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name: 'code-reviewer' description: 'Provides comprehensive code review feedback based on best practices, style guides, and potential bug detection. Use when the user requests a code review, asks for improvements to code, or needs to ensure code quality.' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:

• read_file
• run_shell_command

---

Code Review Skill

This skill helps to perform thorough code reviews, focusing on readability, maintainability, performance, security, and adherence to project-specific coding standards.

When to Use This Skill

• When a user explicitly asks for a "code review" of a file or set of files.
• When a user asks to "improve the quality" or "refactor" a piece of code.
• When a user submits code and asks for "feedback" or "suggestions".

Core Capabilities

1. Syntax and Style Check: Verify adherence to established coding standards (e.g., PEP 8 for Python, ESLint rules for JavaScript).
2. Best Practices: Identify deviations from common best practices for the given language/framework.
3. Potential Bugs/Errors: Highlight common pitfalls, edge cases, or logical errors.
4. Performance Optimization: Suggest areas where code could be made more efficient.
5. Security Vulnerabilities: Point out potential security risks.
6. Readability and Maintainability: Provide feedback on code clarity, comments, variable naming, and overall structure.
7. Testability: Assess if the code is easily testable and suggest improvements.

Workflow

1. Identify Scope: Determine which files or code snippets are part of the review request.
2. Read Code: Use

   read_file

   to access the content of the specified files.
3. Analyze:
   • Apply language-specific linting/static analysis tools if available (e.g.,

     pylint

     ,

     flake8

     ,

     eslint

     ).
   • Perform a semantic analysis based on the description and context.
   • Cross-reference with project-specific style guides or documentation if linked in

     references/

     .
4. Generate Feedback:
   • Structure feedback clearly, categorizing by type (e.g., "Style", "Potential Bug", "Suggestion").
   • Provide specific line numbers or code snippets for each piece of feedback.
   • Explain why a change is suggested and, if possible, offer a concrete example of how to fix it.
   • Prioritize critical issues (bugs, security) over stylistic suggestions.
5. Present Review: Output the comprehensive review to the user.

Example Usage

User Prompt: "Please review

src/main.py

for any issues."

Agent Action:

1. read_file("src/main.py")

2. Run

   pylint src/main.py

   (if configured).
3. Analyze code content.
4. Generate a markdown-formatted review with findings.

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