code-review

Name: code-review
Availability: InStock
Author: rockandrolla

Analyze Python codebases and produce a severity-ranked Markdown report.

Updated Feb 26, 2026

Search Tags:#architecture #python #quality #static-analysis #lint #code-review

Ready to run

npx skills add https://github.com/rockandrolla13/blueprint --skill code-review-rockandrolla13

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-review
Source: https://github.com/rockandrolla13/blueprint/tree/main/code-review
Command: npx skills add https://github.com/rockandrolla13/blueprint --skill code-review-rockandrolla13

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyzes Python codebases to detect correctness issues, readability gaps, and convention violations, and outputs a severity-ranked Markdown report.

Core Features & Use Cases

Ingests code from repository files, analyzes for common bugs, style violations, and architecture concerns, and produces a concise report.
Generates an executive summary and a prioritized list of findings suitable for handoff to a refactor plan.
Use Case: Before a release, run code-review to surface critical defects and maintainability risks.

Quick Start

Ask the AI to review the Python codebase and generate a severity-ranked report.

Frequently Asked Questions about code-review

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

FAQPage Schema

How do I perform an automated Python code review before a merge?▼

Automated Python code review analyzes your codebase to detect correctness issues, readability gaps, and convention violations, generating a severity-ranked Markdown report. It surfaces critical defects and maintainability risks suitable for pre-merge checks and refactoring planning.

What is a severity-ranked code review report?▼

A severity-ranked code review report is a structured Markdown document containing an executive summary, a prioritized findings section, and a handoff-ready summary table. It categorizes Python codebase defects by severity to help track refactoring tasks and maintainability improvements.

Can I use static analysis to plan Python refactoring tasks?▼

Yes, static analysis can ingest Python repository files to identify architecture concerns, common bugs, and style violations. The analysis outputs a prioritized list of findings that serves as a structured handoff plan for your refactoring tasks.

Does this code review process work with existing Python lint configurations?▼

The code review process analyzes repository files directly to detect convention violations and style issues without requiring external lint dependencies. It evaluates code quality, readability, and architecture concerns to produce a comprehensive executive summary.

What is the best way to identify critical defects in a Python codebase before release?▼

The best way to identify critical defects is to run a comprehensive code review that analyzes your Python codebase for correctness and maintainability risks. It generates a concise, severity-ranked report highlighting the most urgent issues before your release.