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docs: Updated the docs to include details on the new agent spawning system and built-in user interaction tools

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Alex Clarke
2026-02-18 12:16:29 -07:00
parent 655ee2a599
commit 812a8e101c
4 changed files with 253 additions and 3 deletions
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README.md
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@@ -35,7 +35,7 @@ Coming from [AIChat](https://github.com/sigoden/aichat)? Follow the [migration g
* [RAG](./docs/RAG.md): Retrieval-Augmented Generation for enhanced information retrieval and generation. * [RAG](./docs/RAG.md): Retrieval-Augmented Generation for enhanced information retrieval and generation.
* [Sessions](/docs/SESSIONS.md): Manage and persist conversational contexts and settings across multiple interactions. * [Sessions](/docs/SESSIONS.md): Manage and persist conversational contexts and settings across multiple interactions.
* [Roles](./docs/ROLES.md): Customize model behavior for specific tasks or domains. * [Roles](./docs/ROLES.md): Customize model behavior for specific tasks or domains.
* [Agents](/docs/AGENTS.md): Leverage AI agents to perform complex tasks and workflows. * [Agents](/docs/AGENTS.md): Leverage AI agents to perform complex tasks and workflows, including sub-agent spawning, teammate messaging, and user interaction tools.
* [Todo System](./docs/TODO-SYSTEM.md): Built-in task tracking for improved agent reliability with smaller models. * [Todo System](./docs/TODO-SYSTEM.md): Built-in task tracking for improved agent reliability with smaller models.
* [Environment Variables](./docs/ENVIRONMENT-VARIABLES.md): Override and customize your Loki configuration at runtime with environment variables. * [Environment Variables](./docs/ENVIRONMENT-VARIABLES.md): Override and customize your Loki configuration at runtime with environment variables.
* [Client Configurations](./docs/clients/CLIENTS.md): Configuration instructions for various LLM providers. * [Client Configurations](./docs/clients/CLIENTS.md): Configuration instructions for various LLM providers.
config.agent.example.yaml
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@@ -24,6 +24,16 @@ auto_continue: false # Enable automatic continuation when incomplete
max_auto_continues: 10 # Maximum number of automatic continuations before stopping 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 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) 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 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)
inject_spawn_instructions: true # Inject the default agent spawning instructions into the agent's system prompt
summarization_model: null # Model to use for summarizing sub-agent output (e.g. 'openai:gpt-4o-mini'); defaults to current model
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 mcp_servers: # Optional list of MCP servers that the agent utilizes
- github # Corresponds to the name of an MCP server in the `<loki-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 global_tools: # Optional list of additional global tools to enable for the agent; i.e. not tools specific to the agent
docs/AGENTS.md
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@@ -35,6 +35,18 @@ If you're looking for more example agents, refer to the [built-in agents](../ass
- [Bash-Based Agent Tools](#bash-based-agent-tools) - [Bash-Based Agent Tools](#bash-based-agent-tools)
- [5. Conversation Starters](#5-conversation-starters) - [5. Conversation Starters](#5-conversation-starters)
- [6. Todo System & Auto-Continuation](#6-todo-system--auto-continuation) - [6. Todo System & Auto-Continuation](#6-todo-system--auto-continuation)
- [7. Sub-Agent Spawning System](#7-sub-agent-spawning-system)
- [Configuration](#spawning-configuration)
- [Spawning & Collecting Agents](#spawning--collecting-agents)
- [Task Queue with Dependencies](#task-queue-with-dependencies)
- [Active Task Dispatch](#active-task-dispatch)
- [Output Summarization](#output-summarization)
- [Teammate Messaging](#teammate-messaging)
- [Runaway Safeguards](#runaway-safeguards)
- [8. User Interaction Tools](#8-user-interaction-tools)
- [Available Tools](#user-interaction-available-tools)
- [Escalation (Sub-Agent to User)](#escalation-sub-agent-to-user)
- [9. Auto-Injected Prompts](#9-auto-injected-prompts)
- [Built-In Agents](#built-in-agents) - [Built-In Agents](#built-in-agents)
<!--toc:end--> <!--toc:end-->
@@ -87,6 +99,14 @@ auto_continue: false # Enable automatic continuation when incomp
max_auto_continues: 10 # Maximum continuation attempts before stopping max_auto_continues: 10 # Maximum continuation attempts before stopping
inject_todo_instructions: true # Inject todo tool instructions into system prompt inject_todo_instructions: true # Inject todo tool instructions into system prompt
