> ## 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.
# Subagents in the SDK
> Define and invoke subagents to isolate context, run tasks in parallel, and apply specialized instructions in your Claude Agent SDK applications.
Subagents are separate agent instances that your main agent can spawn to handle focused subtasks.
Use them to isolate context, run multiple analyses in parallel, and apply specialized instructions without adding to the main agent's prompt.
This guide explains how to define and use subagents in the SDK using the `agents` parameter.
## Overview
You can create subagents in three ways:
* **Programmatically**: use the `agents` parameter in your `query()` options. See the [TypeScript](/docs/en/agent-sdk/typescript#agentdefinition) and [Python](/docs/en/agent-sdk/python#agentdefinition) references
* **Filesystem-based**: define agents as markdown files in `.claude/agents/` directories. See [defining subagents as files](/docs/en/sub-agents)
* **Built-in general-purpose**: Claude can invoke the built-in `general-purpose` subagent at any time via the Agent tool without you defining anything
This guide focuses on the programmatic approach, which is recommended for SDK applications.
When you define subagents, Claude determines whether to invoke them based on each subagent's `description` field. Write clear descriptions that explain when to use the subagent, and Claude automatically delegates appropriate tasks. You can also explicitly request a subagent by name in your prompt, for example "Use the code-reviewer agent to...".
## Benefits of using subagents
### Context isolation
Each subagent runs in its own fresh conversation. Intermediate tool calls and results stay inside the subagent; only its final message returns to the parent. See [What subagents inherit](#what-subagents-inherit) for exactly what's in the subagent's context.
**Example:** a `research-assistant` subagent can explore dozens of files without any of that content accumulating in the main conversation. The parent receives a concise summary, not every file the subagent read.
### Parallelization
Multiple subagents can run concurrently, so independent subtasks finish in the time of the slowest one rather than the sum of all of them.
**Example:** during a code review, you can run `style-checker`, `security-scanner`, and `test-coverage` subagents simultaneously instead of sequentially.
### Specialized instructions and knowledge
Each subagent can have tailored system prompts with specific expertise, best practices, and constraints.
**Example:** a `database-migration` subagent can have detailed knowledge about SQL best practices, rollback strategies, and data integrity checks that would be unnecessary noise in the main agent's instructions.
### Tool restrictions
Subagents can be limited to specific tools, reducing the risk of unintended actions.
**Example:** a `doc-reviewer` subagent might only have access to Read and Grep tools, ensuring it can analyze but never accidentally modify your documentation files.
## Create subagents
### Programmatic definition (recommended)
Define subagents directly in your code using the `agents` parameter. Claude invokes subagents through the `Agent` tool, so include `Agent` in `allowedTools` to auto-approve subagent invocations without a permission prompt.
Most examples on this page print only the final result. To confirm that Claude delegated to a subagent rather than answering directly, see [Detect subagent invocation](#detect-subagent-invocation).
This example creates two subagents: a code reviewer with read-only access and a test runner that can execute commands.
```python Python theme={null}
import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, AgentDefinition
async def main():
async for message in query(
prompt="Review the authentication module for security issues",
options=ClaudeAgentOptions(
# Auto-approve these tools, including Agent for subagent invocation
allowed_tools=["Read", "Grep", "Glob", "Agent"],
agents={
"code-reviewer": AgentDefinition(
# description tells Claude when to use this subagent
description="Expert code review specialist. Use for quality, security, and maintainability reviews.",
# prompt defines the subagent's behavior and expertise
prompt="""You are a code review specialist with expertise in security, performance, and best practices.
When reviewing code:
- Identify security vulnerabilities
- Check for performance issues
- Verify adherence to coding standards
- Suggest specific improvements
Be thorough but concise in your feedback.""",
# tools restricts what the subagent can do (read-only here)
tools=["Read", "Grep", "Glob"],
# model overrides the default model for this subagent
model="sonnet",
),
"test-runner": AgentDefinition(
description="Runs and analyzes test suites. Use for test execution and coverage analysis.",
prompt="""You are a test execution specialist. Run tests and provide clear analysis of results.
