2538 Sub Agents Doc 1682f837

Documentation Index

Fetch the complete documentation index at: https://code.claude.com/docs/llms.txt Use this file to discover all available pages before exploring further.

Create custom subagents

Create and use specialized AI subagents in Claude Code for task-specific workflows and improved context management.

Subagents are specialized AI assistants that handle specific types of tasks. Each subagent runs in its own context window with a custom system prompt, specific tool access, and independent permissions. When Claude encounters a task that matches a subagent's description, it delegates to that subagent, which works independently and returns results.

Subagents help you:

• Preserve context by keeping exploration and implementation out of your main conversation
• Enforce constraints by limiting which tools a subagent can use
• Reuse configurations across projects with user-level subagents
• Specialize behavior with focused system prompts for specific domains
• Control costs by routing tasks to faster, cheaper models like Haiku

Claude uses each subagent's description to decide when to delegate tasks. When you create a subagent, write a clear description so Claude knows when to use it.

Claude Code includes several built-in subagents like Explore, Plan, and general-purpose. You can also create custom subagents to handle specific tasks. This page covers the built-in subagents, how to create your own, full configuration options, patterns for working with subagents, and example subagents.

Built-in subagents

Claude Code includes built-in subagents that Claude automatically uses when appropriate. Each inherits the parent conversation's permissions with additional tool restrictions.

* **Model**: Haiku (fast, low-latency)
* **Tools**: Read-only tools (denied access to Write and Edit tools)
* **Purpose**: File discovery, code search, codebase exploration

Claude delegates to Explore when it needs to search or understand a codebase without making changes. This keeps exploration results out of your main conversation context.

When invoking Explore, Claude specifies a thoroughness level: **quick** for targeted lookups, **medium** for balanced exploration, or **very thorough** for comprehensive analysis.

* **Model**: Inherits from main conversation
* **Tools**: Read-only tools (denied access to Write and Edit tools)
* **Purpose**: Codebase research for planning

When you're in plan mode and Claude needs to understand your codebase, it delegates research to the Plan subagent. This prevents infinite nesting (subagents cannot spawn other subagents) while still gathering necessary context.

* **Model**: Inherits from main conversation
* **Tools**: All tools
* **Purpose**: Complex research, multi-step operations, code modifications

Claude delegates to general-purpose when the task requires both exploration and modification, complex reasoning to interpret results, or multiple dependent steps.

| Agent             | Model    | When Claude uses it                                      |
| :---------------- | :------- | :------------------------------------------------------- |
| Bash              | Inherits | Running terminal commands in a separate context          |
| statusline-setup  | Sonnet   | When you run `/statusline` to configure your status line |
| Claude Code Guide | Haiku    | When you ask questions about Claude Code features        |

Beyond these built-in subagents, you can create your own with custom prompts, tool restrictions, permission modes, hooks, and skills. The following sections show how to get started and customize subagents.

Quickstart: create your first subagent

Subagents are defined in Markdown files with YAML frontmatter. You can create them manually or use the /agents command.

This walkthrough guides you through creating a user-level subagent with the /agent command. The subagent reviews code and suggests improvements for the codebase.

```
/agents
```

```
A code improvement agent that scans files and suggests improvements
for readability, performance, and best practices. It should explain
each issue, show the current code, and provide an improved version.
```

Claude generates the system prompt and configuration. Press `e` to open it in your editor if you want to customize it.

```
Use the code-improver agent to suggest improvements in this project
```

Claude delegates to your new subagent, which scans the codebase and returns improvement suggestions.

You now have a subagent you can use in any project on your machine to analyze codebases and suggest improvements.

You can also create subagents manually as Markdown files, define them via CLI flags, or distribute them through plugins. The following sections cover all configuration options.

Configure subagents

Use the /agents command

The /agents command provides an interactive interface for managing subagents. Run /agents to:

• View all available subagents (built-in, user, project, and plugin)
• Create new subagents with guided setup or Claude generation
• Edit existing subagent configuration and tool access
• Delete custom subagents
• See which subagents are active when duplicates exist

This is the recommended way to create and manage subagents. For manual creation or automation, you can also add subagent files directly.

To list all configured subagents from the command line without starting an interactive session, run claude agents. This shows agents grouped by source and indicates which are overridden by higher-priority definitions.

Choose the subagent scope

Subagents are Markdown files with YAML frontmatter. Store them in different locations depending on scope. When multiple subagents share the same name, the higher-priority location wins.

Project subagents (.claude/agents/) are ideal for subagents specific to a codebase. Check them into version control so your team can use and improve them collaboratively.