continuation_prompt: null # Custom prompt for continuations (optional) continuation_prompt: null # Custom prompt for continuations (optional)
# Sub-Agent Spawning (see "Sub-Agent Spawning System" section below)
can_spawn_agents: false # Enable spawning child agents
max_concurrent_agents: 4 # Max simultaneous child agents
max_agent_depth: 3 # Max nesting depth (prevents runaway)
inject_spawn_instructions: true # Inject spawning instructions into system prompt
summarization_model: null # Model for summarizing sub-agent output (e.g. 'openai:gpt-4o-mini')
summarization_threshold: 4000 # Char count above which sub-agent output is summarized
escalation_timeout: 300 # Seconds sub-agents wait for escalated user input (default: 5 min)
``` ```
As mentioned previously: Agents utilize function calling to extend a model's capabilities. However, agents operate in As mentioned previously: Agents utilize function calling to extend a model's capabilities. However, agents operate in
@@ -471,13 +491,230 @@ inject_todo_instructions: true # Include the default todo instructions into pr
For complete documentation including all configuration options, tool details, and best practices, see the For complete documentation including all configuration options, tool details, and best practices, see the
[Todo System Guide](./TODO-SYSTEM.md). [Todo System Guide](./TODO-SYSTEM.md).
## 7. Sub-Agent Spawning System
Loki agents can spawn and manage child agents that run **in parallel** as background tasks inside the same process.
This enables orchestrator-style agents that delegate specialized work to other agents, similar to how tools like
Claude Code or OpenCode handle complex multi-step tasks.
For a working example of an orchestrator agent that uses sub-agent spawning, see the built-in
[sisyphus](../assets/agents/sisyphus) agent. For an example of the teammate messaging pattern with parallel sub-agents,
see the [code-reviewer](../assets/agents/code-reviewer) agent.
### Spawning Configuration
| Setting | Type | Default | Description |
|-----------------------------|---------|---------------|--------------------------------------------------------------------------------|
| `can_spawn_agents` | boolean | `false` | Enable this agent to spawn child agents |
| `max_concurrent_agents` | integer | `4` | Maximum number of child agents that can run simultaneously |
| `max_agent_depth` | integer | `3` | Maximum nesting depth for sub-agents (prevents runaway spawning chains) |
| `inject_spawn_instructions` | boolean | `true` | Inject the default spawning instructions into the agent's system prompt |
| `summarization_model` | string | current model | Model to use for summarizing long sub-agent output (e.g. `openai:gpt-4o-mini`) |
| `summarization_threshold` | integer | `4000` | Character count above which sub-agent output is summarized before returning |
| `escalation_timeout` | integer | `300` | Seconds a sub-agent waits for an escalated user interaction response |
**Example configuration:**
```yaml
# agents/my-orchestrator/config.yaml
can_spawn_agents: true
max_concurrent_agents: 6
max_agent_depth: 2
inject_spawn_instructions: true
summarization_model: openai:gpt-4o-mini
summarization_threshold: 3000
escalation_timeout: 600
```
### Spawning & Collecting Agents
When `can_spawn_agents` is enabled, the agent receives tools for spawning and managing child agents:
| Tool | Description |
|------------------|-------------------------------------------------------------------------|
| `agent__spawn` | Spawn a child agent in the background. Returns an agent ID immediately. |
| `agent__check` | Non-blocking check: is the agent done? Returns `PENDING` or the result. |
| `agent__collect` | Blocking wait: wait for an agent to finish, return its output. |
| `agent__list` | List all spawned agents and their status. |
| `agent__cancel` | Cancel a running agent by ID. |
The core pattern is **Spawn -> Continue -> Collect**:
```
# 1. Spawn agents in parallel (returns IDs immediately)
agent__spawn --agent explore --prompt "Find auth middleware patterns in src/"
agent__spawn --agent explore --prompt "Find error handling patterns in src/"
# 2. Continue your own work while they run
# 3. Check if done (non-blocking)
agent__check --id agent_explore_a1b2c3d4
# 4. Collect results when ready (blocking)
agent__collect --id agent_explore_a1b2c3d4
agent__collect --id agent_explore_e5f6g7h8
```
Any agent defined in your `<loki-config-dir>/agents/` directory can be spawned as a child. Child agents:
- Run in a fully isolated environment (separate session, config, and tools)
- Have their output suppressed from the terminal (no spinner, no tool call logging)
- Return their accumulated output to the parent when collected
### Task Queue with Dependencies
For complex workflows where tasks have ordering requirements, the spawning system includes a dependency-aware
