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coff33ninja
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verify-and-cite

Verifies AI-generated claims with sources and expresses uncertainty in responses.

Updated Jun 27, 2026
Search Tags:#verification#accuracy#citation#uncertainty expression#factual information
One-click install
npx skills add https://github.com/coff33ninja/ai-skills-mcp --skill verify-and-cite
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: verify-and-cite
Source: https://github.com/coff33ninja/ai-skills-mcp/tree/main/skills/verify-and-cite
Command: npx skills add https://github.com/coff33ninja/ai-skills-mcp --skill verify-and-cite

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill minimizes misinformation and uncertainty in AI responses by enforcing verification, sourcing, and uncertainty expression.

Core Features & Use Cases

  • Factual Verification: Cross-references claims with multiple sources for accuracy.
  • Citation Enforcement: Requires citations for quoted information.
  • Uncertainty Expression: Communicates confidence levels and knowledge limits transparently.
  • Use Case: Before providing technical specifications, the skill ensures that version numbers and release dates are current and verified, and expresses any uncertainties in the response.

Quick Start

Use the verify-and-cite skill when generating responses to factual queries, ensuring all claims are verified and sources cited.

Frequently Asked Questions about verify-and-cite

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

FAQPage Schema
How do I ensure factual accuracy and add citations in AI-generated responses?▼

To ensure factual accuracy, cross-reference claims with multiple external sources, enforce citations for quoted information, and transparently express uncertainty regarding confidence levels in AI-generated responses.

What is the best way to verify data validation and technical specifications before publishing?▼

Verifying data validation requires checking version numbers and release dates against current external sources, ensuring all technical specifications are accurate, and explicitly communicating any remaining uncertainties.

How does uncertainty expression work when generating factual information?▼

Uncertainty expression communicates confidence levels and knowledge limits transparently, ensuring users understand the reliability of factual information and preventing the spread of misinformation in AI responses.

Can I use automated source verification for content creation without external access?▼

No, source verification requires access to external sources and knowledge of appropriate citation formats to cross-reference claims, validate factual data, and enforce citations for quoted information.

When do I need to enforce citations for data validation tasks?▼

You need to enforce citations during data validation whenever providing factual queries, technical specifications, or quoted information to minimize misinformation and ensure credibility in AI-generated responses.

What are the limitations of enforcing source verification in AI content generation?▼

Limitations include complete dependency on external source accessibility and appropriate citation format knowledge, meaning verification fails if external references are unavailable or cannot be properly cited.

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