code-review

Automate structured code reviews with pytest and ruff checks.

Updated Apr 23, 2026

Search Tags:#testing #pytest #static-analysis #quality-assurance #lint #code-review #review-process

Ready to run

npx skills add https://github.com/ladinglogichq/lading-logic-hackathon --skill code-review-ladinglogichq

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-review
Source: https://github.com/ladinglogichq/lading-logic-hackathon/tree/main/.agents/skills/code-review
Command: npx skills add https://github.com/ladinglogichq/lading-logic-hackathon --skill code-review-ladinglogichq

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps engineers validate changes before delivery by providing a structured, repeatable code-review checklist that reduces regressions and quality issues.

Core Features & Use Cases

Correctness: ensures changes solve the intended task with no unintended side effects; edge cases considered; appropriate error handling.
Code Quality: enforces style consistency, readability, and removal of dead code.
Tests: requires test coverage for new functionality and verifies existing tests still pass.
Safety: checks for potential security concerns, input validation, and safe file operations.
Process: outlines steps to read modified files, run tests, run linters, and re-review until issues are resolved.
Helper Scripts: references lint_check.py for static checks.

Quick Start

Run the code-review workflow on your modified files to validate correctness, style, tests, and safety before delivering.

Frequently Asked Questions about code-review

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

FAQPage Schema

How do I automate code reviews for pull requests and patches?▼

Automate code reviews for pull requests by applying a structured checklist that validates correctness, quality, tests, and safety. This process guides reviewers to read modified files, run tests, run linters, and re-review until issues are resolved before delivery.

How do I run pytest and lint checks to validate code changes?▼

Run pytest and lint checks to validate code changes by executing tests with pytest and performing static analysis with ruff. The review process verifies test coverage for new functionality and ensures existing tests pass using a repeatable lint check script.

What should a structured code review checklist include to prevent regressions?▼

A structured code review checklist should include correctness to ensure no unintended side effects, code quality for style consistency, tests for coverage, and safety for input validation. This repeatable process reduces regressions and quality issues before delivery.

Does static analysis with ruff work with pytest test validation workflows?▼

Static analysis with ruff integrates with pytest test validation workflows to enforce style consistency and remove dead code. The review process runs linters alongside pytest to verify that new functionality has test coverage and existing tests still pass safely.

What is the best way to check edge cases and error handling during a code review?▼

The best way to check edge cases and error handling during a code review is using a structured validation process. It ensures changes solve the intended task with appropriate error handling, verifies documentation, and checks for potential security concerns and safe file operations.

Why does my code review process fail to catch dead code and style inconsistencies?▼

Your code review process fails to catch dead code and style inconsistencies without enforced static analysis. Applying a repeatable lint check script with ruff enforces style consistency, improves readability, and removes dead code before changes are delivered.