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Agent Skill · 研究检索

do(做)

do 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。

do 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 38,548。

总安装 1,544周安装 65GitHub Stars 2,583下载 541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:do(做)
来源仓库:https://github.com/cexll/myclaude
仓库路径:skills/do
安装命令:
npx skills add https://github.com/cexll/myclaude --skill do
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/cexll/myclaude --skill do

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

do 是系统化功能开发编排器,通过代码代理驱动实现任务分解与执行流程管理。适用于需要结构化拆解需求、分派子任务并跟踪交付进度的复杂项目开发。自动创建任务目录结构,生成 YAML 元数据和 Markdown 正文分离的需求文档。安装后需配置代理包装脚本,注意任务目录写入权限和项目工作树隔离机制。

do 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/do

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/cexll/myclaude --skill do;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

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

do 怎么安装?

在终端执行 npx skills add https://github.com/cexll/myclaude --skill do。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

do 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。

do 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

do 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。

do 用的人多吗?

公开数据是累计安装 1,544 次,近一周安装 65 次,下载 541 次,GitHub 2,583 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。

do 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。
  • 来源仓库有 2,583 星,维护活跃度相对可查。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
do

做 · 本页

1,5442,583接触敏感数据MIT有提醒

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

do - Feature Development Orchestrator

An orchestrator for systematic feature development. Invoke agents via codeagent-wrapper, never write code directly.

Loop Initialization (REQUIRED)

When triggered via /do <task>, initialize the task directory immediately without asking about worktree:

python3 "$HOME/.claude/skills/do/scripts/setup-do.py" "<task description>"

This creates a task directory under .claude/do-tasks/ with:

  • task.md: Single file containing YAML frontmatter (metadata) + Markdown body (requirements/context)

Worktree decision is deferred until Phase 4 (Implement). Phases 1-3 are read-only and do not require worktree isolation.

Task Directory Management

Use task.py to manage task state:

# Update phase
python3 "$HOME/.claude/skills/do/scripts/task.py" update-phase 2

# Check status
python3 "$HOME/.claude/skills/do/scripts/task.py" status

# List all tasks
python3 "$HOME/.claude/skills/do/scripts/task.py" list

Worktree Mode

The worktree is created only when needed (right before Phase 4: Implement). If the user chooses worktree mode:

  1. Run setup with --worktree flag to create the worktree: python3 "$HOME/.claude/skills/do/scripts/setup-do.py" --worktree "<task description>"
  2. Use the DO_WORKTREE_DIR environment variable to direct codeagent-wrapper develop agent into the worktree. Do NOT pass --worktree to subsequent calls — that creates a new worktree each time.
# Save the worktree path from setup output, then prefix all develop calls:
DO_WORKTREE_DIR=<worktree_dir> codeagent-wrapper --agent develop - . <<'EOF'
...
EOF

Read-only agents (code-explorer, code-architect, code-reviewer) do NOT need DO_WORKTREE_DIR.

Hard Constraints

  1. Never write code directly. Delegate all code changes to codeagent-wrapper agents.
  2. Parallel-first. Run independent tasks via codeagent-wrapper --parallel.
  3. Update phase after each phase. Use task.py update-phase <N>.
  4. Expect long-running codeagent-wrapper calls. High-reasoning modes can take a long time.
  5. Timeouts are not an escape hatch. If a call times out, retry with narrower scope.
  6. Defer worktree decision until Phase 4. Only ask about worktree mode right before implementation. If enabled, prefix develop agent calls with DO_WORKTREE_DIR=<path>. Never pass --worktree after initialization.

Agents

AgentPurposeNeeds --worktree
code-explorerTrace code, map architecture, find patternsNo (read-only)
code-architectDesign approaches, file plans, build sequencesNo (read-only)
code-reviewerReview for bugs, simplicity, conventionsNo (read-only)
developImplement code, run testsYes — use DO_WORKTREE_DIR env prefix

Issue Severity Definitions

Blocking issues (require user input):

  • Impacts core functionality or correctness
  • Security vulnerabilities
  • Architectural conflicts with existing patterns
  • Ambiguous requirements with multiple valid interpretations

Minor issues (auto-fix without asking):

  • Code style inconsistencies
  • Naming improvements
  • Missing documentation
  • Non-critical test coverage gaps

5-Phase Workflow

Phase 1: Understand (Parallel, No Interaction)

Goal: Understand requirements and map codebase simultaneously.

Actions: Run code-architect and 2-3 code-explorer tasks in parallel.

codeagent-wrapper --parallel <<'EOF'
---TASK---
id: p1_requirements
agent: code-architect
workdir: .
---CONTENT---
Analyze requirements completeness (score 1-10):
1. Extract explicit requirements, constraints, acceptance criteria
2. Identify blocking questions (issues that prevent implementation)
3. Identify minor clarifications (nice-to-have but can proceed without)

Output format:
- Completeness score: X/10
- Requirements: [list]
- Non-goals: [list]
- Blocking questions: [list, if any]

---TASK---
id: p1_similar_features
agent: code-explorer
workdir: .
---CONTENT---
Find 1-3 similar features, trace end-to-end. Return: key files with line numbers, call flow, extension points.