User subagents (~/.claude/agents/) are personal subagents available in all your projects.

CLI-defined subagents are passed as JSON when launching Claude Code. They exist only for that session and aren't saved to disk, making them useful for quick testing or automation scripts:

claude --agents '{
  "code-reviewer": {
    "description": "Expert code reviewer. Use proactively after code changes.",
    "prompt": "You are a senior code reviewer. Focus on code quality, security, and best practices.",
    "tools": ["Read", "Grep", "Glob", "Bash"],
    "model": "sonnet"
  }
}'

The --agents flag accepts JSON with the same frontmatter fields as file-based subagents: description, prompt, tools, disallowedTools, model, permissionMode, mcpServers, hooks, maxTurns, skills, and memory. Use prompt for the system prompt, equivalent to the markdown body in file-based subagents. See the CLI reference for the full JSON format.

Plugin subagents come from plugins you've installed. They appear in /agents alongside your custom subagents. See the plugin components reference for details on creating plugin subagents.

Write subagent files

Subagent files use YAML frontmatter for configuration, followed by the system prompt in Markdown:

---
name: code-reviewer
description: Reviews code for quality and best practices
tools: Read, Glob, Grep
model: sonnet
---

You are a code reviewer. When invoked, analyze the code and provide
specific, actionable feedback on quality, security, and best practices.

The frontmatter defines the subagent's metadata and configuration. The body becomes the system prompt that guides the subagent's behavior. Subagents receive only this system prompt (plus basic environment details like working directory), not the full Claude Code system prompt.

Supported frontmatter fields

The following fields can be used in the YAML frontmatter. Only name and description are required.

Choose a model

The model field controls which AI model the subagent uses:

• Model alias: Use one of the available aliases: sonnet, opus, or haiku
• inherit: Use the same model as the main conversation
• Omitted: If not specified, defaults to inherit (uses the same model as the main conversation)

Control subagent capabilities

You can control what subagents can do through tool access, permission modes, and conditional rules.

Available tools

Subagents can use any of Claude Code's internal tools. By default, subagents inherit all tools from the main conversation, including MCP tools.

To restrict tools, use the tools field (allowlist) or disallowedTools field (denylist):

---
name: safe-researcher
description: Research agent with restricted capabilities
tools: Read, Grep, Glob, Bash
disallowedTools: Write, Edit
---

Restrict which subagents can be spawned

When an agent runs as the main thread with claude --agent, it can spawn subagents using the Task tool. To restrict which subagent types it can spawn, use Task(agent_type) syntax in the tools field:

---
name: coordinator
description: Coordinates work across specialized agents
tools: Task(worker, researcher), Read, Bash
---

This is an allowlist: only the worker and researcher subagents can be spawned. If the agent tries to spawn any other type, the request fails and the agent sees only the allowed types in its prompt. To block specific agents while allowing all others, use permissions.deny instead.

To allow spawning any subagent without restrictions, use Task without parentheses:

tools: Task, Read, Bash

If Task is omitted from the tools list entirely, the agent cannot spawn any subagents. This restriction only applies to agents running as the main thread with claude --agent. Subagents cannot spawn other subagents, so Task(agent_type) has no effect in subagent definitions.

Permission modes

The permissionMode field controls how the subagent handles permission prompts. Subagents inherit the permission context from the main conversation but can override the mode.

If the parent uses bypassPermissions, this takes precedence and cannot be overridden.

Preload skills into subagents

Use the skills field to inject skill content into a subagent's context at startup. This gives the subagent domain knowledge without requiring it to discover and load skills during execution.

---
name: api-developer
description: Implement API endpoints following team conventions
skills:
  - api-conventions
  - error-handling-patterns
---

Implement API endpoints. Follow the conventions and patterns from the preloaded skills.

The full content of each skill is injected into the subagent's context, not just made available for invocation. Subagents don't inherit skills from the parent conversation; you must list them explicitly.

Enable persistent memory

The memory field gives the subagent a persistent directory that survives across conversations. The subagent uses this directory to build up knowledge over time, such as codebase patterns, debugging insights, and architectural decisions.

---
name: code-reviewer
description: Reviews code for quality and best practices
memory: user
---

You are a code reviewer. As you review code, update your agent memory with
patterns, conventions, and recurring issues you discover.

Choose a scope based on how broadly the memory should apply:

When memory is enabled:

• The subagent's system prompt includes instructions for reading and writing to the memory directory.
• The subagent's system prompt also includes the first 200 lines of MEMORY.md in the memory directory, with instructions to curate MEMORY.md if it exceeds 200 lines.
• Read, Write, and Edit tools are automatically enabled so the subagent can manage its memory files.

