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面向代码评审反馈的自动化实施能力,能够解析评审意见、生成可执行任务清单,并按规范逐项修改代码、更新文档或补充测试,全程跟踪进度并确保变更符合项目约定与质量标准。
简介
面向代码评审反馈的自动化实施能力,能够解析评审意见、生成可执行任务清单,并按规范逐项修改代码、更新文档或补充测试,全程跟踪进度并确保变更符合项目约定与质量标准。
核心能力速览
✓所属分类:⚡️ 效率工具
✓通过 Agent Skills 协议,将「能力」封装为可复用、可安装的 AI 组件
✓支持按需加载领域知识与工具,让通用模型转变为特定任务的专家
适用场景
适用于「⚡️ 效率工具」相关场景,可作为可复用的 AI 能力组件,接入支持 Agent Skills 的 AI 客户端(如 Claude、Cursor、Cline 等),按需调用以扩展模型能力。
Skills.MD
| name | review-implementing |
| description | Process and implement code review feedback systematically. Use when user provides reviewer comments, PR feedback, code review notes, or asks to implement suggestions from reviews. |
Review Feedback Implementation
Systematically process and implement changes based on code review feedback.
When to Use
- Provides reviewer comments or feedback
- Pastes PR review notes
- Mentions implementing review suggestions
- Says "address these comments" or "implement feedback"
- Shares list of changes requested by reviewers
Systematic Workflow
1. Parse Reviewer Notes
Identify individual feedback items:
- Split numbered lists (1., 2., etc.)
- Handle bullet points or unnumbered feedback
- Extract distinct change requests
- Clarify ambiguous items before starting
2. Create Todo List
Use TodoWrite tool to create actionable tasks:
- Each feedback item becomes one or more todos
- Break down complex feedback into smaller tasks
- Make tasks specific and measurable
- Mark first task as
in_progressbefore starting
Example:
- Add type hints to extract function
- Fix duplicate tag detection logic
- Update docstring in chain.py
- Add unit test for edge case
3. Implement Changes Systematically
For each todo item:
Locate relevant code:
- Use Grep to search for functions/classes
- Use Glob to find files by pattern
- Read current implementation
Make changes:
- Use Edit tool for modifications
- Follow project conventions (CLAUDE.md)
- Preserve existing functionality unless changing behavior
Verify changes:
- Check syntax correctness
- Run relevant tests if applicable
- Ensure changes address reviewer's intent
Update status:
- Mark todo as
completedimmediately after finishing - Move to next todo (only one
in_progressat a time)
4. Handle Different Feedback Types
Code changes:
- Use Edit tool for existing code
- Follow type hint conventions (PEP 604/585)
- Maintain consistent style
New features:
- Create new files with Write tool if needed
- Add corresponding tests
- Update documentation
Documentation:
- Update docstrings following project style
- Modify markdown files as needed
- Keep explanations concise
Tests:
- Write tests as functions, not classes
- Use descriptive names
- Follow pytest conventions
Refactoring:
- Preserve functionality
- Improve code structure
- Run tests to verify no regressions
5. Validation
After implementing changes:
- Run affected tests
- Check for linting errors:
uv run ruff check - Verify changes don't break existing functionality
6. Communication
Keep user informed:
- Update todo list in real-time
- Ask for clarification on ambiguous feedback
- Report blockers or challenges
- Summarize changes at completion
Edge Cases
Conflicting feedback:
- Ask user for guidance
- Explain conflict clearly
Breaking changes required:
- Notify user before implementing
- Discuss impact and alternatives
Tests fail after changes:
- Fix tests before marking todo complete
- Ensure all related tests pass
Referenced code doesn't exist:
- Ask user for clarification
- Verify understanding before proceeding
Important Guidelines
- Always use TodoWrite for tracking progress
- Mark todos completed immediately after each item
- Only one todo in_progress at any time
- Don't batch completions - update status in real-time
- Ask questions for unclear feedback
- Run tests if changes affect tested code
- Follow CLAUDE.md conventions for all code changes
- Use conventional commits if creating commits afterward
快捷安装
在终端执行以下命令,即可将本 Skill 安装到本地 AI 客户端:
npx skills add mhattingpete/claude-skills-marketplace