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Agent Skill · AI 工具

subagent-driven-development(子 Agent 驱动开发)

subagent-driven-development 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

subagent-driven-development 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在AI 工具类的 2,536 个 Skill 里排第 863。

总安装 1,794周安装 74GitHub Stars 891下载 586核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:subagent-driven-development(子 Agent 驱动开发)
来源仓库:https://github.com/neolabhq/context-engineering-kit
仓库路径:skills/subagent-driven-development
安装命令:
npx skills add https://github.com/neolabhq/context-engineering-kit --skill subagent-driven-development
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/neolabhq/context-engineering-kit --skill subagent-driven-development

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

subagent-driven-development 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合围绕仓库状态、代码变更或协作事项进行整理。通过 npx skills add 命令从指定仓库安装并使用该技能。安装前需确认权限范围、维护状态及是否会触发联网或文件操作。

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。

来源仓库内路径:skills/subagent-driven-development

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/neolabhq/context-engineering-kit --skill subag…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

subagent-driven-development 怎么安装?

在终端执行 npx skills add https://github.com/neolabhq/context-engineering-kit --skill subagent-driven…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

subagent-driven-development 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

subagent-driven-development 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

subagent-driven-development 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

subagent-driven-development 用的人多吗?

公开数据是累计安装 1,794 次,近一周安装 74 次,下载 586 次,GitHub 891 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

subagent-driven-development 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
subagent-driven-development

子 Agent 驱动开发 · 本页

1,794891只读MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Subagent-Driven Development

Create and execute plan by dispatching fresh subagent per task or issue, with code and output review after each or batch of tasks.

Core principle: Fresh subagent per task + review between or after tasks = high quality, fast iteration.

Executing Plans through agents:

  • Same session (no context switch)
  • Fresh subagent per task (no context pollution)
  • Code review after each or batch of task (catch issues early)
  • Faster iteration (no human-in-loop between tasks)

Supported types of execution

Sequential Execution

When you have a tasks or issues that are related to each other, and they need to be executed in order, investigating or modifying them sequentially is the best way to go.

Dispatch one agent per task or issue. Let it work sequentially. Review the output and code after each task or issue.

When to use:

  • Tasks are tightly coupled
  • Tasks should be executed in order

Parallel Execution

When you have multiple unrelated tasks or issues (different files, different subsystems, different bugs), investigatin or modifying them sequentially wastes time. Each task or investigation is independent and can happen in parallel.

Dispatch one agent per independent problem domain. Let them work concurrently.

When to use:

  • Tasks are mostly independent
  • Overral review can be done after all tasks are completed

Sequential Execution Process

1. Load Plan

Read plan file, create TodoWrite with all tasks.

2. Execute Task with Subagent

For each task:

Dispatch fresh subagent:

Task tool (general-purpose):
  description: "Implement Task N: [task name]"
  prompt: |
    You are implementing Task N from [plan-file].

    Read that task carefully. Your job is to:
    1. Implement exactly what the task specifies
    2. Write tests (following TDD if task says to)
    3. Verify implementation works
    4. Commit your work
    5. Report back

    Work from: [directory]

    Report: What you implemented, what you tested, test results, files changed, any issues

Subagent reports back with summary of work.

3. Review Subagent's Work

Dispatch code-reviewer subagent:

Task tool (superpowers:code-reviewer):
  Use template at requesting-code-review/code-reviewer.md

  WHAT_WAS_IMPLEMENTED: [from subagent's report]
  PLAN_OR_REQUIREMENTS: Task N from [plan-file]
  BASE_SHA: [commit before task]
  HEAD_SHA: [current commit]
  DESCRIPTION: [task summary]

Code reviewer returns: Strengths, Issues (Critical/Important/Minor), Assessment

4. Apply Review Feedback

If issues found:

  • Fix Critical issues immediately
  • Fix Important issues before next task
  • Note Minor issues

Dispatch follow-up subagent if needed:

"Fix issues from code review: [list issues]"

5. Mark Complete, Next Task

  • Mark task as completed in TodoWrite
  • Move to next task
  • Repeat steps 2-5

6. Final Review

After all tasks complete, dispatch final code-reviewer:

  • Reviews entire implementation
  • Checks all plan requirements met
  • Validates overall architecture

7. Complete Development

After final review passes:

  • Announce: "I'm using the finishing-a-development-branch skill to complete this work."
  • REQUIRED SUB-SKILL: Use superpowers:finishing-a-development-branch
  • Follow that skill to verify tests, present options, execute choice

Example Workflow

You: I'm using Subagent-Driven Development to execute this plan.

[Load plan, create TodoWrite]

Task 1: Hook installation script

[Dispatch implementation subagent]
Subagent: Implemented install-hook with tests, 5/5 passing

[Get git SHAs, dispatch code-reviewer]
Reviewer: Strengths: Good test coverage. Issues: None. Ready.

[Mark Task 1 complete]

Task 2: Recovery modes

[Dispatch implementation subagent]
Subagent: Added verify/repair, 8/8 tests passing

[Dispatch code-reviewer]
Reviewer: Strengths: Solid. Issues (Important): Missing progress reporting

[Dispatch fix subagent]
Fix subagent: Added progress every 100 conversations

[Verify fix, mark Task 2 complete]

...

[After all tasks]
[Dispatch final code-reviewer]
Final reviewer: All requirements met, ready to merge

Done!

Red Flags

Never:

  • Skip code review between tasks
  • Proceed with unfixed Critical issues
  • Dispatch multiple implementation subagents in parallel (conflicts)
  • Implement without reading plan task

If subagent fails task:

  • Dispatch fix subagent with specific instructions
  • Don't try to fix manually (context pollution)

Parallel Execution Process

Load plan, review critically, execute tasks in batches, report for review between batches.

