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create-subagents创建子 Agent

Agent Skill

create-subagents 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

294

周安装

12

GitHub Stars

16

下载量

95
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:create-subagents(创建子 Agent)
来源仓库:https://github.com/cfircoo/claude-code-toolkit
仓库路径:skills/create-subagents
安装命令:
npx skills add https://github.com/cfircoo/claude-code-toolkit --skill create-subagents
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/cfircoo/claude-code-toolkit --skill create-subagents

简介

create-subagents 用于创建可自主运行的特殊化子代理,完成无需用户干预的复杂任务。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 等宿主环境,适合批处理与自动化场景。
  • 支持指定工具集、模型与系统提示词,返回最终结果至主对话流。
  • 安装前请确认权限范围、维护状态及是否会触发外部工具调用与日志记录操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Subagents enable delegation of complex tasks to specialized agents that operate autonomously without user interaction, returning their final output to the main conversation.

<quick_start>

  1. Run /agents command
  2. Select "Create New Agent"
  3. Choose project-level (.claude/agents/) or user-level (~/.claude/agents/)
  4. Define the subagent:

- name: lowercase-with-hyphens - description: When should this subagent be used? - tools: Optional comma-separated list (inherits all if omitted) - model: Optional (sonnet, opus, haiku, or inherit)

  1. Write the system prompt (the subagent's instructions)

<focus_areas>

  • Code quality and maintainability
  • Security vulnerabilities
  • Performance issues
  • Best practices adherence </focus_areas>

<output_format> Provide specific, actionable feedback with file:line references. </output_format>

</example>
</quick_start>

<file_structure>
| Type | Location | Scope | Priority |
|------|----------|-------|----------|
| **Project** | `.claude/agents/` | Current project only | Highest |
| **User** | `~/.claude/agents/` | All projects | Lower |
| **Plugin** | Plugin's `agents/` dir | All projects | Lowest |

Project-level subagents override user-level when names conflict.
</file_structure>

<configuration>
<field name="name">
- Lowercase letters and hyphens only
- Must be unique
</field>

<field name="description">
- Natural language description of purpose
- Include when Claude should invoke this subagent
- Used for automatic subagent selection
</field>

<field name="tools">
- Comma-separated list: `Read, Write, Edit, Bash, Grep`
- If omitted: inherits all tools from main thread
- Use `/agents` interface to see all available tools
</field>

<field name="model">
- `sonnet`, `opus`, `haiku`, or `inherit`
- `inherit`: uses same model as main conversation
- If omitted: defaults to configured subagent model (usually sonnet)
</field>
</configuration>

<execution_model>
<critical_constraint>
**Subagents are black boxes that cannot interact with users.**

Subagents run in isolated contexts and return their final output to the main conversation. They:
- ✅ Can use tools like Read, Write, Edit, Bash, Grep, Glob
- ✅ Can access MCP servers and other non-interactive tools
- ❌ **Cannot use AskUserQuestion** or any tool requiring user interaction
- ❌ **Cannot present options or wait for user input**
- ❌ **User never sees subagent's intermediate steps**

The main conversation sees only the subagent's final report/output.
</critical_constraint>

<workflow_design>
**Designing workflows with subagents:**

Use **main chat** for:
- Gathering requirements from user (AskUserQuestion)
- Presenting options or decisions to user
- Any task requiring user confirmation/input
- Work where user needs visibility into progress

Use **subagents** for:
- Research tasks (API documentation lookup, code analysis)
- Code generation based on pre-defined requirements
- Analysis and reporting (security review, test coverage)
- Context-heavy operations that don't need user interaction

**Example workflow pattern:**

Main Chat: Ask user for requirements (AskUserQuestion) ↓ Subagent: Research API and create documentation (no user interaction) ↓ Main Chat: Review research with user, confirm approach ↓ Subagent: Generate code based on confirmed plan ↓ Main Chat: Present results, handle testing/deployment

</workflow_design>
</execution_model>

<system_prompt_guidelines>
<principle name="be_specific">
Clearly define the subagent's role, capabilities, and constraints.
</principle>

<principle name="use_pure_xml_structure">
Structure the system prompt with pure XML tags. Remove ALL markdown headings from the body.

name: security-reviewer description: Reviews code for security vulnerabilities tools: Read, Grep, Glob, Bash model: sonnet


<role> You are a senior code reviewer specializing in security. </role>

<focus_areas>

  • SQL injection vulnerabilities
  • XSS attack vectors
  • Authentication/authorization issues
  • Sensitive data exposure

</focus_areas>

<workflow>

  1. Read the modified files
  2. Identify security risks
  3. Provide specific remediation steps
  4. Rate severity (Critical/High/Medium/Low)

</workflow>


❌ Bad: "You are a helpful assistant that helps with code" ✅ Good: "You are a React component refactoring specialist. Analyze components for hooks best practices, performance anti-patterns, and accessibility issues." </system_prompt_guidelines>

<subagent_xml_structure> Subagent.md files are system prompts consumed only by Claude. Like skills and slash commands, they should use pure XML structure for optimal parsing and token efficiency.

