How does the skill handle security checks?

The skill scans for hardcoded secrets, validates input handling, and identifies unsafe operations or memory safety violations within the changes.

What is the output format of a PR review?

It generates a structured report containing a Summary, Strengths, Issues Found, Suggestions, Questions, and a clear Verdict (Approve/Request Changes).

What languages does this PR review skill support?

While it can review any code, it features specialized checklists for Python and Mojo (v0.25.7+), including memory safety and SIMD performance patterns.

Does this skill require the GitHub CLI?

Yes, it uses the 'gh' command-line tool to fetch PR diffs, file statistics, and description metadata for a thorough analysis.

Review PR Changes

Name: Review PR Changes
Author: mvillmow

bymvillmow

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协作工具

Conducts structured code reviews for Pull Requests using a comprehensive quality and standards checklist.

关于

Review PR Changes is a specialized capability designed to automate and standardize the code review process. It evaluates Pull Requests against rigorous project standards, covering code quality, testing coverage, documentation, and security. It is particularly optimized for modern Mojo and Python environments, ensuring that changes adhere to specific syntax requirements like Mojo v0.25.7+. By integrating with the GitHub CLI, it provides a structured report that identifies logic errors, architectural impacts, and compliance issues, streamlining the path from submission to approval.

主要功能

Specific validation for modern Mojo syntax and memory management patterns
GitHub CLI integration for automated diff and metadata analysis
Standardized reporting format including strengths, issues, and final verdicts
Comprehensive multi-category checklists for quality, testing, and security
Verification of Git standards and conventional commit compliance
8 GitHub stars

使用场景

Automating the first pass of code reviews to identify standard violations before human intervention
Ensuring rigorous test coverage and documentation for complex AI paper implementations
Validating high-performance Mojo code for memory safety and architectural consistency

关于

主要功能

Specific validation for modern Mojo syntax and memory management patterns
GitHub CLI integration for automated diff and metadata analysis
Standardized reporting format including strengths, issues, and final verdicts
Comprehensive multi-category checklists for quality, testing, and security
Verification of Git standards and conventional commit compliance
8 GitHub stars

使用场景

Automating the first pass of code reviews to identify standard violations before human intervention
Ensuring rigorous test coverage and documentation for complex AI paper implementations
Validating high-performance Mojo code for memory safety and architectural consistency