code-reviewer

Analyze pull request diffs and generate prioritized review reports.

Updated Jun 2, 2026
One-click install
npx skills add https://github.com/ano4l/SiteRent --skill code-reviewer-ano4l
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: code-reviewer
Source: https://github.com/ano4l/SiteRent/tree/main/skills/code-reviewer
Command: npx skills add https://github.com/ano4l/SiteRent --skill code-reviewer-ano4l

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

PR reviews are time-consuming and error-prone; this Skill automates analysis of diffs, quality metrics, and risk signals to produce structured, actionable insights for faster, safer code reviews.

Core Features & Use Cases

  • Automated PR risk scoring based on file categories, changes, and inline risk patterns.
  • Cross-language code quality checks and SOLID-violation detection.
  • Generate concise review reports with actionable items and suggested review order.
  • Use-case: teams seeking consistent, scalable PR evaluation across multiple languages.

Quick Start

Run automated PR analysis on a repository to produce a prioritized review report.

Frequently Asked Questions about code-reviewer

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

FAQPage Schema
How do I automate PR analysis to detect code quality risks across multiple languages?

Automated PR analysis evaluates file categories, inline risk patterns, and cross-language code smells to detect code quality risks. It applies static analysis directly to repository diffs, producing structured insights for evaluating changes and potential SOLID violations safely.

What is the best way to generate actionable code review reports from GitHub-like workflows?

The best way to generate actionable code review reports is by analyzing diffs for risk patterns and code smells. This process produces concise outputs with a suggested review order, prioritizing files based on risk scoring to accelerate evaluation in GitHub-like workflows.

Can I use cross-language static analysis to identify SOLID violations in repository diffs?

Yes, cross-language static analysis can identify SOLID violations by evaluating repository diffs. It applies quality checks across multiple programming languages, targeting specific inline risk patterns and changes to ensure consistent evaluation regardless of the codebase's language mix.

Does automated code review provide risk scoring for changed files in a pull request?

Automated code review provides risk scoring by categorizing changed files and analyzing inline risk patterns within the pull request. This scoring mechanism helps prioritize the review order, highlighting files with the most significant quality risks and code smells first.

How do I identify code smells and risk patterns in diffs without manual inspection?

To identify code smells and risk patterns in diffs without manual inspection, you apply automated static analysis to the changes. This evaluates the diff against known risk patterns and quality metrics, generating a prioritized report of actionable items automatically.