pr-report

Analyze pull requests and generate severity-ordered HTML or Markdown review reports.

Updated Apr 28, 2026
One-click install
npx skills add https://github.com/khoabd/paperclip --skill pr-report-khoabd
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pr-report
Source: https://github.com/khoabd/paperclip/tree/main/.agents/skills/pr-report
Command: npx skills add https://github.com/khoabd/paperclip --skill pr-report-khoabd

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill eliminates the tedious, time-consuming manual work of deep pull request review, contributor design explanation, and polished report generation for open-source maintainers, cutting down hours of repetitive evaluation work.

Core Features & Use Cases

  • Deep PR Analysis: Conduct maintainer-grade reviews of PRs, branches, or large contributions, with findings ordered by severity and clear distinction between architectural, product, and implementation concerns.
  • Tutorial-Style Explanation: Reconstruct and explain the contribution's system design, runtime contracts, and lifecycle for team members who did not write the code.
  • Polished Report Generation: Create standalone HTML or Markdown review artifacts with professional styling, or short maintainer summaries for chat, to support merge decisions.
  • Use Case: When a contributor submits a large new feature for your open-source project, use this Skill to analyze the design, compare it to similar existing systems, and generate a shareable HTML report for the team to review merge readiness.

Quick Start

Use the pr-report skill to analyze the latest PR from the contributor @alex and generate a polished HTML merge recommendation report saved to your team's shared review folder.

Frequently Asked Questions about pr-report

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

FAQPage Schema
How do I generate a maintainer-grade pull request review report for a large open-source contribution?▼

To generate a pull request review report, you can analyze the contribution to produce severity-ordered findings and merge recommendations. The review reconstructs the system design and outputs a polished standalone HTML or Markdown artifact for team evaluation.

What is the best way to explain a contributor's design decisions to team members who did not write the code?▼

Explaining a contributor's design decisions involves reconstructing the system design, runtime contracts, and lifecycle into a tutorial-style explanation. This helps team members understand the architectural, product, and implementation concerns before evaluating merge readiness.

Can I compare a pull request to similar open-source systems before preparing a merge recommendation?▼

Yes, you can compare a pull request to similar open-source systems during deep PR analysis. This comparison evaluates the contribution's design against existing architectures to support a well-informed merge recommendation for your project.

Does the PR review process distinguish between architectural, product, and implementation concerns?▼

Yes, the PR review process explicitly distinguishes between architectural, product, and implementation concerns. Findings are severity-ordered to ensure maintainers can prioritize critical structural issues before evaluating granular product or implementation details.

How do I output a short maintainer summary for chat from a deep code review?▼

To output a short maintainer summary for chat, the code review generates concise merge recommendations instead of a standalone HTML or Markdown file. This format delivers the essential severity-ordered findings directly into team communication channels.

When do I need a standalone HTML report for pull request reviews?▼

You need a standalone HTML report for pull request reviews when sharing a polished, comprehensive merge recommendation with your team. It provides professional styling and tutorial-style system explanations for evaluating large open-source contributions.