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rework-rate

Analyze pull request rework rates and review cycle metrics.

Updated Apr 12, 2026
Search Tags:#code review#quality metrics#Pull Request#DORA metric#rework analysis
One-click install
npx skills add https://github.com/barichter/squad --skill rework-rate-barichter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rework-rate
Source: https://github.com/barichter/squad/tree/main/templates/skills/rework-rate
Command: npx skills add https://github.com/barichter/squad --skill rework-rate-barichter

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

The Skill helps developers and teams understand the rework rate in their pull requests, which is a key indicator of code quality and review efficiency.

Core Features & Use Cases

  • Measure PR Rework Rate: Calculate the percentage of code changes that require revision after initial review submission.
  • Identify Rework Patterns: Analyze trends in PR revision cycles to identify areas for improvement.
  • Use Cases: Monitor team code review efficiency, track AI-generated code retention rates, and build engineering health dashboards.

Quick Start

Use the squad rework command to analyze the rework rate from merged pull requests.

Frequently Asked Questions about rework-rate

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

FAQPage Schema
How do I calculate the rework rate of pull requests?▼

To calculate the pull request rework rate, use the `squad rework` command to analyze merged pull requests and measure the percentage of code changes requiring revision after the initial review submission.

What is PR rework rate analysis and how does it work?▼

PR rework rate analysis evaluates your code review processes by tracking revision cycles and rejection rates, providing metrics that identify inefficiencies and trends in code quality requiring changes post-review.

Can I use this to track AI-generated code retention rates?▼

Yes, you can track AI-generated code retention rates by analyzing the rework rate of pull requests, measuring how often AI-generated code changes require revision after the initial code review submission.

How do I monitor team code review efficiency using DORA metrics?▼

Monitor team code review efficiency by analyzing the rework rate of pull requests, which provides metrics on revision cycles and rejection rates to help track engineering health and optimize code quality.

Does this Skill require any external dependencies to analyze code review quality metrics?▼

No, this Skill operates without external dependencies, relying solely on its internal scripts to analyze code review quality metrics and calculate the rework rate from your merged pull requests.

What's the best way to identify rework patterns in pull requests?▼

The best way to identify rework patterns is to analyze trends in pull request revision cycles using the `squad rework` command, which surfaces inefficiencies in your code review processes for targeted improvement.

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