task queue:
| Tool | Description |
|------------------------|-----------------------------------------------------------------------------|
| `agent__task_create` | Create a task with optional dependencies and auto-dispatch agent. |
| `agent__task_list` | List all tasks with their status, dependencies, and assignments. |
| `agent__task_complete` | Mark a task done. Returns newly unblocked tasks and auto-dispatches agents. |
| `agent__task_fail` | Mark a task as failed. Dependents remain blocked. |
```
# Create tasks with dependency ordering
agent__task_create --subject "Explore existing patterns"
agent__task_create --subject "Implement feature" --blocked_by ["task_1"]
agent__task_create --subject "Write tests" --blocked_by ["task_2"]
# Mark tasks complete to unblock dependents
agent__task_complete --task_id task_1
```
### Active Task Dispatch
Tasks can optionally specify an agent to auto-spawn when the task becomes runnable:
```
agent__task_create \
--subject "Implement the auth module" \
--blocked_by ["task_1"] \
--agent coder \
--prompt "Implement auth module based on patterns found in task_1"
```
When `task_1` completes and the dependent task becomes unblocked, an agent is automatically spawned with the
specified prompt. No manual intervention needed. This enables fully automated multi-step pipelines.
### Output Summarization
When a child agent produces long output, it can be automatically summarized before returning to the parent.
This keeps parent context windows manageable.
- If the output exceeds `summarization_threshold` characters (default: 4000), it is sent through an LLM
summarization pass
- The `summarization_model` setting lets you use a cheaper/faster model for summarization (e.g. `gpt-4o-mini`)
- If `summarization_model` is not set, the parent's current model is used
- The summarization preserves all actionable information: code snippets, file paths, error messages, and
concrete recommendations
### Teammate Messaging
All agents (including children) automatically receive tools for **direct sibling-to-sibling messaging**:
| Tool | Description |
|-----------------------|-----------------------------------------------------|
| `agent__send_message` | Send a text message to another agent's inbox by ID. |
| `agent__check_inbox` | Drain all pending messages from your inbox. |
This enables coordination patterns where child agents share cross-cutting findings:
```
# Agent A discovers something relevant to Agent B
agent__send_message --id agent_reviewer_b1c2d3e4 --message "Found a security issue in auth.rs line 42"
# Agent B checks inbox before finalizing
agent__check_inbox
```
Messages are routed through the parent's supervisor. A parent can message its children, and children can message
their siblings. For a working example of the teammate pattern, see the built-in
[code-reviewer](../assets/agents/code-reviewer) agent, which spawns file-specific reviewers that share
cross-cutting findings with each other.
### Runaway Safeguards
The spawning system includes built-in safeguards to prevent runaway agent chains:
- **`max_concurrent_agents`:** Caps how many agents can run at once (default: 4). Spawn attempts beyond this
limit return an error asking the agent to wait or cancel existing agents.
- **`max_agent_depth`:** Caps nesting depth (default: 3). A child agent spawning its own child increments the
depth counter. Attempts beyond the limit are rejected.
- **`can_spawn_agents`:** Only agents with this flag set to `true` can spawn children. By default, spawning is
disabled. This means child agents cannot spawn their own children unless you explicitly create them with
`can_spawn_agents: true` in their config.
## 8. User Interaction Tools
Loki includes built-in tools for agents (and the REPL) to interactively prompt the user for input. These tools
are **always available**. No configuration needed. They are automatically injected into every agent and into
REPL mode when function calling is enabled.
### User Interaction Available Tools
| Tool | Description | Returns |
|------------------|-----------------------------------------|----------------------------------|
| `user__ask` | Present a single-select list of options | The selected option string |
| `user__confirm` | Ask a yes/no question | `"yes"` or `"no"` |
| `user__input` | Request free-form text input | The text entered by the user |
| `user__checkbox` | Present a multi-select checkbox list | Array of selected option strings |
**Parameters:**
- `user__ask`: `--question "..." --options ["Option A", "Option B", "Option C"]`
- `user__confirm`: `--question "..."`
- `user__input`: `--question "..."`
- `user__checkbox`: `--question "..." --options ["Option A", "Option B", "Option C"]`
At the top level (depth 0), these tools render interactive terminal prompts directly using arrow-key navigation,
checkboxes, and text input fields.
