doublecheck

Extract claims from AI-generated text and verify them via web search.

Updated Apr 22, 2026
One-click install
npx skills add https://github.com/hoonsubin/github-projects-mcp-server --skill doublecheck-hoonsubin
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: doublecheck
Source: https://github.com/hoonsubin/github-projects-mcp-server/tree/main/.roo/skills/doublecheck
Command: npx skills add https://github.com/hoonsubin/github-projects-mcp-server --skill doublecheck-hoonsubin

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides comprehensive verification for AI-generated content, ensuring claims are factually accurate and sourced correctly, reducing the risk of misinformation.

Core Features & Use Cases

  • Three-Layer Verification: A multi-step process for verifying factual claims.
  • Web Search and Citation Analysis: Searches for evidence to support or contradict claims.
  • Adversarial Review: Checks for common patterns of error in AI-generated text.
  • Structured Report: Provides a clear, structured report for human review.

Quick Start

Use the doublecheck skill on any AI-generated text you want to verify for accuracy and reliability.

Frequently Asked Questions about doublecheck

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

FAQPage Schema
How do I verify AI-generated content for factual accuracy?

To verify AI-generated content for factual accuracy, you can use an automated fact-checking process that extracts claims, validates them against web sources, and generates a structured report for human review.

What is the best way to fact-check AI output claims using source validation?

The best way to fact-check AI output claims using source validation is through a three-layer verification process that includes claim extraction, web search citation analysis, and adversarial review to identify common error patterns.

Can I check AI-generated text for misinformation before publishing?

Yes, you can check AI-generated text for misinformation before publishing by applying adversarial review and source verification, which reduces the risk of spreading inaccuracies by providing sourced evidence.

How does adversarial review improve AI output verification?

Adversarial review improves AI output verification by actively checking the generated text for common patterns of error, ensuring that factual claims are cross-referenced and supported by web search evidence.

What kind of report do I get from automated AI fact-checking?

Automated AI fact-checking provides a clear, structured report designed for human review, summarizing the accuracy validation results and source links gathered during the claim extraction and verification process.