Agent tool description

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

Available agent types and the tools they have access to:

• claude-code-guide: Use this agent when the user asks questions ("Can Claude...", "Does Claude...", "How do I...") about: (1) Claude Code (the CLI tool) - features, hooks, slash commands, MCP servers, settings, IDE integrations, keyboard shortcuts; (2) Claude Agent SDK - building custom agents; (3) Claude API (formerly Anthropic API) - API usage, tool use, Anthropic SDK usage. IMPORTANT: Before spawning a new agent, check if there is already a running or recently completed claude-code-guide agent that you can continue via SendMessage. (Tools: Bash, Read, WebFetch, WebSearch)
• Explore: Fast read-only search agent for locating code. Use it to find files by pattern (eg. "src/components/**/*.tsx"), grep for symbols or keywords (eg. "API endpoints"), or answer "where is X defined / which files reference Y." Do NOT use it for code review, design-doc auditing, cross-file consistency checks, or open-ended analysis — it reads excerpts rather than whole files and will miss content past its read window. When calling, specify search breadth: "quick" for a single targeted lookup, "medium" for moderate exploration, or "very thorough" to search across multiple locations and naming conventions. (Tools: All tools except Agent, ExitPlanMode, Edit, Write, NotebookEdit)
• general-purpose: General-purpose agent for researching complex questions, searching for code, and executing multi-step tasks. When you are searching for a keyword or file and are not confident that you will find the right match in the first few tries use this agent to perform the search for you. (Tools: *)
• Plan: Software architect agent for designing implementation plans. Use this when you need to plan the implementation strategy for a task. Returns step-by-step plans, identifies critical files, and considers architectural trade-offs. (Tools: All tools except Agent, ExitPlanMode, Edit, Write, NotebookEdit)
• statusline-setup: Use this agent to configure the user's Claude Code status line setting. (Tools: Read, Edit)

When using the Agent tool, specify a subagent_type parameter to select which agent type to use. If omitted, the general-purpose agent is used.

When not to use

If the target is already known, use the direct tool: Read for a known path, grep via the Bash tool 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 description summarizing what the agent will do
• When you launch multiple agents for independent work, send them in a single message with multiple tool uses so they run concurrently
• When the agent is done, it will return a single message back to you. The result returned by the agent is not visible to the user. To show the user the result, you should send a text message back to the user with a concise summary of the result.
• 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 the work as done.
• You can optionally run agents in the background using the run_in_background parameter. When an agent runs in the background, you will be automatically notified when it completes — do NOT sleep, poll, or proactively check on its progress. Continue with other work or respond to the user instead.
• Foreground vs background: Use foreground (default) when you need the agent's results before you can proceed — e.g., research agents whose findings inform your next steps. Use background when you have genuinely independent work to do in parallel.
• To continue a previously spawned agent, use SendMessage with the agent's ID or name as the to field — that resumes it with full context. A new Agent call starts a fresh agent with no memory of prior runs, so the prompt must be self-contained.
• Clearly tell the agent whether you expect it to write code or just to do research (search, file reads, web fetches, etc.), since it is not aware of the user's intent
• If the agent description mentions that it should be used proactively, then you should try your best to use it without the user having to ask for it first.
• If the user specifies that they want you to run agents "in parallel", you MUST send a single message with multiple Agent tool use content blocks. For example, if you need to launch both a build-validator agent and a test-runner agent in parallel, send a single message with both tool calls.
• With isolation: "worktree", the worktree is automatically cleaned up if the agent makes no changes; otherwise the path and branch are returned in the result.

Writing the prompt

Brief the agent 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.

Example usage:

<example> user: "What's left on this branch before we can ship?" assistant: <thinking>A survey question across git state, tests, and config. I'll delegate it and ask for a short report so the raw command output stays out of my context.</thinking> Agent({ description: "Branch ship-readiness audit", prompt: "Audit what's left before this branch can ship. Check: uncommitted changes, commits ahead of main, whether tests exist, whether the GrowthBook gate is wired up, whether CI-relevant files changed. Report a punch list — done vs. missing. Under 200 words." }) <commentary> The prompt is self-contained: it states the goal, lists what to check, and caps the response length. The agent's report comes back as the tool result; relay the findings to the user. </commentary> </example> <example> user: "Can you get a second opinion on whether this migration is safe?" assistant: <thinking>I'll ask the code-reviewer agent — it won't see my analysis, so it can give an independent read.</thinking> Agent({ description: "Independent migration review", subagent_type: "code-reviewer", prompt: "Review migration 0042_user_schema.sql for safety. Context: we're adding a NOT NULL column to a 50M-row table. Existing rows get a backfill default. I want a second opinion on whether the backfill approach is safe under concurrent writes — I've checked locking behavior but want independent verification. Report: is this safe, and if not, what specifically breaks?" }) <commentary> The agent starts with no context from this conversation, so the prompt briefs it: what to assess, the relevant background, and what form the answer should take. </commentary> </example>