Focus on:
- Running test commands
- Analyzing test output
- Identifying failing tests
- Suggesting fixes for failures""",
# Bash access lets this subagent run test commands
tools=["Bash", "Read", "Grep"],
),
},
),
):
if hasattr(message, "result"):
print(message.result)
asyncio.run(main())
```
```typescript TypeScript theme={null}
import { query } from "@anthropic-ai/claude-agent-sdk";
for await (const message of query({
prompt: "Review the authentication module for security issues",
options: {
// Auto-approve these tools, including Agent for subagent invocation
allowedTools: ["Read", "Grep", "Glob", "Agent"],
agents: {
"code-reviewer": {
// description tells Claude when to use this subagent
description:
"Expert code review specialist. Use for quality, security, and maintainability reviews.",
// prompt defines the subagent's behavior and expertise
prompt: `You are a code review specialist with expertise in security, performance, and best practices.
When reviewing code:
- Identify security vulnerabilities
- Check for performance issues
- Verify adherence to coding standards
- Suggest specific improvements
Be thorough but concise in your feedback.`,
// tools restricts what the subagent can do (read-only here)
tools: ["Read", "Grep", "Glob"],
// model overrides the default model for this subagent
model: "sonnet"
},
"test-runner": {
description:
"Runs and analyzes test suites. Use for test execution and coverage analysis.",
prompt: `You are a test execution specialist. Run tests and provide clear analysis of results.
Focus on:
- Running test commands
- Analyzing test output
- Identifying failing tests
- Suggesting fixes for failures`,
// Bash access lets this subagent run test commands
tools: ["Bash", "Read", "Grep"]
}
}
}
})) {
if ("result" in message) console.log(message.result);
}
```
### AgentDefinition configuration
| Field | Type | Required | Description |
| :---------------- | :---------------------------------------------------------- | :------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| `description` | `string` | Yes | Natural language description of when to use this agent |
| `prompt` | `string` | Yes | The agent's system prompt defining its role and behavior |
| `tools` | `string[]` | No | Array of allowed tool names. If omitted, inherits every [tool available to subagents](/docs/en/sub-agents#available-tools) |
| `disallowedTools` | `string[]` | No | Array of tool names to remove from the agent's tool set. MCP server-level patterns are also accepted: `mcp__server` or `mcp__server__*` removes every tool from that server, and `mcp__*` removes every MCP tool from any server |
| `model` | `string` | No | Model override for this agent. Accepts an alias such as `'fable'`, `'opus'`, `'sonnet'`, `'haiku'`, `'inherit'`, or a full model ID. Defaults to main model if omitted |
| `skills` | `string[]` | No | List of skill names to preload into the agent's context at startup. Unlisted skills remain invocable through the Skill tool |
| `memory` | `'user' \| 'project' \| 'local'` | No | Memory source for this agent |
| `mcpServers` | `(string \| object)[]` | No | MCP servers available to this agent, by name or inline config |
| `initialPrompt` | `string` | No | Auto-submitted as the first user turn when this agent runs as the main thread agent. Ignored when the agent is invoked as a subagent |
| `maxTurns` | `number` | No | Maximum number of agentic turns before the agent stops |
| `background` | `boolean` | No | Run this agent as a non-blocking background task when invoked |
| `effort` | `'low' \| 'medium' \| 'high' \| 'xhigh' \| 'max' \| number` | No | Reasoning effort level for this agent |
| `permissionMode` | `PermissionMode` | No | Permission mode for tool execution within this agent |
In the Python SDK, multi-word field names such as `disallowedTools` and `mcpServers` keep their camelCase spelling to match the wire format rather than following Python's snake\_case convention. See the [`AgentDefinition` reference](/docs/en/agent-sdk/python#agentdefinition) for details.
Two subagent behaviors changed in Claude Code v2.1.198:
* Subagents run in the background by default. An Agent tool call that omits the [`run_in_background`](/docs/en/agent-sdk/typescript) input launches a background subagent, and Claude sets `run_in_background: false` when it needs the result before continuing. Before v2.1.198, omitting `run_in_background` ran the subagent synchronously. Set the `background` field to `true` to force background execution for a specific agent regardless of what Claude requests.
