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_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 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