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dtbuchholz
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pr-review-quick

Runs parallel AI reviews of git diff changes for security, bugs, performance, and code quality.

Updated Jan 22, 2026
Search Tags:#code quality#code review#performance#pull request#security#ai agents#bug detection
One-click install
npx skills add https://github.com/dtbuchholz/claude-config --skill pr-review-quick
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pr-review-quick
Source: https://github.com/dtbuchholz/claude-config/tree/main/skills/pr-review-quick
Command: npx skills add https://github.com/dtbuchholz/claude-config --skill pr-review-quick

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill automates the process of quickly reviewing code changes in a pull request, identifying potential issues across security, bugs, performance, and code quality without requiring extensive manual effort.

Core Features & Use Cases

  • Parallel Agent Review: Utilizes multiple specialized AI agents (security, bugs, performance, quality) to analyze code changes concurrently.
  • Targeted Feedback: Focuses feedback specifically on newly added or modified lines of code, ignoring pre-existing issues.
  • Cost-Effective Analysis: Employs the haiku model for faster and cheaper reviews.
  • Use Case: Before merging a feature branch, quickly get an assessment of potential risks and areas for improvement in the new code.

Quick Start

Run a quick code review on the current changes in the pull request.

Frequently Asked Questions about pr-review-quick

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

FAQPage Schema
How do I perform a quick code review on a pull request?▼

To perform a quick code review on a pull request, this Skill analyzes recent git diff changes using parallel specialist AI agents for security, bugs, performance, and code quality concurrently.

Can I use AI agents to check newly added code lines for security and performance issues?▼

Yes, you can use AI agents to check newly added or modified code lines for security and performance issues, applying targeted feedback that specifically ignores pre-existing problems in the repository.

How do pre-commit checks work with parallel AI agents?▼

Pre-commit checks work by running multiple concurrent task tool calls with the haiku model, enabling rapid analysis of recent code changes across security, bug detection, and quality dimensions before merging.

What is the best way to analyze recent git diff changes for bug detection?▼

The best way to analyze recent git diff changes for bug detection is deploying parallel specialist AI agents that focus exclusively on newly added or modified lines to identify potential risks.

Does this code review approach evaluate pre-existing issues in the repository?▼

No, this code review approach does not evaluate pre-existing issues, as it specifically focuses feedback on newly added or modified lines of code to target current pull request risks.

Why use the haiku model for automated pull request analysis?▼

You use the haiku model for automated pull request analysis to achieve cost-effective and faster reviews, running multiple concurrent task tool calls to assess code quality and security rapidly.

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