review

Automates pull request review for SQL safety, LLM trust boundary violations, conditional side effects, and structural issues.

Updated Jun 22, 2026
One-click install
npx skills add https://github.com/GrassHopper42/ANTidy --skill review-grasshopper42
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: review
Source: https://github.com/GrassHopper42/ANTidy/tree/main/.claude/skills/gstack/review
Command: npx skills add https://github.com/GrassHopper42/ANTidy --skill review-grasshopper42

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires Bash, Read, Edit, Write, Grep, Glob, Agent, AskUserQuestion, WebSearch, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of reviewing pull requests, ensuring SQL safety, LLM trust, conditional side effects, and other structural issues are identified before merging code changes.

Core Features & Use Cases

  • Automated PR Review: Analyze pull requests against a set of predefined criteria for SQL safety, LLM trust, and structural issues.
  • Proactive Suggestions: Suggest improvements or necessary actions when the user is about to merge or land code changes.
  • Use Case: Before merging a pull request, use this Skill to automatically check for potential issues and provide a report with suggested fixes.

Quick Start

Use the /review skill to analyze the pull request you're working on.

Frequently Asked Questions about review

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

FAQPage Schema
How do I automate PR review for SQL safety and structural issues?

You can automate PR review for SQL safety by running this Skill to analyze pull requests against predefined criteria, identifying potential SQL safety violations and structural issues before merging code changes.

What are LLM trust boundary violations and how are they detected in code?

LLM trust boundary violations occur when code improperly trusts LLM outputs. This Skill detects them during automated pull request reviews by analyzing structural issues and proactively suggesting necessary improvements before landing code.

Can I use Bash and Grep to check pull requests for conditional side effects?

Yes, this Skill leverages Bash, Grep, and other capabilities to analyze pull requests, checking for conditional side effects and structural issues to ensure code safety prior to merging.

Does automated code analysis work for pre-landing reviews and proactive suggestions?

Automated code analysis works for pre-landing reviews by proactively analyzing pull requests for SQL safety, LLM trust boundaries, and structural issues, providing a report with suggested fixes before code changes are merged.

What is the best way to check for SQL safety violations before merging a pull request?

The best way to check for SQL safety violations is to use an automated PR review Skill that analyzes your pull request for SQL safety, LLM trust boundaries, and conditional side effects, delivering a report with suggested fixes.