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nw-sc-review-dimensions

Critique code and test quality using structured review dimensions.

Updated Apr 15, 2026
Search Tags:#testing#code-review#acceptance-criteria#peer-review#quality-assessment#risk-detection#qa-patterns
One-click install
npx skills add https://github.com/StudentCristian/nWave-github --skill nw-sc-review-dimensions
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: nw-sc-review-dimensions
Source: https://github.com/StudentCristian/nWave-github/tree/main/.github/skills/nw-sc-review-dimensions
Command: npx skills add https://github.com/StudentCristian/nWave-github --skill nw-sc-review-dimensions

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill provides a formal framework to critique code and tests in peer reviews by codifying core dimensions such as implementation bias, test quality validation, completeness checks, and priority validation.

Core Features & Use Cases

  • Structured review criteria across production code and tests to uncover biases and quality gaps.
  • Guidance on interpretation of findings, with clearly defined dimensions and severity levels.
  • Use Case: during code reviews, teams can apply the dimensions to detect over-engineering, insufficient test coverage, and misaligned acceptance criteria.

Quick Start

Run the review in the current codebase and return a structured YAML report outlining findings across the defined critique dimensions.

Frequently Asked Questions about nw-sc-review-dimensions

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

FAQPage Schema
What are the key dimensions for evaluating code quality during a peer review?▼

Structured code review dimensions include implementation bias, test quality validation, completeness coverage, and priority validation. These criteria uncover over-engineering, insufficient test coverage, and misaligned acceptance criteria during peer reviews.

How do I detect implementation bias and test quality gaps in a pre-merge code check?▼

To detect implementation bias and test quality gaps during pre-merge checks, apply structured review criteria across production code and tests. This process returns a structured YAML report outlining findings and severity levels across defined critique dimensions.

Can I use structured review dimensions for post-merge audits of production tests?▼

Yes, structured review dimensions apply to post-merge audits across production code and tests. The framework evaluates test quality validation and completeness coverage, generating a YAML report that outlines prioritization decisions and quality findings.

What is the best way to assess if acceptance criteria are met during code reviews?▼

The best way to assess acceptance criteria during code reviews is using a formal framework with priority validation dimensions. This evaluates completeness coverage and misaligned requirements, returning a structured YAML report outlining findings and severity levels.

How do I get a structured report of risk detection findings after running a code review?▼

To get a structured report of risk detection findings, run the review in your current codebase. This generates a structured YAML report outlining findings across defined critique dimensions, including severity levels and prioritization decisions for quality assessment.

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