evidence-evaluation

What problem does it solve?

In data-driven decisions, weak or unverified evidence leads to flawed conclusions, biased judgments, and increased risk. This skill provides a structured framework to distinguish facts from assumptions, evaluate source quality, and document evidence in a reproducible, audit-friendly way.

Core Features & Use Cases

• Credibility assessment: evaluate source trustworthiness and potential conflicts of interest.
• Methodology evaluation: examine data collection methods, sample size, controls, and repeatability.
• Recency & relevance: ensure information is up-to-date and directly applicable to the decision context.
• Evidence documentation: capture claims, sources, quality scores, and red flags for governance.
• Use cases: decision analyses, risk reviews, policy decisions, and research audits.

Quick Start

Input an evidence item and run it through the evaluation workflow to score credibility, methodology, recency, and relevance.