Core principle: Batch execution with checkpoints for architect review.

Announce at start: "I'm using the executing-plans skill to implement this plan."

Step 1: Load and Review Plan

  1. Read plan file
  2. Review critically - identify any questions or concerns about the plan
  3. If concerns: Raise them with your human partner before starting
  4. If no concerns: Create TodoWrite and proceed

Step 2: Execute Batch

Default: First 3 tasks

For each task:

  1. Mark as in_progress
  2. Follow each step exactly (plan has bite-sized steps)
  3. Run verifications as specified
  4. Mark as completed

Step 3: Report

When batch complete:

  • Show what was implemented
  • Show verification output
  • Say: "Ready for feedback."

Step 4: Continue

Based on feedback:

  • Apply changes if needed
  • Execute next batch
  • Repeat until complete

Step 5: Complete Development

After all tasks complete and verified:

  • Announce: "I'm using the finishing-a-development-branch skill to complete this work."
  • REQUIRED SUB-SKILL: Use superpowers:finishing-a-development-branch
  • Follow that skill to verify tests, present options, execute choice

When to Stop and Ask for Help

STOP executing immediately when:

  • Hit a blocker mid-batch (missing dependency, test fails, instruction unclear)
  • Plan has critical gaps preventing starting
  • You don't understand an instruction
  • Verification fails repeatedly

Ask for clarification rather than guessing.

When to Revisit Earlier Steps

Return to Review (Step 1) when:

  • Partner updates the plan based on your feedback
  • Fundamental approach needs rethinking

Don't force through blockers - stop and ask.

Remember

  • Review plan critically first
  • Follow plan steps exactly
  • Don't skip verifications
  • Reference skills when plan says to
  • Between batches: just report and wait
  • Stop when blocked, don't guess

Parallel Investigation Process

Special case of parallel execution, when you have multiple unrelated failures that can be investigated without shared state or dependencies.

1. Identify Independent Domains

Group failures by what's broken:

  • File A tests: Tool approval flow
  • File B tests: Batch completion behavior
  • File C tests: Abort functionality

Each domain is independent - fixing tool approval doesn't affect abort tests.

2. Create Focused Agent Tasks

Each agent gets:

  • Specific scope: One test file or subsystem
  • Clear goal: Make these tests pass
  • Constraints: Don't change other code
  • Expected output: Summary of what you found and fixed

3. Dispatch in Parallel

// In Claude Code / AI environment
Task("Fix agent-tool-abort.test.ts failures")
Task("Fix batch-completion-behavior.test.ts failures")
Task("Fix tool-approval-race-conditions.test.ts failures")
// All three run concurrently

4. Review and Integrate

When agents return:

  • Read each summary
  • Verify fixes don't conflict
  • Run full test suite
  • Integrate all changes

Agent Prompt Structure

Good agent prompts are:

  1. Focused - One clear problem domain
  2. Self-contained - All context needed to understand the problem
  3. Specific about output - What should the agent return?
Fix the 3 failing tests in src/agents/agent-tool-abort.test.ts:

1. "should abort tool with partial output capture" - expects 'interrupted at' in message
2. "should handle mixed completed and aborted tools" - fast tool aborted instead of completed
3. "should properly track pendingToolCount" - expects 3 results but gets 0

These are timing/race condition issues. Your task:

1. Read the test file and understand what each test verifies
2. Identify root cause - timing issues or actual bugs?
3. Fix by:
   - Replacing arbitrary timeouts with event-based waiting
   - Fixing bugs in abort implementation if found
   - Adjusting test expectations if testing changed behavior

Do NOT just increase timeouts - find the real issue.

Return: Summary of what you found and what you fixed.

Common Mistakes

❌ Too broad: "Fix all the tests" - agent gets lost ✅ Specific: "Fix agent-tool-abort.test.ts" - focused scope

❌ No context: "Fix the race condition" - agent doesn't know where ✅ Context: Paste the error messages and test names

❌ No constraints: Agent might refactor everything ✅ Constraints: "Do NOT change production code" or "Fix tests only"

❌ Vague output: "Fix it" - you don't know what changed ✅ Specific: "Return summary of root cause and changes"

When NOT to Use

Related failures: Fixing one might fix others - investigate together first Need full context: Understanding requires seeing entire system Exploratory debugging: You don't know what's broken yet Shared state: Agents would interfere (editing same files, using same resources)

Real Example from Session

Scenario: 6 test failures across 3 files after major refactoring

Failures:

  • agent-tool-abort.test.ts: 3 failures (timing issues)
  • batch-completion-behavior.test.ts: 2 failures (tools not executing)
  • tool-approval-race-conditions.test.ts: 1 failure (execution count = 0)

Decision: Independent domains - abort logic separate from batch completion separate from race conditions

Dispatch:

Agent 1 → Fix agent-tool-abort.test.ts
Agent 2 → Fix batch-completion-behavior.test.ts
Agent 3 → Fix tool-approval-race-conditions.test.ts

Results:

  • Agent 1: Replaced timeouts with event-based waiting
  • Agent 2: Fixed event structure bug (threadId in wrong place)
  • Agent 3: Added wait for async tool execution to complete

Integration: All fixes independent, no conflicts, full suite green

Time saved: 3 problems solved in parallel vs sequentially

#Verification

After agents return:

  1. Review each summary - Understand what changed
  2. Check for conflicts - Did agents edit same code?
  3. Run full suite - Verify all fixes work together
  4. Spot check - Agents can make systematic errors

平台分布

Claude Code

26.19%
按下载量换算153

OpenCode

22.85%
按下载量换算134

Antigravity

17.43%
按下载量换算102

Gemini CLI

12.13%
按下载量换算71

Codex

7.68%
按下载量换算45

trae

3.69%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。

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