Review Feedback Implementation

Systematically process and implement changes based on code review feedback.

When to Use

Automatically activate when the user:

• •Provides reviewer comments or feedback
• •Pastes PR review notes
• •Mentions implementing review suggestions
• •Says "address these comments" or "implement feedback"
• •Shares a 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 any 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_progress before 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 completed immediately after finishing
• •Move to next todo (only one in_progress at 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 the 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

Example

User: "Implement these review comments:

1. •Add type hints to the extract function
2. •Fix the duplicate tag detection logic
3. •Update the docstring in chain.py"

Actions:

1. •Create TodoWrite with 3 items
2. •Mark item 1 as in_progress
3. •Grep for extract function
4. •Read file containing function
5. •Edit to add type hints
6. •Mark item 1 completed
7. •Mark item 2 in_progress
8. •Repeat process for remaining items
9. •Summarize all changes made