fact-check

Decompose claims and evaluate source credibility with deterministic validation.

74|12|Updated Apr 5, 2026
One-click install
npx skills add https://github.com/petar-nauka/fact-check-skill --skill fact-check-petar-nauka
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fact-check
Source: https://github.com/petar-nauka/fact-check-skill/tree/main
Command: npx skills add https://github.com/petar-nauka/fact-check-skill --skill fact-check-petar-nauka

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and schema (resource) components.

What problem does it solve?

This Skill addresses the difficulty of verifying information in a complex media landscape by providing a structured, evidence-based workflow to detect misinformation, evaluate source credibility, and prebunk false narratives.

Core Features & Use Cases

  • Evidence-Led Verification: Decomposes claims into checkable units and maintains a transparent evidence ledger.
  • Manipulation Detection: Scans content for red flags like emotional framing, logical fallacies, and coordinated disinformation patterns.
  • Use Case: When a user shares a suspicious social media post or article, the Skill performs a lateral reading of the source, checks for manipulation markers, and generates a share-safe summary with a confidence-calibrated verdict.

Quick Start

Use the fact-check skill to verify the claim in the provided article link and generate a structured analysis.

Frequently Asked Questions about fact-check

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

FAQPage Schema
How does fact-checking detect misinformation and manipulation in media content?▼

Fact-checking detects misinformation by decomposing claims into checkable units, scanning for emotional framing and logical fallacies, and evaluating source credibility to identify coordinated disinformation patterns.

How do I verify a suspicious social media post or article link for false narratives?▼

To verify a suspicious post, the system performs lateral reading of the source, checks for manipulation markers, maintains an evidence ledger, and generates a confidence-calibrated verdict with a share-safe summary.

What is claim decomposition and how does it support evidence-led verification?▼

Claim decomposition breaks down complex statements into discrete, checkable units. This supports evidence-led verification by allowing each unit to be individually validated against sources, ensuring transparent and structured analysis.

Can I perform prebunking briefings and fact-checking across multiple languages and geopolitical contexts?▼

Yes, you can perform prebunking briefings across multiple languages and geopolitical contexts. The system utilizes deterministic validation to produce transparent, source-grounded verification results for diverse information environments.

What is the best way to evaluate source credibility when checking for disinformation?▼

The best way to evaluate source credibility is through lateral reading and maintaining a transparent evidence ledger. This approach tracks red flags like coordinated disinformation patterns and logical fallacies to ensure accuracy.