Persistent memory tips

• user is the recommended default scope. Use project or local when the subagent's knowledge is only relevant to a specific codebase.

• Ask the subagent to consult its memory before starting work: "Review this PR, and check your memory for patterns you've seen before."

• Ask the subagent to update its memory after completing a task: "Now that you're done, save what you learned to your memory." Over time, this builds a knowledge base that makes the subagent more effective.

• Include memory instructions directly in the subagent's markdown file so it proactively maintains its own knowledge base:

  Update your agent memory as you discover codepaths, patterns, library
  locations, and key architectural decisions. This builds up institutional
  knowledge across conversations. Write concise notes about what you found
  and where.
  

Conditional rules with hooks

For more dynamic control over tool usage, use PreToolUse hooks to validate operations before they execute. This is useful when you need to allow some operations of a tool while blocking others.

This example creates a subagent that only allows read-only database queries. The PreToolUse hook runs the script specified in command before each Bash command executes:

---
name: db-reader
description: Execute read-only database queries
tools: Bash
hooks:
  PreToolUse:
    - matcher: "Bash"
      hooks:
        - type: command
          command: "./scripts/validate-readonly-query.sh"
---

Claude Code passes hook input as JSON via stdin to hook commands. The validation script reads this JSON, extracts the Bash command, and exits with code 2 to block write operations:

#!/bin/bash
# ./scripts/validate-readonly-query.sh

INPUT=$(cat)
COMMAND=$(echo "$INPUT" | jq -r '.tool_input.command // empty')

# Block SQL write operations (case-insensitive)
if echo "$COMMAND" | grep -iE '\b(INSERT|UPDATE|DELETE|DROP|CREATE|ALTER|TRUNCATE)\b' > /dev/null; then
  echo "Blocked: Only SELECT queries are allowed" >&2
  exit 2
fi

exit 0

See Hook input for the complete input schema and exit codes for how exit codes affect behavior.

Disable specific subagents

You can prevent Claude from using specific subagents by adding them to the deny array in your settings. Use the format Task(subagent-name) where subagent-name matches the subagent's name field.

{
  "permissions": {
    "deny": ["Task(Explore)", "Task(my-custom-agent)"]
  }
}

This works for both built-in and custom subagents. You can also use the --disallowedTools CLI flag:

claude --disallowedTools "Task(Explore)"

See Permissions documentation for more details on permission rules.

Define hooks for subagents

Subagents can define hooks that run during the subagent's lifecycle. There are two ways to configure hooks:

1. In the subagent's frontmatter: Define hooks that run only while that subagent is active
2. In settings.json: Define hooks that run in the main session when subagents start or stop

Hooks in subagent frontmatter

Define hooks directly in the subagent's markdown file. These hooks only run while that specific subagent is active and are cleaned up when it finishes.

All hook events are supported. The most common events for subagents are:

This example validates Bash commands with the PreToolUse hook and runs a linter after file edits with PostToolUse:

---
name: code-reviewer
description: Review code changes with automatic linting
hooks:
  PreToolUse:
    - matcher: "Bash"
      hooks:
        - type: command
          command: "./scripts/validate-command.sh $TOOL_INPUT"
  PostToolUse:
    - matcher: "Edit|Write"
      hooks:
        - type: command
          command: "./scripts/run-linter.sh"
---

Stop hooks in frontmatter are automatically converted to SubagentStop events.

Project-level hooks for subagent events

Configure hooks in settings.json that respond to subagent lifecycle events in the main session.

Both events support matchers to target specific agent types by name. This example runs a setup script only when the db-agent subagent starts, and a cleanup script when any subagent stops:

{
  "hooks": {
    "SubagentStart": [
      {
        "matcher": "db-agent",
        "hooks": [
          { "type": "command", "command": "./scripts/setup-db-connection.sh" }
        ]
      }
    ],
    "SubagentStop": [
      {
        "hooks": [
          { "type": "command", "command": "./scripts/cleanup-db-connection.sh" }
        ]
      }
    ]
  }
}

See Hooks for the complete hook configuration format.

Work with subagents

Understand automatic delegation

Claude automatically delegates tasks based on the task description in your request, the description field in subagent configurations, and current context. To encourage proactive delegation, include phrases like "use proactively" in your subagent's description field.