* A subagent inherits the main session's extended thinking configuration. On earlier versions, extended thinking is disabled inside subagents regardless of the main session's setting.
{/* min-version: 2.1.217 */}By default, subagents can't spawn subagents of their own. To let them, set [`CLAUDE_CODE_MAX_SUBAGENT_SPAWN_DEPTH`](/docs/en/env-vars) to the number of subagent layers you want below your main conversation, `2` or higher; see [nested subagents](/docs/en/sub-agents#let-subagents-spawn-their-own-subagents). From Claude Code v2.1.172 through v2.1.216, subagents could nest by default, up to five layers.
### Filesystem-based definition (alternative)
You can also define subagents as markdown files in `.claude/agents/` directories. See the [Claude Code subagents documentation](/docs/en/sub-agents) for details on this approach. Programmatically defined agents take precedence over filesystem-based agents with the same name.
Even without defining custom subagents, Claude can spawn the built-in `general-purpose` subagent. This is useful for delegating research or exploration tasks without creating specialized agents. Include `Agent` in `allowedTools` so these invocations auto-approve without a permission prompt.
## What subagents inherit
A subagent's context window starts fresh, with no parent conversation, but isn't empty. The only content you pass from parent to subagent is the Agent tool's prompt string, so include any file paths, error messages, or decisions the subagent needs directly in that prompt.
{/* min-version: 2.1.206 */}A subagent that has the [`SendMessage`](/docs/en/tools-reference) tool starts with a list of the other named agents running in the session, so it knows which names it can send messages to. Claude Code adds the list to the subagent's first turn automatically. A [fork](/docs/en/sub-agents#fork-the-current-conversation) doesn't get the list because it inherits the parent conversation instead. The list requires Claude Code v2.1.206 or later.
| The subagent receives | The subagent doesn't receive |
| :------------------------------------------------------------------------------------------------------------------------------------ | :----------------------------------------------------------------- |
| Its own system prompt (`AgentDefinition.prompt`) and the Agent tool's prompt | The parent's conversation history or tool results |
| Project CLAUDE.md (loaded via [`settingSources`](/docs/en/agent-sdk/claude-code-features#control-filesystem-settings-with-settingsources)) | Preloaded skill content, unless listed in `AgentDefinition.skills` |
| Tool definitions (inherited from parent or the subset in `tools`, [filtered for background runs](/docs/en/sub-agents#available-tools)) | The parent's system prompt |
The parent receives the subagent's final message as the Agent tool result, but may summarize it in its own response. To preserve subagent output verbatim in the user-facing response, include an instruction to do so in the prompt or `systemPrompt` option you pass to the main `query()` call.
{/* min-version: 2.1.210 */}In v2.1.210 and later, Claude Code [scans the final message for instruction-shaped patterns](/docs/en/sub-agents#subagent-output-scanning) before the parent reads it. The scan treats three kinds of pattern differently:
* **Control-tag imitation**: Claude Code neutralizes a tag that only the harness emits, such as a `` block, in place. It inserts a backslash after the opening angle bracket and deletes nothing.
* **Permission-configuration mentions**: Claude Code keeps references to the permission configuration, such as `.claude/settings.json`, `bypassPermissions`, or `--dangerously-skip-permissions`, as written.
* **Turn markers**: a line that starts with `Human:` or `Assistant:` gets a backslash before the colon, so the message can't imitate a conversation turn boundary.
For a control-tag or permission-configuration match, Claude Code prepends a `[harness: ...]` marker line naming the matched patterns; a turn-marker match doesn't add the marker line. Those are the only modifications the scan makes: it never removes or rewords the subagent's text.
