ASSET_CANDIDATES+=("loki-x86_64-unknown-linux-musl.tar.gz")
   else
-    ASSET_CANDIDATES+=("coyote-aarch64-unknown-linux-musl.tar.gz")
+    ASSET_CANDIDATES+=("loki-aarch64-unknown-linux-musl.tar.gz")
   fi
 else
   echo "Error: unsupported OS for this installer: $OS" >&2; exit 1
@@ -170,9 +170,9 @@ log "Download URL: $ASSET_URL"
 
 ARCHIVE="$TMPDIR/asset"
 if [[ "$DL" == "curl" ]]; then
-  curl -fL -H 'User-Agent: coyote-installer' "$ASSET_URL" -o "$ARCHIVE"
+  curl -fL -H 'User-Agent: loki-installer' "$ASSET_URL" -o "$ARCHIVE"
 else
-  wget -q --header='User-Agent: coyote-installer' "$ASSET_URL" -O "$ARCHIVE"
+  wget -q --header='User-Agent: loki-installer' "$ASSET_URL" -O "$ARCHIVE"
 fi
 
 WORK="$TMPDIR/work"; mkdir -p "$WORK"
@@ -192,21 +192,21 @@ fi
 BIN_PATH=""
 while IFS= read -r -d '' f; do
   base=$(basename "$f")
-  if [[ "$base" == "coyote" ]]; then
+  if [[ "$base" == "loki" ]]; then
   	BIN_PATH="$f"
   	break
   fi
 done < <(find "$EXTRACTED_DIR" -type f -print0)
 
 if [[ -z "$BIN_PATH" ]]; then
-	echo "Error: could not find 'coyote' binary in the archive" >&2
+	echo "Error: could not find 'loki' binary in the archive" >&2
 	exit 1
 fi
 
 chmod +x "$BIN_PATH"
-install -m 0755 "$BIN_PATH" "${BIN_DIR}/coyote"
+install -m 0755 "$BIN_PATH" "${BIN_DIR}/loki"
 
-log "Installed: ${BIN_DIR}/coyote"
+log "Installed: ${BIN_DIR}/loki"
 
 case ":$PATH:" in
   *":${BIN_DIR}:"*) ;;
@@ -216,5 +216,5 @@ case ":$PATH:" in
     ;;
 esac
 
-log "Done. Try: coyote --help"
+log "Done. Try: loki --help"
 

scripts/shell-integration/integration.bash

@@ -1,7 +1,7 @@
-_coyote_bash() {
+_loki_bash() {
     if [[ -n "$READLINE_LINE" ]]; then
-        READLINE_LINE=$(coyote -e "$READLINE_LINE")
+        READLINE_LINE=$(loki -e "$READLINE_LINE")
         READLINE_POINT=${#READLINE_LINE}
     fi
 }
-bind -x '"\ee": _coyote_bash'
+bind -x '"\ee": _loki_bash'

scripts/shell-integration/integration.elv

@@ -1,7 +1,7 @@
-fn _coyote_elvish {
+fn _loki_elvish {
     var line = (edit:current-command)
-    var new-line = (coyote -e $line)
+    var new-line = (loki -e $line)
     edit:replace-input $new-line
 }
 
-edit:insert:binding[Alt-e] = $_coyote_elvish
+edit:insert:binding[Alt-e] = $_loki_elvish

scripts/shell-integration/integration.fish

@@ -1,9 +1,9 @@
-function _coyote_fish
+function _loki_fish
     set -l _old (commandline)
     if test -n $_old
         echo -n "⌛"
         commandline -f repaint
-        commandline (coyote -e $_old)
+        commandline (loki -e $_old)
     end
 end
-bind \ee _coyote_fish
+bind \ee _loki_fish

scripts/shell-integration/integration.nu

@@ -1,20 +1,20 @@
-def _coyote_nushell [] {
+def _loki_nushell [] {
     let _prev = (commandline)
     if ($_prev != "") {
         print '⌛'
-        commandline edit -r (coyote -e $_prev)
+        commandline edit -r (loki -e $_prev)
     }
 }
 
 $env.config.keybindings = ($env.config.keybindings | append {
-        name: coyote_integration
+        name: loki_integration
         modifier: alt
         keycode: char_e
         mode: [emacs, vi_insert]
         event:[
             {
                 send: executehostcommand,
-                cmd: "_coyote_nushell"
+                cmd: "_loki_nushell"
             }
         ]
     }

scripts/shell-integration/integration.ps1

@@ -3,7 +3,7 @@ Set-PSReadLineKeyHandler -Chord "alt+e" -ScriptBlock {
     [Microsoft.PowerShell.PSConsoleReadline]::GetBufferState([ref]$_old, [ref]$null)
     if ($_old) {
         [Microsoft.PowerShell.PSConsoleReadLine]::Insert('⌛')
-        $_new = (coyote -e $_old)
+        $_new = (loki -e $_old)
         [Microsoft.PowerShell.PSConsoleReadLine]::DeleteLine()
         [Microsoft.PowerShell.PSConsoleReadline]::Insert($_new)
     }

