Fact Checker

Verify factual claims in documents using web search and official sources, then apply corrections with user confirmation.

Features

• ✅ Comprehensive fact verification across multiple domains
• 🔍 Searches authoritative sources (official docs, API specs, academic papers)
• 📊 Generates detailed correction reports with sources
• 🤖 Auto-applies corrections after user approval
• 🕐 Adds temporal context to prevent information decay

Supported Claim Types

• AI Model Specifications: Context windows, pricing, features, benchmarks
• Technical Documentation: API capabilities, version numbers, library features
• Statistical Data: Metrics, benchmark scores, performance data
• General Facts: Any verifiable factual statement

Usage Examples

Example 1: Update Outdated AI Model Info

User: Fact-check the AI model specifications in section 2.1

What happens:

1. Identifies claims: "Claude 3.5 Sonnet: 200K tokens", "GPT-4o: 128K tokens"
2. Searches official documentation for current models
3. Finds: Claude Sonnet 4.5, GPT-5.2 with updated specs
4. Generates correction report with sources
5. Applies fixes after user confirms

Example 2: Verify Technical Claims

User: Check if these library versions are still current

What happens:

1. Extracts version numbers from document
2. Checks package registries (npm, PyPI, etc.)
3. Identifies outdated versions
4. Suggests updates with changelog references

Example 3: Validate Statistics

User: Verify the benchmark scores in this section

What happens:

1. Identifies numerical claims and metrics
2. Searches official benchmark publications
3. Compares document values vs. source data
4. Flags discrepancies with authoritative links

Workflow

The skill follows a 5-step process:

Fact-checking Progress:
- [ ] Step 1: Identify factual claims
- [ ] Step 2: Search authoritative sources
- [ ] Step 3: Compare claims against sources
- [ ] Step 4: Generate correction report
- [ ] Step 5: Apply corrections with user approval

Source Evaluation

Preferred sources (in order):

1. Official product pages and documentation
2. API documentation and developer guides
3. Official blog announcements
4. GitHub releases (for open source)

Use with caution:

• Third-party aggregators (verify against official sources)
• Blog posts and articles (cross-reference)

Avoid:

• Outdated documentation
• Unofficial wikis without citations
• Speculation and rumors

Real-World Example

Before:

AI 大模型的"上下文窗口"不断升级：
- Claude 3.5 Sonnet: 200K tokens（约 15 万汉字）
- GPT-4o: 128K tokens（约 10 万汉字）
- Gemini 1.5 Pro: 2M tokens（约 150 万汉字）

After fact-checking:

AI 大模型的"上下文窗口"不断升级（截至 2026 年 1 月）：
- Claude Sonnet 4.5: 200K tokens（约 15 万汉字）
- GPT-5.2: 400K tokens（约 30 万汉字）
- Gemini 3 Pro: 1M tokens（约 75 万汉字）

Changes made:

• ✅ Updated Claude 3.5 Sonnet → Claude Sonnet 4.5
• ✅ Corrected GPT-4o (128K) → GPT-5.2 (400K)
• ✅ Fixed Gemini 1.5 Pro (2M) → Gemini 3 Pro (1M)
• ✅ Added temporal marker "截至 2026 年 1 月"

Installation

# Via CCPM (recommended)
ccpm install @daymade-skills/fact-checker

# Manual installation
Download fact-checker.zip and install through Claude Code

Trigger Keywords

The skill activates when you mention:

• "fact-check this document"
• "verify these claims"
• "check if this is accurate"
• "update outdated information"
• "validate the data"

Configuration

No configuration required. The skill works out of the box.

Limitations

Cannot verify:

• Subjective opinions or judgments
• Future predictions or specifications
• Claims requiring paywalled sources
• Disputed facts without authoritative consensus

For such cases, the skill will:

• Note the limitation in the report
• Suggest qualification language
• Recommend user research or expert consultation

Best Practices

For Authors

1. Run regularly: Fact-check documents periodically to catch outdated info
2. Include dates: Add temporal markers like "as of [date]" to claims
3. Cite sources: Keep original source links for future verification
4. Review reports: Always review the correction report before applying changes

For Fact-Checking

1. Be specific: Target specific sections rather than entire books
2. Verify critical claims first: Prioritize high-impact information
3. Cross-reference: For important claims, verify across multiple sources
4. Update regularly: Technical specs change frequently - recheck periodically

Development

Created with skill-creator v1.2.2 following Anthropic's best practices.

Testing:

• Verified on Claude Sonnet 4.5, Opus 4.5, and Haiku 4
• Tested with real-world documentation updates
• Validated correction workflow with user approval gates

Version History

1.0.0 (2026-01-05)

• Initial release
• Support for AI models, technical docs, statistics
• Auto-correction with user approval
• Comprehensive source evaluation framework

License

MIT License - See repository for details

Contributing

Issues and pull requests welcome at daymade/claude-code-skills