nw-rr-critique-dimensions

Evaluate research documents against predefined critique dimensions for bias and evidence quality.

Updated Apr 15, 2026

Search Tags:#research #evaluation #evidence #bias #critique #dimensions #replicability

Ready to run

npx skills add https://github.com/StudentCristian/nWave-github --skill nw-rr-critique-dimensions

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: nw-rr-critique-dimensions
Source: https://github.com/StudentCristian/nWave-github/tree/main/.github/skills/nw-rr-critique-dimensions
Command: npx skills add https://github.com/StudentCristian/nWave-github --skill nw-rr-critique-dimensions

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This framework guides reviewers to systematically critique research documents by applying defined dimensions to surface bias, evidence quality, replicability, and decision justification.

Core Features & Use Cases

Dimension-based evaluation of Source Selection Bias, Evidence Quality, Replicability, Priority Validation, and Completeness.
Generates a structured output template including an evaluation template with YAML-like sections for priority_validation, review_outputs, and credibility analysis.
Suitable for academic peer reviews, policy assessments, and research-communication tasks.

Quick Start

Apply the five critique dimensions to your research document to generate a structured evaluation report.

Frequently Asked Questions about nw-rr-critique-dimensions

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

FAQPage Schema

How do I systematically critique research for evidence quality and bias?▼

A systematic research critique evaluates documents by applying dimensions like Source Selection Bias, Evidence Quality, and Replicability. This process surfaces methodological flaws and generates a structured report detailing credibility analysis and decision justification.

What is the best way to audit replicability and source selection bias in a research review?▼

Auditing replicability involves applying a framework with explicit criteria for Replicability and Source Selection Bias. This framework targets research reviews to expose priority validation issues and generate a structured credibility analysis.

Can I use a dimension-based framework for academic peer review and policy assessment?▼

Dimension-based evaluation suits academic peer reviews and policy assessments by applying five critique dimensions to documents. It generates a structured output template with priority validation and credibility analysis for research-communication tasks.

How do I generate a structured evaluation template for methodological audits?▼

Generate a structured evaluation template by applying critique dimensions to your research document. The output includes YAML-like sections for priority validation, review outputs, and credibility analysis, detailing sources and gaps.

What are the limitations of using predefined critique dimensions for research evaluation?▼

Predefined critique dimensions require a structured evaluation workflow with explicit criteria to function properly. Without a formal output template, the framework cannot adequately detail sources, gaps, and credibility analysis for complex research reviews.