<recommended_tags> Common tags for subagent structure:

- `<role>` - Who the subagent is and what it does
- `<constraints>` - Hard rules (NEVER/MUST/ALWAYS)
- `<focus_areas>` - What to prioritize
- `<workflow>` - Step-by-step process
- `<output_format>` - How to structure deliverables
- `<success_criteria>` - Completion criteria
- `<validation>` - How to verify work </recommended_tags>

<intelligence_rules> **Simple subagents** (single focused task):

- Use role + constraints + workflow minimum
- Example: code-reviewer, test-runner

**Medium subagents** (multi-step process):

- Add workflow steps, output_format, success_criteria
- Example: api-researcher, documentation-generator

**Complex subagents** (research + generation + validation):

- Add all tags as appropriate including validation, examples
- Example: mcp-api-researcher, comprehensive-auditor </intelligence_rules>

<critical_rule> **Remove ALL markdown headings (##, ###) from subagent body.** Use semantic XML tags instead.

Keep markdown formatting WITHIN content (bold, italic, lists, code blocks, links).

For XML structure principles and token efficiency details, see @skills/create-agent-skills/references/use-xml-tags.md - the same principles apply to subagents. </critical_rule> </subagent_xml_structure>
Use the code-reviewer subagent to check my recent changes
Have the test-writer subagent create tests for the new API endpoints

<manual_editing> You can also edit subagent files directly:

- Project: `.claude/agents/subagent-name.md`
- User: `~/.claude/agents/subagent-name.md` </manual_editing>

**Subagent usage and configuration**: [references/subagents.md](https://github.com/cfircoo/claude-code-toolkit/blob/HEAD/skills/create-subagents/references/subagents.md)

- File format and configuration
- Model selection (Sonnet 4.5 + Haiku 4.5 orchestration)
- Tool security and least privilege
- Prompt caching optimization
- Complete examples

**Writing effective prompts**: [references/writing-subagent-prompts.md](https://github.com/cfircoo/claude-code-toolkit/blob/HEAD/skills/create-subagents/references/writing-subagent-prompts.md)

- Core principles and XML structure
- Description field optimization for routing
- Extended thinking for complex reasoning
- Security constraints and strong modal verbs
- Success criteria definition

**Advanced topics**:

**Evaluation and testing**: [references/evaluation-and-testing.md](https://github.com/cfircoo/claude-code-toolkit/blob/HEAD/skills/create-subagents/references/evaluation-and-testing.md)

- Evaluation metrics (task completion, tool correctness, robustness)
- Testing strategies (offline, simulation, online monitoring)
- Evaluation-driven development
- G-Eval for custom criteria

**Error handling and recovery**: [references/error-handling-and-recovery.md](https://github.com/cfircoo/claude-code-toolkit/blob/HEAD/skills/create-subagents/references/error-handling-and-recovery.md)

- Common failure modes and causes
- Recovery strategies (graceful degradation, retry, circuit breakers)
- Structured communication and observability
- Anti-patterns to avoid

**Context management**: [references/context-management.md](https://github.com/cfircoo/claude-code-toolkit/blob/HEAD/skills/create-subagents/references/context-management.md)

- Memory architecture (STM, LTM, working memory)
- Context strategies (summarization, sliding window, scratchpads)
- Managing long-running tasks
- Prompt caching interaction

**Orchestration patterns**: [references/orchestration-patterns.md](https://github.com/cfircoo/claude-code-toolkit/blob/HEAD/skills/create-subagents/references/orchestration-patterns.md)

- Sequential, parallel, hierarchical, coordinator patterns
- Sonnet + Haiku orchestration for cost/performance
- Multi-agent coordination
- Pattern selection guidance

**Debugging and troubleshooting**: [references/debugging-agents.md](https://github.com/cfircoo/claude-code-toolkit/blob/HEAD/skills/create-subagents/references/debugging-agents.md)

- Logging, tracing, and correlation IDs
- Common failure types (hallucinations, format errors, tool misuse)
- Diagnostic procedures
- Continuous monitoring

<success_criteria> A well-configured subagent has:

- Valid YAML frontmatter (name matches file, description includes triggers)
- Clear role definition in system prompt
- Appropriate tool restrictions (least privilege)
- XML-structured system prompt with role, approach, and constraints
- Description field optimized for automatic routing
- Successfully tested on representative tasks
- Model selection appropriate for task complexity (Sonnet for reasoning, Haiku for simple tasks) </success_criteria>

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

29.47%
按下载量换算28

windsurf

20.98%
按下载量换算20

OpenCode

17.17%
按下载量换算16

Codex

12.14%
按下载量换算12

Antigravity

7.06%
按下载量换算7

Gemini CLI

3%
按下载量换算3

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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