{/* min-version: 2.1.199 */}An API error that ends the subagent early, such as a rate limit, is never delivered as its result. If a rate limit, overload, or server error cuts off a foreground subagent that already produced text output, the Agent tool returns that partial output with a note that the subagent didn't finish. {/* min-version: 2.1.200 */}A subagent that produced nothing, or whose only output was tool calls with no text, fails with an error message, `Agent terminated early due to an API error`, followed by the error detail. See [API errors in subagents](/docs/en/sub-agents#api-errors-in-subagents) for the foreground and background behavior.
This partial-output handling requires Claude Code v2.1.199 or later. In v2.1.199, a rate limit, overload, or server error left the tool-calls-only shape with an empty partial result containing only the cutoff note.
## Invoke subagents
### Automatic invocation
Claude automatically decides when to invoke subagents based on the task and each subagent's `description`. For example, if you define a `performance-optimizer` subagent with the description "Performance optimization specialist for query tuning", Claude will invoke it when your prompt mentions optimizing queries.
Write clear, specific descriptions so Claude can match tasks to the right subagent.
### Explicit invocation
To guarantee Claude uses a specific subagent, mention it by name in your prompt:
```text theme={null}
"Use the code-reviewer agent to check the authentication module"
```
This bypasses automatic matching and directly invokes the named subagent.
### Dynamic agent configuration
You can create agent definitions dynamically based on runtime conditions. This example creates a security reviewer with different strictness levels, using a more powerful model for strict reviews.
```python Python theme={null}
import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, AgentDefinition
# Factory function that returns an AgentDefinition
# This pattern lets you customize agents based on runtime conditions
def create_security_agent(security_level: str) -> AgentDefinition:
is_strict = security_level == "strict"
return AgentDefinition(
description="Security code reviewer",
# Customize the prompt based on strictness level
prompt=f"You are a {'strict' if is_strict else 'balanced'} security reviewer...",
tools=["Read", "Grep", "Glob"],
# Key insight: use a more capable model for high-stakes reviews
model="opus" if is_strict else "sonnet",
)
async def main():
# The agent is created at query time, so each request can use different settings
async for message in query(
prompt="Review this PR for security issues",
options=ClaudeAgentOptions(
allowed_tools=["Read", "Grep", "Glob", "Agent"],
agents={
# Call the factory with your desired configuration
"security-reviewer": create_security_agent("strict")
},
),
):
if hasattr(message, "result"):
print(message.result)
asyncio.run(main())
```
```typescript TypeScript theme={null}
import { query, type AgentDefinition } from "@anthropic-ai/claude-agent-sdk";
// Factory function that returns an AgentDefinition
// This pattern lets you customize agents based on runtime conditions
function createSecurityAgent(securityLevel: "basic" | "strict"): AgentDefinition {
const isStrict = securityLevel === "strict";
return {
description: "Security code reviewer",
// Customize the prompt based on strictness level
prompt: `You are a ${isStrict ? "strict" : "balanced"} security reviewer...`,
tools: ["Read", "Grep", "Glob"],
// Key insight: use a more capable model for high-stakes reviews
model: isStrict ? "opus" : "sonnet"
};
}
// The agent is created at query time, so each request can use different settings
for await (const message of query({
prompt: "Review this PR for security issues",
options: {
allowedTools: ["Read", "Grep", "Glob", "Agent"],
agents: {
// Call the factory with your desired configuration
"security-reviewer": createSecurityAgent("strict")
}
}
})) {
if ("result" in message) console.log(message.result);
}
```
## Detect subagent invocation
Claude invokes subagents through the Agent tool. To detect when a subagent is invoked, check for `tool_use` blocks where `name` is `"Agent"`. Messages from within a subagent's context include a `parent_tool_use_id` field.
The tool name was renamed from `"Task"` to `"Agent"` in Claude Code v2.1.63. Current SDK releases emit `"Agent"` in `tool_use` blocks but still use `"Task"` in the `system:init` tools list and in `result.permission_denials[].tool_name`. Checking both values in `block.name` ensures compatibility across SDK versions.
The message structure differs between SDKs. In Python, you access content blocks directly via `message.content`. In TypeScript, `SDKAssistantMessage` wraps the Claude API message, so you access content via `message.message.content`.