### Escalation (Sub-Agent to User)
When a **child agent** (depth > 0) calls a `user__*` tool, it cannot prompt the terminal directly. Instead,
the request is **automatically escalated** to the root agent:
1. The child agent calls `user__ask(...)` and **blocks**, waiting for a reply
2. The root agent sees a `pending_escalations` notification in its next tool results
3. The root agent either answers from context or prompts the user itself, then calls
`agent__reply_escalation` to unblock the child
4. The child receives the reply and continues
The escalation timeout is configurable via `escalation_timeout` in the agent's `config.yaml` (default: 300
seconds / 5 minutes). If the timeout expires, the child receives a fallback message asking it to use its
best judgment.
| Tool | Description |
|---------------------------|--------------------------------------------------------------------------|
| `agent__reply_escalation` | Reply to a pending child escalation, unblocking the waiting child agent. |
This tool is automatically available to any agent with `can_spawn_agents: true`.
## 9. Auto-Injected Prompts
Loki automatically appends usage instructions to your agent's system prompt for each enabled built-in system.
These instructions are injected into both **static and dynamic instructions** after your own instructions,
ensuring agents always know how to use their available tools.
| System | Injected When | Toggle |
|--------------------|----------------------------------------------------------------|-----------------------------|
| Todo tools | `auto_continue: true` AND `inject_todo_instructions: true` | `inject_todo_instructions` |
| Spawning tools | `can_spawn_agents: true` AND `inject_spawn_instructions: true` | `inject_spawn_instructions` |
| Teammate messaging | Always (all agents) | None (always injected) |
| User interaction | Always (all agents) | None (always injected) |
If you prefer to write your own instructions for a system, set the corresponding `inject_*` flag to `false`
and include your custom instructions in the agent's `instructions` field. The built-in tools will still be
available; only the auto-injected prompt text is suppressed.
## Built-In Agents ## Built-In Agents
Loki comes packaged with some useful built-in agents: Loki comes packaged with some useful built-in agents:
* `coder`: An agent to assist you with all your coding tasks * `coder`: An agent to assist you with all your coding tasks
* `code-reviewer`: A [CodeRabbit](https://coderabbit.ai)-style code reviewer that spawns per-file reviewers using the teammate messaging pattern
* `demo`: An example agent to use for reference when learning to create your own agents * `demo`: An example agent to use for reference when learning to create your own agents
* `explore`: An agent designed to help you explore and understand your codebase * `explore`: An agent designed to help you explore and understand your codebase
* `jira-helper`: An agent that assists you with all your Jira-related tasks * `jira-helper`: An agent that assists you with all your Jira-related tasks
* `oracle`: An agent for high-level architecture, design decisions, and complex debugging * `oracle`: An agent for high-level architecture, design decisions, and complex debugging
* `sisyphus`: A powerhouse agent for writing complex code and acting as a natural language interface for your codebase (similar to ClaudeCode, Gemini CLI, Codex, or OpenCode) * `sisyphus`: A powerhouse orchestrator agent for writing complex code and acting as a natural language interface for your codebase (similar to ClaudeCode, Gemini CLI, Codex, or OpenCode). Uses sub-agent spawning to delegate to `explore`, `coder`, and `oracle`.
* `sql`: A universal SQL agent that enables you to talk to any relational database in natural language * `sql`: A universal SQL agent that enables you to talk to any relational database in natural language
docs/REPL.md
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@@ -50,6 +50,9 @@ things like
* **Configurable Keybindings:** You can switch between `emacs` style keybindings or `vi` style keybindings * **Configurable Keybindings:** You can switch between `emacs` style keybindings or `vi` style keybindings
* [**Custom REPL Prompt:**](./REPL-PROMPT.md) You can even customize the REPL prompt to display information about the * [**Custom REPL Prompt:**](./REPL-PROMPT.md) You can even customize the REPL prompt to display information about the
current context in the prompt current context in the prompt
* **Built-in user interaction tools:** When function calling is enabled in the REPL, the `user__ask`, `user__confirm`,
`user__input`, and `user__checkbox` tools are always available for interactive prompts. These are not injected in the
one-shot CLI mode.
--- ---