Launch a new agent to handle complex, multi-step tasks autonomously. Each agent type has specific capabilities and tools available to it.

Available agent types and the tools they have access to:
{{typeList}}

Custom agents can be defined in .pi/agents/<name>.md (project) or {{agentDir}}/agents/<name>.md (global) — they are picked up automatically. Project-level agents override global ones. Creating a .md file with the same name as a default agent overrides it.

When using the Agent tool, specify a subagent_type parameter to select which agent type to use.

## When not to use

If the target is already known, use a direct tool — `read` for a known path, `grep`/`find` for a specific symbol or string. Reserve this tool for open-ended questions that span the codebase, or tasks that match an available agent type.

## Usage notes

- Always include a short (3-5 word) description summarizing what the agent will do (shown in UI).
- When an agent finishes or fails, you will be notified on subagent completion/failure — do NOT poll or sleep waiting for it.
- Trust but verify: an agent's summary describes what it intended to do, not necessarily what it did. When an agent writes or edits code, check the actual changes before reporting work as done.
- Use resume with an agent ID to continue a previous agent's work. A new (non-resume) Agent call starts a fresh agent with no memory of prior runs, so the prompt must be self-contained.
- Use steer_subagent to send mid-run messages to a running subagent.
- Clearly tell the agent whether you expect it to write code or just to do research (search, file reads, etc.), since it is not aware of the user's intent.
- Use inherit_context if the agent needs the parent conversation history.{{isolationGuideline}}{{scheduleGuideline}}

## Writing the prompt

Provide clear, detailed prompts so the agent can work autonomously. Brief it like a smart colleague who just walked into the room — it hasn't seen this conversation, doesn't know what you've tried, doesn't understand why this task matters.
- Explain what you're trying to accomplish and why.
- Describe what you've already learned or ruled out.
- Give enough context about the surrounding problem that the agent can make judgment calls rather than just following a narrow instruction.
- If you need a short response, say so ("report in under 200 words").
- Lookups: hand over the exact command. Investigations: hand over the question — prescribed steps become dead weight when the premise is wrong.

Terse command-style prompts produce shallow, generic work.

**Never delegate understanding.** Don't write "based on your findings, fix the bug" or "based on the research, implement it." Those phrases push synthesis onto the agent instead of doing it yourself. Write prompts that prove you understood: include file paths, line numbers, what specifically to change.