This example iterates through streamed messages, logging when a subagent is invoked and when subsequent messages originate from within that subagent's execution context.
```python Python theme={null}
import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, AgentDefinition, ToolUseBlock
async def main():
async for message in query(
prompt="Use the code-reviewer agent to review this codebase",
options=ClaudeAgentOptions(
allowed_tools=["Read", "Glob", "Grep", "Agent"],
agents={
"code-reviewer": AgentDefinition(
description="Expert code reviewer.",
prompt="Analyze code quality and suggest improvements.",
tools=["Read", "Glob", "Grep"],
)
},
),
):
# Check for subagent invocation. Match both names: older SDK
# versions emitted "Task", current versions emit "Agent".
if hasattr(message, "content") and message.content:
for block in message.content:
if isinstance(block, ToolUseBlock) and block.name in (
"Task",
"Agent",
):
print(f"Subagent invoked: {block.input.get('subagent_type')}")
# Check if this message is from within a subagent's context
if hasattr(message, "parent_tool_use_id") and message.parent_tool_use_id:
print(" (running inside subagent)")
if hasattr(message, "result"):
print(message.result)
asyncio.run(main())
```
```typescript TypeScript theme={null}
import { query } from "@anthropic-ai/claude-agent-sdk";
for await (const message of query({
prompt: "Use the code-reviewer agent to review this codebase",
options: {
allowedTools: ["Read", "Glob", "Grep", "Agent"],
agents: {
"code-reviewer": {
description: "Expert code reviewer.",
prompt: "Analyze code quality and suggest improvements.",
tools: ["Read", "Glob", "Grep"]
}
}
}
})) {
const msg = message as any;
// Check for subagent invocation. Match both names: older SDK versions
// emitted "Task", current versions emit "Agent".
for (const block of msg.message?.content ?? []) {
if (block.type === "tool_use" && (block.name === "Task" || block.name === "Agent")) {
console.log(`Subagent invoked: ${block.input.subagent_type}`);
}
}
// Check if this message is from within a subagent's context
if (msg.parent_tool_use_id) {
console.log(" (running inside subagent)");
}
if ("result" in message) {
console.log(message.result);
}
}
```
## Resume subagents
You can resume a subagent to continue where it left off rather than starting fresh. A resumed subagent retains its full conversation history, including all previous tool calls, results, and reasoning.
When a subagent completes, the Agent tool result includes a text block containing `agentId: `. The built-in [`Explore` and `Plan` agents](/docs/en/sub-agents#built-in-subagents) are one-shot and don't return an `agentId`, so use a custom agent or `general-purpose` when you need to resume. To resume a subagent programmatically:
1. **Capture the session ID**: extract `session_id` from messages during the first query
2. **Extract the agent ID**: parse `agentId` from the Agent tool result text
3. **Resume the session**: pass `resume: sessionId` in the second query's options, and include the agent ID in your prompt
You must resume the same session to access the subagent's transcript. Each `query()` call starts a new session by default, so pass `resume: sessionId` to continue in the same session.
When using a custom agent, pass the same agent definition in the `agents` parameter for both queries.
The example below defines a custom `endpoint-finder` agent. The first query runs it and captures the session ID and agent ID from the Agent tool result, then the second query resumes the session to ask a follow-up question that requires context from the first analysis.
```python Python theme={null}
import asyncio
import re
from claude_agent_sdk import query, ClaudeAgentOptions, AgentDefinition, ToolResultBlock
AGENTS = {
"endpoint-finder": AgentDefinition(
description="Locates and catalogs API endpoints in a codebase.",
prompt="You find and document API endpoints. Report each endpoint's path, method, and handler.",
tools=["Read", "Grep", "Glob"],
)
}
def extract_agent_id(block: ToolResultBlock) -> str | None:
"""Extract agentId from an Agent tool result's text content."""
