review

Name: review
Availability: InStock
Author: ehsaanark

Analyze pull request diffs for SQL safety, data handling, and policy violations.

Updated Mar 14, 2026

Search Tags:#LLM #review #policy #lint #risk #pull-request

Ready to run

npx skills add https://github.com/EhsaanArk/ai-signal-router --skill review-ehsaanark

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: review
Source: https://github.com/EhsaanArk/ai-signal-router/tree/main/.claude/skills/gstack/review
Command: npx skills add https://github.com/EhsaanArk/ai-signal-router --skill review-ehsaanark

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Streamlines manual PR review by automating consistency checks, risk signals, and policy violations in code diffs.

Core Features & Use Cases

Automated policy checks: detect SQL safety and data safety issues, prompt trust boundaries, and conditional side effects.
Consistent review prompts: generate actionable feedback for engineers and maintainers.
Use Case: before merging a PR, trigger a review for potential bugs and compliance issues.

Quick Start

Trigger /review on a pull request to generate a diagnostic report and recommended fixes.

Frequently Asked Questions about review

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

FAQPage Schema

How do I automate pull request reviews for SQL safety and policy violations?▼

Automating pull request reviews for SQL safety and policy violations involves analyzing diffs against a defined checklist to detect critical quality issues. This process surfaces data handling risks and generates actionable feedback with suggested fixes before merging.

What is an AI-assisted PR review and how does it identify risk signals in code diffs?▼

An AI-assisted PR review is an automated process that analyzes code diffs to identify risk signals and policy violations. It validates changes against a defined checklist, detecting issues like SQL safety concerns and prompt trust boundaries to report findings and suggest fixes.

How do I check a pull request for model-trust boundaries and data handling risks before merging?▼

To check a pull request for model-trust boundaries and data handling risks before merging, trigger an automated review on the diff. The system validates the changes against a defined checklist to surface compliance issues and generate a diagnostic report.

Does automated PR review work for detecting conditional side effects across multiple repositories?▼

Yes, automated PR review works for detecting conditional side effects across multiple repositories. It is designed for pre-merge reviews to validate diffs against a defined checklist, consistently surfacing critical quality issues and generating actionable feedback for maintainers.

What is the best way to generate actionable feedback and fix suggestions for engineers during code review?▼

The best way to generate actionable feedback and fix suggestions during code review is to run an automated diagnostic on the pull request. This validates the diff against a checklist and outputs a plan-ready format with recommended fixes for engineers.

What type of compliance issues can an automated PR review detect in a code diff?▼

An automated PR review can detect compliance issues in a code diff such as SQL safety violations, data safety issues, prompt trust boundary violations, and conditional side effects. It reports these findings and suggests fixes in a plan-ready format.