You can also request a specific subagent explicitly:

Use the test-runner subagent to fix failing tests
Have the code-reviewer subagent look at my recent changes

Run subagents in foreground or background

Subagents can run in the foreground (blocking) or background (concurrent):

• Foreground subagents block the main conversation until complete. Permission prompts and clarifying questions (like AskUserQuestion) are passed through to you.
• Background subagents run concurrently while you continue working. Before launching, Claude Code prompts for any tool permissions the subagent will need, ensuring it has the necessary approvals upfront. Once running, the subagent inherits these permissions and auto-denies anything not pre-approved. If a background subagent needs to ask clarifying questions, that tool call fails but the subagent continues.

If a background subagent fails due to missing permissions, you can resume it in the foreground to retry with interactive prompts.

Claude decides whether to run subagents in the foreground or background based on the task. You can also:

• Ask Claude to "run this in the background"
• Press Ctrl+B to background a running task

To disable all background task functionality, set the CLAUDE_CODE_DISABLE_BACKGROUND_TASKS environment variable to 1. See Environment variables.

Common patterns

Isolate high-volume operations

One of the most effective uses for subagents is isolating operations that produce large amounts of output. Running tests, fetching documentation, or processing log files can consume significant context. By delegating these to a subagent, the verbose output stays in the subagent's context while only the relevant summary returns to your main conversation.

Use a subagent to run the test suite and report only the failing tests with their error messages

Run parallel research

For independent investigations, spawn multiple subagents to work simultaneously:

Research the authentication, database, and API modules in parallel using separate subagents

Each subagent explores its area independently, then Claude synthesizes the findings. This works best when the research paths don't depend on each other.

For tasks that need sustained parallelism or exceed your context window, agent teams give each worker its own independent context.

Chain subagents

For multi-step workflows, ask Claude to use subagents in sequence. Each subagent completes its task and returns results to Claude, which then passes relevant context to the next subagent.

Use the code-reviewer subagent to find performance issues, then use the optimizer subagent to fix them

Choose between subagents and main conversation

Use the main conversation when:

• The task needs frequent back-and-forth or iterative refinement
• Multiple phases share significant context (planning → implementation → testing)
• You're making a quick, targeted change
• Latency matters. Subagents start fresh and may need time to gather context

Use subagents when:

• The task produces verbose output you don't need in your main context
• You want to enforce specific tool restrictions or permissions
• The work is self-contained and can return a summary

Consider Skills instead when you want reusable prompts or workflows that run in the main conversation context rather than isolated subagent context.

Manage subagent context

Resume subagents

Each subagent invocation creates a new instance with fresh context. To continue an existing subagent's work instead of starting over, ask Claude to resume it.

Resumed subagents retain their full conversation history, including all previous tool calls, results, and reasoning. The subagent picks up exactly where it stopped rather than starting fresh.

When a subagent completes, Claude receives its agent ID. To resume a subagent, ask Claude to continue the previous work:

Use the code-reviewer subagent to review the authentication module
[Agent completes]

Continue that code review and now analyze the authorization logic
[Claude resumes the subagent with full context from previous conversation]

You can also ask Claude for the agent ID if you want to reference it explicitly, or find IDs in the transcript files at ~/.claude/projects/{project}/{sessionId}/subagents/. Each transcript is stored as agent-{agentId}.jsonl.

Subagent transcripts persist independently of the main conversation:

• Main conversation compaction: When the main conversation compacts, subagent transcripts are unaffected. They're stored in separate files.
• Session persistence: Subagent transcripts persist within their session. You can resume a subagent after restarting Claude Code by resuming the same session.
• Automatic cleanup: Transcripts are cleaned up based on the cleanupPeriodDays setting (default: 30 days).

Auto-compaction

Subagents support automatic compaction using the same logic as the main conversation. By default, auto-compaction triggers at approximately 95% capacity. To trigger compaction earlier, set CLAUDE_AUTOCOMPACT_PCT_OVERRIDE to a lower percentage (for example, 50). See environment variables for details.

Compaction events are logged in subagent transcript files:

{
  "type": "system",
  "subtype": "compact_boundary",
  "compactMetadata": {
    "trigger": "auto",
    "preTokens": 167189
  }
}

The preTokens value shows how many tokens were used before compaction occurred.

Example subagents

These examples demonstrate effective patterns for building subagents. Use them as starting points, or generate a customized version with Claude.

• Design focused subagents: each subagent should excel at one specific task
• Write detailed descriptions: Claude uses the description to decide when to delegate
• Limit tool access: grant only necessary permissions for security and focus
• Check into version control: share project subagents with your team

Code reviewer

A read-only subagent that reviews code without modifying it. This example shows how to design a focused subagent with limited tool access (no Edit or Write) and a detailed prompt that specifies exactly what to look for and how to format output.

