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buchananwill
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review-process

Automate standardized code reviews with scoring and structured output.

2|Updated Mar 17, 2026
Search Tags:#automation#workflow#quality-assurance#code-review#auditability#change-tracking
One-click install
npx skills add https://github.com/buchananwill/ue-claude-scaffold --skill review-process-buchananwill
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-process
Source: https://github.com/buchananwill/ue-claude-scaffold/tree/main/skills/review-process
Command: npx skills add https://github.com/buchananwill/ue-claude-scaffold --skill review-process-buchananwill

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides a repeatable, auditable process for code reviews, guiding an agent through identifying changed files, loading full context, validating against domain criteria, scoring findings, and filtering results to produce a consistent review.

Core Features & Use Cases

  • Identify Changed Files: determine affected files from a git range or explicit paths.
  • Read Full Context: load complete file contents and relevant project headers to understand usage and intent.
  • Domain Criteria Validation: systematically check changes against criteria derived from a domain skill or policy.
  • Score & Filter: assign confidence levels to findings and surface only actionable issues for review.
  • Use Case: apply this workflow to large codebases with multiple reviewers to ensure consistent quality and traceability across changes.

Quick Start

Provide the changed files or a git range to trigger the universal review sequence (identify, read context, validate criteria, score, and filter) and produce a structured review output.

Frequently Asked Questions about review-process

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

FAQPage Schema
How do I automate standardized code reviews for pull requests?▼

Automated code review standardization orchestrates change identification, context loading, criteria validation, scoring, and filtering. It applies a universal sequence to pull requests or commit sets to produce consistent, structured review outputs.

How do I ensure code review consistency across large codebases with multiple reviewers?▼

Code review consistency across large codebases is achieved by applying a universal review sequence that scores findings and filters actionable issues. This ensures reproducible results and auditable quality assurance across diverse changes.

Can I use a git range to identify changed files for an automated code review?▼

Yes, automated code review supports identifying affected files from a git range or explicit paths. It then loads full file contents and relevant project headers to validate the changes against domain criteria.

What is the best way to generate auditable and structured code review outputs?▼

Auditable code review outputs are generated by systematically validating changes against domain criteria and assigning confidence scores to findings. The process filters results to surface only actionable issues according to a defined schema.

Does the automated code review process load full file context or just the diffs?▼

The automated code review process loads full file contents and relevant project headers, not just diffs. Loading complete context ensures the agent understands usage and intent before validating changes against domain criteria.

When do I need to apply domain criteria validation during a code review?▼

Domain criteria validation is needed during code review after reading full file context to systematically check changes. It ensures the code is evaluated against specific domain policies before scoring and filtering findings.

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