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ricardoroche
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code-review-framework

Apply a structured review framework to Python pull requests.

2|Updated Nov 13, 2025
Search Tags:#code quality#testing#code review#performance#feedback#security#maintainability#PR review
One-click install
npx skills add https://github.com/ricardoroche/ricardos-claude-code --skill code-review-framework
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-review-framework
Source: https://github.com/ricardoroche/ricardos-claude-code/tree/main/.claude/skills/code-review-framework
Command: npx skills add https://github.com/ricardoroche/ricardos-claude-code --skill code-review-framework

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pytest, httpx, pydantic.

What problem does it solve?

This Skill provides a comprehensive, structured framework for conducting code reviews, addressing issues like inconsistent feedback, missed critical bugs, and subjective comments. It ensures thorough evaluation across correctness, security, performance, and maintainability, leading to higher code quality and fewer post-release defects.

Core Features & Use Cases

  • Structured Checklist: Offers a detailed checklist covering correctness (error handling, edge cases), security (input validation, SQL injection), and performance (N+1 queries, async usage).
  • Severity & Categorization: Guides on categorizing comments by ReviewCategory (e.g., SECURITY, PERFORMANCE) and ReviewSeverity (BLOCKING, MAJOR, MINOR).
  • Specific Feedback: Emphasizes providing concrete suggestions with code examples, rather than vague comments.
  • Review Summary: Provides a template for summarizing review findings, including blocking issues, major concerns, and positive feedback.
  • Use Case: A senior engineer is reviewing a pull request for a critical backend service. This skill helps them systematically check for SQL injection vulnerabilities, N+1 query problems, and proper error handling, ensuring the code meets high standards before merging.

Quick Start

Review the attached Python code for correctness, security vulnerabilities, and performance issues, providing specific suggestions.

Frequently Asked Questions about code-review-framework

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I conduct consistent code reviews across my Python project?▼

Structured code reviews apply a standardized framework covering correctness, security, performance, and maintainability. This approach eliminates inconsistent feedback by using categorized review comments, severity levels (blocking, major, minor), and reusable checklists—ensuring every pull request receives thorough evaluation against the same criteria.

What should I check for when reviewing Python backend code for security vulnerabilities?▼

Security code reviews focus on input validation, SQL injection prevention, authentication boundaries, and data exposure. The framework provides specific checks and prompts reviewers to identify these vulnerabilities systematically, then document them with concrete code examples and actionable suggestions rather than vague comments.

How can I identify performance issues like N+1 queries during code review?▼

Performance reviews examine database query patterns, async/await usage, and computational complexity. A structured checklist guides reviewers to spot N+1 queries, inefficient loops, and missing optimizations, categorizing findings by severity so blocking performance regressions surface immediately for developers.

What's the best way to document code review feedback for a team?▼

Structured reviews generate summaries categorizing findings: blocking issues requiring fixes, major concerns needing attention, and positive feedback. This template format ensures reviewers communicate consistently, blocking issues are never missed, and developers receive actionable guidance tied to specific categories like security or maintainability.

Can I use this code review framework with pytest and httpx in my backend service?▼

Yes. The framework integrates with Python projects using pytest for testing and httpx for HTTP interactions. It works within your existing stack to apply structured review logic to pull requests in backend systems, generating categorized feedback via ReviewComment objects and severity enums.

Why should code reviews be categorized by type rather than treated as general comments?▼

Categorized reviews by type (correctness, security, performance, maintainability) ensure reviewers systematically cover all dimensions and stakeholders—security engineers, architects, and testers—know which findings matter to them. Severity levels (blocking, major, minor) surface critical issues immediately, preventing low-priority feedback from obscuring blocking problems.

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