Code reviewer
Skill learn-with-santosh/claude-master-skills/skills/code-reviewer
A curated collection of specialized skills and workflows designed to enhance Claude's capabilities in specific domains. These skills provide frameworks, psychological triggers, and structured processes to deliver high-quality, professional results.
npx -y skills add learn-with-santosh/claude-master-skills --skill code-reviewerAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
What its author says it does
Copied from the file, not written here
Performs deep, professional code reviews. Use this skill whenever a user wants to "review this code", "check for bugs", "improve quality", or needs a second pair of eyes on a Pull Request. This skill focuses on performance, security, maintainability, and clean code principles.
SKILL.md
2.8 KB, as published. Nobody here has run it
Code Reviewer Pro 🔍
This skill acts as a Senior Staff Engineer reviewing your work. It provides constructive, actionable feedback to elevate code quality and catch issues before they reach production.
When to use this skill
Use this skill when:
- Reviewing a new feature before submission.
- Refactoring complex logic.
- Hunting for performance bottlenecks.
- Checking for security vulnerabilities.
- Ensuring consistency with project standards.
Review Framework: The "Four Pillars"
Every review must evaluate the code across these four categories:
1. Correctness & Security
- Does it actually work as intended?
- Are there edge cases (nulls, empty lists, timeouts)?
- Any security risks (SQL injection, XSS, exposed secrets)?
2. Performance & Scalability
- Big O complexity of new algorithms.
- Unnecessary re-renders or API calls.
- Memory leaks or resource management issues.
3. Maintainability & Readability
- Is the naming descriptive and consistent?
- Is the logic too "clever" or hard to follow?
- Does it follow the DRY (Don't Repeat Yourself) principle?
- Proper documentation/comments for complex blocks.
4. Project Specifics
- Does it follow the patterns defined in
CLAUDE.md? - Are tests included and sufficient?
Output Format
📝 Executive Summary
A quick overview of the review (e.g., "LGTM" or "Major concerns found").
🔴 Critical Issues
High-priority bugs or security risks that MUST be fixed.
🟡 Improvements
Suggestions for better performance or cleaner code.
🟢 Nitpicks
Minor stylistic suggestions or optional refactors.
💡 Refactored Version (Optional)
Provide a code block showing how the most complex part could be improved.
Examples
Example 1: Catching a Race Condition
Input: [Code snippet with an async loop]
Output:
"🔴 Critical: You are using forEach with an async callback. This won't wait for the promises to resolve.
Fix: Use for...of or Promise.all() to ensure execution order and completion."
Example 2: Performance Improvement
Input: [React component with heavy calculation in render]
Output:
"🟡 Improvement: The calculation of filteredData runs on every render.
Fix: Wrap it in useMemo with data as a dependency to avoid unnecessary recalculations."
Best Practices
- Be Respectful: Frame feedback as "we" or "the code" rather than "you."
- Provide Rationale: Explain why a change is recommended.
- Prioritize: Don't bury critical bugs under minor nitpicks.