fact-checker

Verify factual claims by evaluating evidence and source credibility.

203|27|Updated Apr 19, 2026
One-click install
npx skills add https://github.com/franklee16/academic-research-skills --skill fact-checker-franklee16
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fact-checker
Source: https://github.com/franklee16/academic-research-skills/tree/main/peer-review/fact-checker
Command: npx skills add https://github.com/franklee16/academic-research-skills --skill fact-checker-franklee16

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps you systematically verify potentially false or misleading statements by matching each claim to the evidence needed to confirm or refute it.

Core Features & Use Cases

  • Structured claim verification: Extracts the exact assertion and separates fact from opinion, including implicit or measurable components.
  • Evidence and credibility evaluation: Assesses what evidence would prove/disprove the claim and ranks source quality (from peer-reviewed studies to social media).
  • Clear verdict with context: Produces a rating (TRUE to UNVERIFIABLE) plus reasoning, missing nuance, and correct information when applicable.
  • Use case: When you encounter a viral statistic like “X causes Y,” you can fact-check it by verifying the data, timeframe, methodology, and source credibility before you share or rely on it.

Quick Start

Ask an AI to fact-check a specific statement by providing the claim text and requesting a verdict using evidence-based sources.

Frequently Asked Questions about fact-checker

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

FAQPage Schema
How do I fact-check a viral statistic or claim I found online?

To fact-check a viral claim, you must extract the exact assertion, identify the evidence required to prove or disprove it, and evaluate source credibility. This process yields a structured verdict rating from TRUE to UNVERIFIABLE, complete with supporting evidence and context.

What is the best way to evaluate source credibility for misinformation detection?

Evaluating source credibility involves ranking the quality of information sources, ranging from peer-reviewed studies down to social media posts. This assessment determines the reliability of the evidence used to confirm or refute a potentially misleading statement.

Can I use this approach to verify statistical accuracy in news and research reports?

Yes, you can verify statistical accuracy by checking the data, timeframe, methodology, and source credibility cited in news or research. This ensures that measurable components and implicit claims are evaluated against authoritative evidence.

How does claim verification separate factual assertions from opinions?

Claim verification separates fact from opinion by extracting the exact assertion and identifying its implicit or measurable components. This structured extraction ensures that only testable factual statements are matched against evidence for a confidence-based verdict.

What does a structured fact-checking verdict include when assessing a rumor?

A structured fact-checking verdict includes a rating from TRUE to UNVERIFIABLE, a confidence score, supporting or refuting evidence, missing nuance, and correct information. It also provides a transparent assessment of source quality to contextualize the final judgment.

When should I not rely on automated claim verification for evidence evaluation?

You should not rely solely on automated claim verification when a claim is categorized as UNVERIFIABLE, indicating a lack of credible evidence or authoritative sources. In these cases, the process highlights missing nuance and context but cannot produce a definitive factual rating.