scripts/shell-integration/integration.zsh

@@ -1,11 +1,11 @@
-_coyote_zsh() {
+_loki_zsh() {
     if [[ -n "$BUFFER" ]]; then
         local _old=$BUFFER
         BUFFER+="⌛"
         zle -I && zle redisplay
-        BUFFER=$(coyote -e "$_old")
+        BUFFER=$(loki -e "$_old")
         zle end-of-line
     fi
 }
-zle -N _coyote_zsh
-bindkey '\ee' _coyote_zsh
+zle -N _loki_zsh
+bindkey '\ee' _loki_zsh

src/cli/completer.rs

@@ -1,15 +1,13 @@
 use crate::client::{ModelType, list_models};
 use crate::config::paths;
 use crate::config::{AppConfig, Config, list_agents, list_sessions};
-use crate::utils::list_file_names;
 use crate::vault::Vault;
 use clap_complete::{CompletionCandidate, Shell, generate};
 use clap_complete_nushell::Nushell;
-use std::env;
 use std::ffi::OsStr;
 use std::io;
 
-const COYOTE_CLI_NAME: &str = "coyote";
+const LOKI_CLI_NAME: &str = "loki";
 
 #[derive(Clone, Copy, Debug, clap::ValueEnum)]
 pub enum ShellCompletion {
@@ -24,14 +22,12 @@ pub enum ShellCompletion {
 impl ShellCompletion {
     pub fn generate_completions(self, cmd: &mut clap::Command) {
         match self {
-            Self::Bash => generate(Shell::Bash, cmd, COYOTE_CLI_NAME, &mut io::stdout()),
-            Self::Elvish => generate(Shell::Elvish, cmd, COYOTE_CLI_NAME, &mut io::stdout()),
-            Self::Fish => generate(Shell::Fish, cmd, COYOTE_CLI_NAME, &mut io::stdout()),
-            Self::PowerShell => {
-                generate(Shell::PowerShell, cmd, COYOTE_CLI_NAME, &mut io::stdout())
-            }
-            Self::Zsh => generate(Shell::Zsh, cmd, COYOTE_CLI_NAME, &mut io::stdout()),
-            Self::Nushell => generate(Nushell, cmd, COYOTE_CLI_NAME, &mut io::stdout()),
+            Self::Bash => generate(Shell::Bash, cmd, LOKI_CLI_NAME, &mut io::stdout()),
+            Self::Elvish => generate(Shell::Elvish, cmd, LOKI_CLI_NAME, &mut io::stdout()),
+            Self::Fish => generate(Shell::Fish, cmd, LOKI_CLI_NAME, &mut io::stdout()),
+            Self::PowerShell => generate(Shell::PowerShell, cmd, LOKI_CLI_NAME, &mut io::stdout()),
+            Self::Zsh => generate(Shell::Zsh, cmd, LOKI_CLI_NAME, &mut io::stdout()),
+            Self::Nushell => generate(Nushell, cmd, LOKI_CLI_NAME, &mut io::stdout()),
         }
     }
 }
@@ -98,36 +94,9 @@ pub(super) fn macro_completer(current: &OsStr) -> Vec<CompletionCandidate> {
         .collect()
 }
 
-fn extract_agent_from_args() -> Option<String> {
-    let args: Vec<String> = env::args().collect();
-    let mut i = 0;
-    while i < args.len() {
-        let arg = &args[i];
-
-        if let Some(value) = arg.strip_prefix("--agent=") {
-            return Some(value.to_string());
-        }
-
-        if (arg == "--agent" || arg == "-a") && i + 1 < args.len() {
-            return Some(args[i + 1].clone());
-        }
-
-        i += 1;
-    }
-    None
-}
-
 pub(super) fn session_completer(current: &OsStr) -> Vec<CompletionCandidate> {
     let cur = current.to_string_lossy();
-
-    let sessions = if let Some(agent_name) = extract_agent_from_args() {
-        let sessions_dir = paths::agent_data_dir(&agent_name).join("sessions");
-        list_file_names(sessions_dir, ".yaml")
-    } else {
-        list_sessions()
-    };
-
-    sessions
+    list_sessions()
         .into_iter()
         .filter(|s| s.starts_with(&*cur))
         .map(CompletionCandidate::new)
@@ -137,16 +106,13 @@ pub(super) fn session_completer(current: &OsStr) -> Vec<CompletionCandidate> {
 pub(super) fn secrets_completer(current: &OsStr) -> Vec<CompletionCandidate> {
     let cur = current.to_string_lossy();
     match load_app_config_for_completion() {
-        Ok(app_config) => match Vault::init(&app_config) {
-            Ok(vault) => vault
-                .list_secrets(false)
-                .unwrap_or_default()
-                .into_iter()
-                .filter(|s| s.starts_with(&*cur))
-                .map(CompletionCandidate::new)
-                .collect(),
-            Err(_) => vec![],
-        },
+        Ok(app_config) => Vault::init(&app_config)
+            .list_secrets(false)
+            .unwrap_or_default()
+            .into_iter()
+            .filter(|s| s.starts_with(&*cur))
+            .map(CompletionCandidate::new)
+            .collect(),
         Err(_) => vec![],
     }
 }