---
name: code-reviewer
description: Expert code review specialist. Proactively reviews code for quality, security, and maintainability. Use immediately after writing or modifying code.
tools: Read, Grep, Glob, Bash
model: inherit
---

You are a senior code reviewer ensuring high standards of code quality and security.

When invoked:
1. Run git diff to see recent changes
2. Focus on modified files
3. Begin review immediately

Review checklist:
- Code is clear and readable
- Functions and variables are well-named
- No duplicated code
- Proper error handling
- No exposed secrets or API keys
- Input validation implemented
- Good test coverage
- Performance considerations addressed

Provide feedback organized by priority:
- Critical issues (must fix)
- Warnings (should fix)
- Suggestions (consider improving)

Include specific examples of how to fix issues.

Debugger

A subagent that can both analyze and fix issues. Unlike the code reviewer, this one includes Edit because fixing bugs requires modifying code. The prompt provides a clear workflow from diagnosis to verification.

---
name: debugger
description: Debugging specialist for errors, test failures, and unexpected behavior. Use proactively when encountering any issues.
tools: Read, Edit, Bash, Grep, Glob
---

You are an expert debugger specializing in root cause analysis.

When invoked:
1. Capture error message and stack trace
2. Identify reproduction steps
3. Isolate the failure location
4. Implement minimal fix
5. Verify solution works

Debugging process:
- Analyze error messages and logs
- Check recent code changes
- Form and test hypotheses
- Add strategic debug logging
- Inspect variable states

For each issue, provide:
- Root cause explanation
- Evidence supporting the diagnosis
- Specific code fix
- Testing approach
- Prevention recommendations

Focus on fixing the underlying issue, not the symptoms.

Data scientist

A domain-specific subagent for data analysis work. This example shows how to create subagents for specialized workflows outside of typical coding tasks. It explicitly sets model: sonnet for more capable analysis.

---
name: data-scientist
description: Data analysis expert for SQL queries, BigQuery operations, and data insights. Use proactively for data analysis tasks and queries.
tools: Bash, Read, Write
model: sonnet
---

You are a data scientist specializing in SQL and BigQuery analysis.

When invoked:
1. Understand the data analysis requirement
2. Write efficient SQL queries
3. Use BigQuery command line tools (bq) when appropriate
4. Analyze and summarize results
5. Present findings clearly

Key practices:
- Write optimized SQL queries with proper filters
- Use appropriate aggregations and joins
- Include comments explaining complex logic
- Format results for readability
- Provide data-driven recommendations

For each analysis:
- Explain the query approach
- Document any assumptions
- Highlight key findings
- Suggest next steps based on data

Always ensure queries are efficient and cost-effective.

Database query validator

A subagent that allows Bash access but validates commands to permit only read-only SQL queries. This example shows how to use PreToolUse hooks for conditional validation when you need finer control than the tools field provides.

---
name: db-reader
description: Execute read-only database queries. Use when analyzing data or generating reports.
tools: Bash
hooks:
  PreToolUse:
    - matcher: "Bash"
      hooks:
        - type: command
          command: "./scripts/validate-readonly-query.sh"
---

You are a database analyst with read-only access. Execute SELECT queries to answer questions about the data.

When asked to analyze data:
1. Identify which tables contain the relevant data
2. Write efficient SELECT queries with appropriate filters
3. Present results clearly with context

You cannot modify data. If asked to INSERT, UPDATE, DELETE, or modify schema, explain that you only have read access.

Claude Code passes hook input as JSON via stdin to hook commands. The validation script reads this JSON, extracts the command being executed, and checks it against a list of SQL write operations. If a write operation is detected, the script exits with code 2 to block execution and returns an error message to Claude via stderr.

Create the validation script anywhere in your project. The path must match the command field in your hook configuration:

#!/bin/bash
# Blocks SQL write operations, allows SELECT queries

# Read JSON input from stdin
INPUT=$(cat)

# Extract the command field from tool_input using jq
COMMAND=$(echo "$INPUT" | jq -r '.tool_input.command // empty')

if [ -z "$COMMAND" ]; then
  exit 0
fi

# Block write operations (case-insensitive)
if echo "$COMMAND" | grep -iE '\b(INSERT|UPDATE|DELETE|DROP|CREATE|ALTER|TRUNCATE|REPLACE|MERGE)\b' > /dev/null; then
  echo "Blocked: Write operations not allowed. Use SE

…(truncated)