parts = block.content if isinstance(block.content, list) else [{"text": block.content}]
for part in parts:
if match := re.search(r"agentId:\s*([\w-]+)", part.get("text") or ""):
return match.group(1)
return None
async def main():
agent_id = None
session_id = None
# First invocation - run the endpoint-finder subagent
try:
async for message in query(
prompt="Use the endpoint-finder agent to find all API endpoints in this codebase",
options=ClaudeAgentOptions(allowed_tools=["Read", "Grep", "Glob", "Agent"], agents=AGENTS),
):
# Capture session_id from ResultMessage (needed to resume this session)
if hasattr(message, "session_id"):
session_id = message.session_id
# Search tool results for the agentId trailer
for block in getattr(message, "content", None) or []:
if isinstance(block, ToolResultBlock):
agent_id = extract_agent_id(block) or agent_id
# Print the final result
if hasattr(message, "result"):
print(message.result)
except Exception as error:
# A single-shot query() raises after yielding an error result,
# so session_id and agent_id have already been captured by the loop above.
print(f"Session ended with an error: {error}")
# Second invocation - resume and ask follow-up
if agent_id and session_id:
async for message in query(
prompt=f"Resume agent {agent_id} and list the top 3 most complex endpoints",
options=ClaudeAgentOptions(
allowed_tools=["Read", "Grep", "Glob", "Agent"], agents=AGENTS, resume=session_id
),
):
if hasattr(message, "result"):
print(message.result)
else:
print("No agentId found in the first query, so there is no subagent to resume.")
asyncio.run(main())
```
```typescript TypeScript theme={null}
import { query, type SDKMessage } from "@anthropic-ai/claude-agent-sdk";
const agents = {
"endpoint-finder": {
description: "Locates and catalogs API endpoints in a codebase.",
prompt: "You find and document API endpoints. Report each endpoint's path, method, and handler.",
tools: ["Read", "Grep", "Glob"]
}
};
// Stringify content to search for agentId without traversing nested block types
function extractAgentId(message: SDKMessage): string | undefined {
if (message.type !== "assistant" && message.type !== "user") return undefined;
const content = JSON.stringify(message.message.content);
const match = content.match(/agentId:\s*([\w-]+)/);
return match?.[1];
}
let agentId: string | undefined;
let sessionId: string | undefined;
// First invocation - run the endpoint-finder subagent
try {
for await (const message of query({
prompt: "Use the endpoint-finder agent to find all API endpoints in this codebase",
options: { allowedTools: ["Read", "Grep", "Glob", "Agent"], agents }
})) {
// Capture session_id from ResultMessage (needed to resume this session)
if ("session_id" in message) sessionId = message.session_id;
// Search message content for the agentId (appears in Agent tool results)
const extractedId = extractAgentId(message);
if (extractedId) agentId = extractedId;
// Print the final result
if ("result" in message) console.log(message.result);
}
} catch (error) {
// A single-shot query() throws after yielding an error result,
// so sessionId and agentId have already been captured by the loop above.
console.error(`Session ended with an error: ${error}`);
}
// Second invocation - resume and ask follow-up
if (agentId && sessionId) {
for await (const message of query({
prompt: `Resume agent ${agentId} and list the top 3 most complex endpoints`,
options: { allowedTools: ["Read", "Grep", "Glob", "Agent"], agents, resume: sessionId }
})) {
if ("result" in message) console.log(message.result);
}
} else {
console.log("No agentId found in the first query, so there is no subagent to resume.");
}
```
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, which defaults to 30 days.
## Tool restrictions
Use the `tools` field to limit what a subagent can do:
* **Omit `tools`**: the subagent gets every [tool available to subagents](/docs/en/sub-agents#available-tools)
* **List tools**: the subagent gets only those. A code reviewer that should never edit files, for example, gets `["Read", "Grep", "Glob"]`
A tool you leave out isn't in the subagent's session at all: Claude works without it, with no permission prompt or error.
This example creates a read-only analysis agent that can examine code but can't modify files or run commands.
