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Feedback

This skill should be used when CodeRabbit code review feedback needs to be processed and fixed systematically. Use after running `coderabbit --plain` to automatically save feedback, analyze issues using MCP tools, and implement minimal code fixes with proper planning.

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SKILL.md

name coderabbit-fix-flow
description This skill should be used when CodeRabbit code review feedback needs to be processed and fixed systematically. Use after running `coderabbit --plain` to automatically save feedback, analyze issues using MCP tools, and implement minimal code fixes with proper planning.

CodeRabbit Fix Flow

Overview

This skill automates the workflow of processing CodeRabbit code review feedback by saving the review output to a timestamped document, then using MCP tools (sequential thinking and Exa context) to analyze and implement fixes with minimal code changes.

When to Use

Use this skill immediately after running coderabbit --plain or when you have CodeRabbit feedback that needs systematic processing. The skill handles type safety issues, code style violations, and other CodeRabbit-identified problems.

Workflow

Step 1: Execute CodeRabbit Review

Run the CodeRabbit review command in plain text mode:

coderabbit --plain

Step 2: Save Feedback Document

Save the CodeRabbit output to a timestamped QA document:

  • Create file: memory-bank/qa/coderabbit/cr-qa-{timestamp}.md
  • Include the full CodeRabbit output in the document
  • Add YAML front matter with metadata:
    ---
    title: "CodeRabbit QA Review - {timestamp}"
    link: "cr-qa-{timestamp}"
    type: "qa"
    tags:
      - code-review
      - coderabbit
      - type-safety
    created_at: "{timestamp}"
    updated_at: "{timestamp}"
    uuid: "{generate-uuid}"
    ---
    

Step 3: Analyze Issues with Sequential Thinking

Use the sequential thinking MCP tool to analyze all identified issues:

  1. Categorize issues by type (type safety, performance, style, security)
  2. Prioritize fixes (critical runtime issues first, then documentation)
  3. Plan minimal changes to achieve the fixes
  4. Identify dependencies between issues

Step 4: Get Best Practices Context

Use the Exa code context MCP tool to research current best practices for each issue type:

  • For type issues: "TypeScript type guards runtime validation best practices"
  • For Python type issues: "Python type annotations Optional None best practices"
  • For performance: "Performance optimization best practices [language]"
  • For security: "Security vulnerability fixes [language]"

Step 5: Implement Fixes Systematically

Execute the fixes following the sequential thinking plan:

  1. Create TodoWrite list tracking all issues
  2. Mark each issue as in_progress → completed
  3. Apply minimal code changes using best practices from Exa context
  4. Verify fixes address the root cause identified by CodeRabbit

Step 6: Validate and Document

Run validation as appropriate:

  • TypeScript: npm run build or tsc --noEmit
  • Python: mypy or ruff check
  • JavaScript: npm run lint or biome

Document the fixes in the QA document with:

  • What was fixed
  • How it was fixed
  • Validation results

Issue Type Patterns

Type Safety Issues

  • Use proper type guards instead of assertions
  • Apply Optional/Union types for nullable fields
  • Implement runtime validation where needed

Code Style Issues

  • Follow language-specific style guides
  • Use linting tools to verify fixes
  • Maintain consistency with existing codebase

Performance Issues

  • Research current optimization patterns
  • Implement minimal impactful changes
  • Measure before/after when possible

Security Issues

  • Understand the vulnerability context
  • Apply security best practices
  • Ensure fixes don't break functionality

Examples

Type Safety Fix Pattern

// Before (unsafe)
const data = response as ResearchDataShape;

// After (safe)
const data = isResearchDataShape(response) ? response : {} as ResearchDataShape;

Python Type Annotation Fix Pattern

# Before (incorrect)
timestamp: float = None
metadata: dict[str, Any] = None

# After (correct)
timestamp: float | None = None
metadata: dict[str, Any] | None = None

MCP Tool Usage

Sequential Thinking Tool

Use for:

  • Breaking down complex issues into steps
  • Planning fix order and dependencies
  • Analyzing multiple issues systematically

Exa Code Context Tool

Use for:

  • Getting current best practices
  • Understanding language-specific patterns
  • Finding optimal implementation approaches

Resources

This skill doesn't require bundled resources as it relies on MCP tools for context and the existing codebase for implementation.