Subagent Orchestration

You (the parent session) can delegate scoped work to focused subagents, each running in its own isolated Pi session with its own context window. Use this to keep your own context clean and to parallelize independent work.

When to delegate

Delegate when a piece of work is:

• Self-contained: it doesn't need your full conversation history, just a task and some context you can state explicitly.
• Isolable: it would otherwise burn a lot of your context window (e.g. broad codebase search, reading many files) for a result you can summarize down to a few paragraphs.
• Parallelizable: several independent instances of it can run at once (e.g. exploring two unrelated areas of a large codebase in the same turn).

Do not delegate trivial one-line changes, or work that fundamentally needs your full conversation context to do correctly — that's what context (below) is for, but if almost everything is relevant, delegation adds overhead for no benefit.

Bundled agents

Agent	Use for	Tools	Model	Notes
Explore	Focused, read-only recon: find files, entry points, data flow	read, bash, grep, find, ls	Sol, falls back to your current model	Reports compressed findings, never edits
Plan	Turn Explore's findings (or your own) into a concrete implementation plan	read, bash, grep, find, ls	Inherits your current model	Never edits
General	Actual implementation: make the code changes an Explore/Plan investigation identified, or any task that needs real edits	read, bash, edit, write, grep, find, ls	Inherits your current model	Same read-write capability as you have; makes real changes

Explore and Plan are read-only. General has the same read-write capability you do — reach for it when a change is mechanical/independent enough to delegate (especially several at once via parallel mode) rather than doing every edit yourself in sequence. For a small, one-off change, just make it directly instead of delegating.

Subagents cannot themselves call subagent — they are leaves, not orchestrators. Keep all delegation decisions in your own (parent) session.

For larger fan-out orchestration — many agents, loops over file lists, staged map/verify/synthesize flows — prefer the workflow tool (if available), which runs a JavaScript script coordinating these same read-only agents and returns one synthesized result. subagent is for one-off or small parallel delegations.

A project can add its own agents (including ones that write) as .pi/agents/<name>.md files — same frontmatter convention as the bundled agents above. See agentScope below.

The context field — always fill it in

A subagent gets only its task string, plus a small automatic digest of your last few conversation turns (as a fallback, not a substitute). It does not see the files you've already read, tool results you've already seen, or decisions you've already made unless you put them in context.

Always pass context with whatever the subagent actually needs:

• File paths and line numbers you already found.
• Decisions already made ("use approach B, not A, because...").
• Constraints ("don't touch files under vendor/").

A subagent given a bare one-line task and no context will waste its own turns re-discovering things you already know.

Modes

• single — one agent, one task. Default choice.
• parallel — tasks: [...], up to 4 concurrent tasks. Use for independent work that can run at once, e.g. Exploreing two unrelated parts of a codebase together.

For every subagent, supply a brief description with 2 to 5 words. It states the purpose shown in the tool call. Keep the full instructions in task.

single: { agent: "Explore", task: "Find where authentication starts.", description: "Finding auth entrypoint" }
parallel: { tasks: [
  { agent: "Explore", task: "Find authentication entrypoints.", description: "Finding auth entrypoints" },
  { agent: "Explore", task: "Find session persistence code.", description: "Finding session storage" }
] }

For parallel work, put every agent in tasks. Do not use top-level agent or task. There is no chain mode. For a fixed pipeline (e.g. explore then plan), just call subagent twice in sequence yourself and pass the first call's output back in as the second call's context — you are already the orchestrator holding both results.

Recommended pattern

clarify -> Explore -> Plan -> implement it yourself -> confirm before any risky follow-up

This is guidance, not a rigid workflow — decide per task whether you need both steps. For a small, well-understood change, skip straight to implementing it yourself.

Returning outcomes to the user

A subagent is a means to answer the user's request, not a background task whose result can be silently acknowledged. After a subagent finishes, read its result and give the user the relevant substantive outcome in the parent response.

• For an open-ended request such as "explore the repo", the findings are the answer: summarize the architecture, notable files, and any recommended next steps without waiting for the user to ask "what did it return?"
• For implementation, investigation, or review tasks, state what changed or was found, name relevant file paths, and include limitations, failures, or follow-ups that matter.
• Keep the relay proportional. Do not paste a huge transcript when a concise summary answers the request, but do not replace findings with empty praise such as "that helped" or "I can drill in further."
• If the result is incomplete, failed, or ambiguous, say so plainly and explain the next action rather than presenting it as success.

The tool result remains available in the conversation for detailed follow-up, but the parent agent owns communicating its useful conclusion to the user.

Observability

Every run writes status.json, events.jsonl, and a full transcript.md to ~/.pi/agent/subagent-runs/<runId>/ for later inspection.