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ProgMastermind
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review-pr

Automate code review for ATOM PRs with risk assessments.

Updated Jul 15, 2026
Search Tags:#code review#AI-driven#PR analysis#performance assessment#ATOM
One-click install
npx skills add https://github.com/ProgMastermind/ATOM --skill review-pr-progmastermind
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-pr
Source: https://github.com/ProgMastermind/ATOM/tree/main/.claude/skills/review-pr
Command: npx skills add https://github.com/ProgMastermind/ATOM --skill review-pr-progmastermind

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the code review process for ATOM Pull Requests (PRs), enhancing code quality and efficiency through AI-driven analysis.

Core Features & Use Cases

  • Automated Code Review: Reviews ATOM PRs for performance claims, cross-repo dependencies, model coverage, and AI-generated code patterns.
  • Semantic Understanding: Analyzes changes at a semantic level to identify potential issues like silent bypasses, hardcoded assumptions, and uninitialized states.
  • Backbone File Risk Assessment: Classifies files based on their impact and assesses risk associated with changes in critical components.

Quick Start

Run the review-pr skill with a PR number to start the code review process.

Frequently Asked Questions about review-pr

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

FAQPage Schema
How does AI-driven code review for ATOM PRs work?▼

AI-driven code review for ATOM PRs works by analyzing PR numbers to assess performance claims, cross-repo dependencies, model coverage, and AI-generated code patterns at a semantic level. It classifies files based on impact to evaluate risk in critical components like backbone files and dispatch logic.

What is the best way to automate PR analysis for backbone file risk assessment?▼

The best way to automate PR analysis for backbone file risk assessment is using an AI-driven code review Skill that classifies files based on their impact. It evaluates changes in critical components like dispatch logic to provide detailed risk assessments for ATOM PRs.

Can I detect silent bypasses and hardcoded assumptions in AI-generated code patterns?▼

Yes, you can detect silent bypasses and hardcoded assumptions in AI-generated code patterns by running an automated code review on ATOM PRs. The review analyzes changes at a semantic level to identify potential issues like uninitialized states and hardcoded values.

Does automated code review support cross-repo dependencies and model coverage analysis?▼

Automated code review supports cross-repo dependencies and model coverage analysis by evaluating ATOM PRs. It examines performance claims and assesses how changes across repositories interact, ensuring comprehensive risk evaluation for critical backbone files.

How do I start an automated code review for an ATOM Pull Request?▼

To start an automated code review for an ATOM Pull Request, run the review-pr Skill and provide the specific PR number. This initiates the AI-driven analysis of performance claims, model coverage, and backbone file risks.

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