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d3hunter-pr-reviewing

Reviews behavior-altering pull requests using a standardized 10-category checklist and risk-adaptive workflow.

Updated Mar 3, 2026
Search Tags:#code review#pull request#compatibility#concurrency#pr review#test coverage#correctness
One-click install
npx skills add https://github.com/D3Hunter/ai-engineer --skill d3hunter-pr-reviewing
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: d3hunter-pr-reviewing
Source: https://github.com/D3Hunter/ai-engineer/tree/main/skills/d3hunter-pr-reviewing
Command: npx skills add https://github.com/D3Hunter/ai-engineer --skill d3hunter-pr-reviewing

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Behavior-changing pull requests often introduce subtle correctness regressions, compatibility breaks, concurrency bugs, or inadequate test coverage that standard lightweight reviews miss, leading to production incidents and costly rollbacks.

Core Features & Use Cases

  • 10-category structured review checklist: Covers correctness, compatibility, code structure, failure semantics, concurrency, scope, performance, API clarity, comments, and test quality for comprehensive coverage.
  • Risk-adaptive hotspot first pass: Triages high-risk files and modules first for large or high-impact PRs to surface critical issues early.
  • Standardized output contracts: Supports inline, threaded, and standalone review modes with consistent severity tagging, 5-field rubric for findings, and tone-aligned phrasing.
  • Phrase bank and decision pipelines: Provides pre-vetted wording stems and confidence-to-action matrices to keep feedback concise, actionable, and consistent. Ideal for engineering teams reviewing PRs that touch core system logic, migration paths, concurrency controls, versioned metadata, or critical test changes where a missed edge case can cause widespread user impact.

Quick Start

Use the d3hunter-pr-reviewing skill to conduct a structured second-opinion review of the attached behavior-changing pull request, following the default 10-step review order and outputting findings sorted by risk.

Frequently Asked Questions about d3hunter-pr-reviewing

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

FAQPage Schema
How do I perform a structured code review for behavior-changing pull requests?▼

A structured code review for behavior-changing pull requests applies a 10-category checklist covering correctness, compatibility, concurrency, and test coverage to eliminate inconsistent feedback and prevent production incidents. It uses risk-adaptive triage to surface critical issues early.

What is a risk-adaptive code review and when do I need it?▼

Risk-adaptive code review is a process that triages high-risk files and modules first to surface critical correctness regressions early. You need it for large or high-impact pull requests touching core system logic, migration paths, or concurrency controls.

How do I standardize code review output for correctness and compatibility checks?▼

You standardize code review output by using a 5-field rubric for findings with consistent severity tagging and tone-aligned phrasing. This structured approach ensures feedback remains concise, actionable, and uniform across inline, threaded, and standalone review modes.

Does this pull request review process work for concurrency and migration path changes?▼

Yes, the pull request review process explicitly covers concurrency controls and migration paths within its 10-category checklist. It identifies subtle compatibility breaks and concurrency bugs that standard lightweight reviews often miss.

What is the best way to check test coverage for critical behavior changes in a PR?▼

The best way to check test coverage for critical behavior changes is applying a standardized review checklist that evaluates test quality alongside failure semantics. This ensures edge cases in core system logic receive adequate coverage before deployment.

Why does my standard code review miss subtle correctness regressions?▼

Standard code reviews miss subtle correctness regressions because they lack a risk-adaptive hotspot triage and a standardized severity-based output contract. Without a 10-category structured checklist, edge cases in concurrency and compatibility breaks remain undetected.

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