```python Python theme={null}
import asyncio
from claude_agent_sdk import query, ClaudeAgentOptions, AgentDefinition
async def main():
async for message in query(
prompt="Analyze the architecture of this codebase",
options=ClaudeAgentOptions(
allowed_tools=["Read", "Grep", "Glob", "Agent"],
agents={
"code-analyzer": AgentDefinition(
description="Static code analysis and architecture review",
prompt="""You are a code architecture analyst. Analyze code structure,
identify patterns, and suggest improvements without making changes.""",
# Read-only tools: no Edit, Write, or Bash access
tools=["Read", "Grep", "Glob"],
)
},
),
):
if hasattr(message, "result"):
print(message.result)
asyncio.run(main())
```
```typescript TypeScript theme={null}
import { query } from "@anthropic-ai/claude-agent-sdk";
for await (const message of query({
prompt: "Analyze the architecture of this codebase",
options: {
allowedTools: ["Read", "Grep", "Glob", "Agent"],
agents: {
"code-analyzer": {
description: "Static code analysis and architecture review",
prompt: `You are a code architecture analyst. Analyze code structure,
identify patterns, and suggest improvements without making changes.`,
// Read-only tools: no Edit, Write, or Bash access
tools: ["Read", "Grep", "Glob"]
}
}
}
})) {
if ("result" in message) console.log(message.result);
}
```
### Common tool combinations
| Use case | Tools | Description |
| :----------------- | :-------------------------------------- | :----------------------------------------------------------------- |
| Read-only analysis | `Read`, `Grep`, `Glob` | Can examine code but not modify or execute |
| Test execution | `Bash`, `Read`, `Grep` | Can run commands and analyze output |
| Code modification | `Read`, `Edit`, `Write`, `Grep`, `Glob` | Full read/write access without command execution |
| Full access | All tools | Inherits the tools available to subagents (omit the `tools` field) |
## Scale up with dynamic workflows
Subagents work well for a few delegated tasks per turn. For runs that coordinate dozens to hundreds of agents, use the `Workflow` tool, which moves the orchestration into a script the runtime executes outside the conversation context. See [dynamic workflows](/docs/en/workflows) for how workflows differ from turn-by-turn subagent delegation.
The `Workflow` tool is available in the TypeScript Agent SDK v0.3.149 and later. Include `Workflow` in `allowedTools` to auto-approve workflow runs. The tool input and output schemas are listed in the [TypeScript reference](/docs/en/agent-sdk/typescript#workflow).
## Troubleshooting
### Claude not delegating to subagents
If Claude completes tasks directly instead of delegating to your subagent:
* **Check Agent invocations are approved**: include `Agent` in `allowedTools` to auto-approve subagent calls. Without it, Agent invocations fall through to your `canUseTool` callback or, in `dontAsk` mode, are denied
* **Use explicit prompting**: mention the subagent by name in your prompt, for example "Use the code-reviewer agent to..."
* **Write a clear description**: explain exactly when to use the subagent so Claude can match tasks appropriately
### Filesystem-based agents not loading
Claude Code watches `~/.claude/agents/` and `.claude/agents/` and picks up a new or edited agent file within a few seconds, with no restart needed. If a definition never appears, work through these causes:
* **New `agents` directory**: the watcher covers only directories that existed when the session started, so the first file in a new directory needs a session restart. This is the most common cause.
* **Invalid frontmatter or a duplicate `name`**: check the file's YAML, and whether an existing agent already uses the `name`.
* **`--disable-slash-commands`**: sessions started with this flag don't watch these directories and always need a restart to load new files.
* **A programmatic agent with the same name**: `agents` passed to `query()` override a filesystem agent with the same name.
For the file format, see [how to write subagent files](/docs/en/sub-agents#write-subagent-files).
### Long prompt failures on Windows
On Windows, subagents with very long prompts may fail due to the command line length limit of 8191 characters. Keep prompts concise or use filesystem-based agents for complex instructions.
## Related documentation
* [Claude Code subagents](/docs/en/sub-agents): comprehensive subagent documentation including filesystem-based definitions
* [Dynamic workflows](/docs/en/workflows): orchestrate many subagents from a script for jobs too large for one conversation
* [SDK overview](/docs/en/agent-sdk/overview): getting started with the Claude Agent SDK