---TASK---
id: p1_architecture
agent: code-explorer
workdir: .
---CONTENT---
Map architecture for relevant subsystem. Return: module map + 5-10 key files.

---TASK---
id: p1_conventions
agent: code-explorer
workdir: .
---CONTENT---
Identify testing patterns, conventions, config. Return: test commands + file locations.
EOF

Phase 2: Clarify (Conditional)

Goal: Resolve blocking ambiguities only.

Actions:

  1. Review p1_requirements output for blocking questions
  2. IF blocking questions exist → Use AskUserQuestion
  3. IF no blocking questions (completeness >= 8) → Skip to Phase 3

Phase 3: Design (No Interaction)

Goal: Produce minimal-change implementation plan.

codeagent-wrapper --agent code-architect - . <<'EOF'
Design minimal-change implementation:
- Reuse existing abstractions
- Minimize new files
- Follow established patterns from Phase 1 exploration

Output:
- File touch list with specific changes
- Build sequence
- Test plan
- Risks and mitigations
EOF

Phase 4: Implement + Review

Goal: Build feature and review in one phase.

Step 1: Decide on worktree mode (ONLY NOW)

Use AskUserQuestion to ask:

Develop in a separate worktree? (Isolates changes from main branch)
- Yes (Recommended for larger changes)
- No (Work directly in current directory)

If user chooses worktree:

python3 "$HOME/.claude/skills/do/scripts/setup-do.py" --worktree "<task description>"
# Save the worktree path from output for DO_WORKTREE_DIR

Step 2: Invoke develop agent

For full-stack projects, split into backend/frontend tasks with per-task skills: injection. Use --parallel when tasks can be split; use single agent when the change is small or single-domain.

Single-domain example (prefix with DO_WORKTREE_DIR if worktree enabled):

# With worktree:
DO_WORKTREE_DIR=<worktree_dir> codeagent-wrapper --agent develop --skills golang-base-practices - . <<'EOF'
Implement with minimal change set following the Phase 3 blueprint.
- Follow Phase 1 patterns
- Add/adjust tests per Phase 3 plan
- Run narrowest relevant tests
EOF

# Without worktree:
codeagent-wrapper --agent develop --skills golang-base-practices - . <<'EOF'
Implement with minimal change set following the Phase 3 blueprint.
- Follow Phase 1 patterns
- Add/adjust tests per Phase 3 plan
- Run narrowest relevant tests
EOF

Full-stack parallel example (adapt task IDs, skills, and content based on Phase 3 design):

# With worktree:
DO_WORKTREE_DIR=<worktree_dir> codeagent-wrapper --parallel <<'EOF'
---TASK---
id: p4_backend
agent: develop
workdir: .
skills: golang-base-practices
---CONTENT---
Implement backend changes following Phase 3 blueprint.
- Follow Phase 1 patterns
- Add/adjust tests per Phase 3 plan

---TASK---
id: p4_frontend
agent: develop
workdir: .
skills: frontend-design,vercel-react-best-practices
dependencies: p4_backend
---CONTENT---
Implement frontend changes following Phase 3 blueprint.
- Follow Phase 1 patterns
- Add/adjust tests per Phase 3 plan
EOF

# Without worktree: remove DO_WORKTREE_DIR prefix

Note: Choose which skills to inject based on Phase 3 design output. Only inject skills relevant to each task's domain.

Step 3: Review

Step 3: Review

Run parallel reviews:

codeagent-wrapper --parallel <<'EOF'
---TASK---
id: p4_correctness
agent: code-reviewer
workdir: .
---CONTENT---
Review for correctness, edge cases, failure modes.
Classify each issue as BLOCKING or MINOR.

---TASK---
id: p4_simplicity
agent: code-reviewer
workdir: .
---CONTENT---
Review for KISS: remove bloat, collapse needless abstractions.
Classify each issue as BLOCKING or MINOR.
EOF

Step 4: Handle review results

  • MINOR issues only → Auto-fix via develop, no user interaction
  • BLOCKING issues → Use AskUserQuestion: "Fix now / Proceed as-is"

Phase 5: Complete (No Interaction)

Goal: Document what was built.

codeagent-wrapper --agent code-reviewer - . <<'EOF'
Write completion summary:
- What was built
- Key decisions/tradeoffs
- Files modified (paths)
- How to verify (commands)
- Follow-ups (optional)
EOF

Output the completion signal:

<promise>DO_COMPLETE</promise>

平台分布

OpenCode

26.21%
按下载量换算142

Claude Code

21.27%
按下载量换算115

Codex

18.93%
按下载量换算102

Cursor

11.86%
按下载量换算64

windsurf

7.62%
按下载量换算41

Antigravity

3.68%
按下载量换算20

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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