Subagent Orchestration

Use the subagent tool to delegate tasks to isolated pi subprocesses. Each subagent gets a fresh context window — no shared state with the parent session.

When to use subagents

• A task can be split into independent pieces that run in parallel
• You need a chain of specialists (scout → planner → worker)
• A subtask benefits from a clean context window (no accumulated noise)
• You want crash isolation (failed subtask doesn't corrupt main session)

Modes

Single — one agent, one task

{ "agent": "scout", "task": "Find all REST endpoints in " }

Parallel — multiple agents concurrently (streams progress as each completes)

{ "tasks": [
    { "agent": "scout", "task": "Audit auth module" },
    { "agent": "scout", "task": "Audit API routes" },
    { "agent": "scout", "task": "Audit database queries" }
  ]
}

Chain — sequential pipeline, use {previous} for prior step's output

{ "chain": [
    { "agent": "scout", "task": "Find all TODO comments in the codebase" },
    { "agent": "planner", "task": "Categorize and prioritize these TODOs:\n{previous}" },
    { "agent": "worker", "task": "Fix the top 3 critical TODOs:\n{previous}" }
  ]
}

Per-task options

Every task (single, parallel item, chain step) supports these overrides:

| Option | Type | Description | |--------|------|-------------| | model | string | Model override (e.g. "claude-haiku-4-5" for fast, "claude-sonnet-4-5" for complex) | | thinking | string | Thinking level: off, minimal, low, medium, high, xhigh | | extensions | string[] | Extension paths to load (subagents run with -ne — only whitelisted) | | skills | string[] | Skill files/dirs to load via --skill | | noTools | boolean | Disable all built-in tools (--no-tools) — for analysis-only agents | | noSkills | boolean | Disable skill discovery (-ns) | | cwd | string | Working directory override |

Priority: per-task item > top-level params > agent .md frontmatter > global settings

Examples

Fast recon with cheap model, no thinking overhead:

{ "agent": "scout", "task": "Map the auth module", "model": "claude-haiku-4-5", "thinking": "off" }

Research task needing web search:

{ "agent": "worker", "task": "Find pricing for Vercel Pro", "extensions": ["extensions/pi-brave-search"] }

Parallel with different models per task:

{ "tasks": [
    { "agent": "scout", "task": "Map the codebase", "model": "claude-haiku-4-5" },
    { "agent": "reviewer", "task": "Review the PR diff", "model": "claude-sonnet-4-5", "thinking": "high" }
  ]
}

Chain with escalating capability:

{ "chain": [
    { "agent": "scout", "task": "Map the auth module", "model": "claude-haiku-4-5", "thinking": "off" },
    { "agent": "planner", "task": "Plan a refactor based on: {previous}", "thinking": "high" },
    { "agent": "worker", "task": "Implement the plan: {previous}", "thinking": "medium" }
  ]
}

Extension isolation

Subagents always run with --no-extensions (-ne). They cannot:

• Spawn further subagents (pi-subagent is always blocked)
• Send messages via channels, cron, or heartbeat
• Access the web dashboard or webserver

Whitelist only what a specific task needs via the extensions parameter.

Agent scope

• "user" (default) — loads from ~/.pi/agent/agents/*.md
• "both" — also includes .pi/agents/*.md (prompts for confirmation)
• "project" — only project-local agents

Creating agents

Place .md files in ~/.pi/agent/agents/ with YAML frontmatter:

---
name: scout
description: Fast codebase reconnaissance
tools: read, grep, find, ls, bash
extensions: extensions/pi-dotenv
model: claude-haiku-4-5
---
System prompt for the agent goes here...

| Frontmatter | Description | |-------------|-------------| | name | Agent name (required) | | description | What the agent does (required) | | tools | Comma-separated tool whitelist | | model | Default model | | extensions | Comma-separated extension paths to load |

Tips

• Scout first: use scout (haiku, fast) for recon, then hand results to planner/worker
• Parallel for independence: only parallelize truly independent tasks
• Chain for pipelines: scout → planner → worker is the classic pattern
• Model matching: use haiku for simple recon, sonnet for analysis/implementation
• Thinking levels: off for fast tasks, high/xhigh for complex reasoning
• Keep extensions minimal: only whitelist what's actually needed per task