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code-review

Automate code-review analysis for GitHub pull requests and pre-commit changes.

Updated Oct 11, 2025
Search Tags:#code quality#automation#development#code review#pull request#github#standards
One-click install
npx skills add https://github.com/tnez/docent --skill code-review-tnez
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-review
Source: https://github.com/tnez/docent/tree/main/skills/development/code-review
Command: npx skills add https://github.com/tnez/docent --skill code-review-tnez

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires gh cli, git cli, npm.

What problem does it solve?

Manual code reviews can be inconsistent, time-consuming, and prone to overlooking critical issues. This Skill provides a structured, comprehensive process for evaluating pull requests and pre-commit changes, ensuring high code quality, architectural alignment, and adherence to project standards.

Core Features & Use Cases

  • PR Overview & Context: Quickly grasp the purpose and context of any pull request.
  • Automated Check Validation: Ensure CI/CD checks pass before diving into manual code inspection.
  • Local Testing & Code Quality: Check out PRs locally to run tests, build, and thoroughly inspect code for maintainability and best practices.
  • Architectural Alignment: Verify changes against project ADRs and established patterns.
  • Use Case: A new contributor submits a pull request. Use this Skill to guide your agent through checking CI status, reviewing the code locally, verifying architectural alignment, and providing structured feedback, all while ensuring no critical steps are missed.

Quick Start

Review pull request #123 for quality and architectural alignment.

Frequently Asked Questions about code-review

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

FAQPage Schema
How do I automate code review checks for pull requests on GitHub?▼

Automated code review validates pull requests by checking CI/CD status, running tests, building locally, and verifying code quality against project standards. This Skill guides you through PR context analysis, architectural alignment with ADRs, test coverage inspection, and linting results to generate structured feedback without manual oversight gaps.

Can I review pull requests locally with automated quality checks before merging?▼

Yes. Checkout PRs locally, run build tools and tests, inspect code for maintainability, and validate against coding standards and ADRs. This Skill orchestrates the full workflow—CI validation, local testing, architectural alignment verification—so you catch critical issues before merge without missing steps.

What should I check in a code review to ensure quality and standards compliance?▼

Code review encompasses PR context and purpose, CI/CD check status, local test and build results, code quality and best practices, architectural alignment with project ADRs, test coverage, linting compliance, and documentation changes. This Skill structures these assessments into a comprehensive process for consistent evaluation across pull requests.

Do I need GitHub CLI and git to run automated code reviews?▼

Yes. This Skill requires GitHub CLI v2.0+, git, npm, and local project build tools to retrieve PR data, validate changes, run tests, and generate actionable feedback. Familiarity with ADRs and project coding standards is also necessary for architectural alignment checks.

How does code review prevent inconsistent or incomplete quality checks?▼

Manual reviews are inconsistent and time-consuming. This Skill applies a structured, repeatable process across pull requests—validating CI status, running local tests, checking architectural alignment, and verifying coding standards—to eliminate oversights and ensure every review follows the same comprehensive criteria.

Can this code review process work across multiple projects?▼

Yes. This Skill applies to GitHub PR workflows and local pre-commit reviews across multiple projects. It guides assessment of code quality, ADR adherence, test coverage, and linting results, adapting to each project's build tools, standards, and architectural patterns.

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