Verify claims in Pyrite knowledge bases and generate traceable evidence reports.
npx skills add https://github.com/markramm/pyrite --skill fact-checker-markramm
Please help me install this Agent Skill. Skill: fact-checker Source: https://github.com/markramm/pyrite/tree/main/.claude/skills/fact-checker Command: npx skills add https://github.com/markramm/pyrite --skill fact-checker-markramm
This solution streamlines journalism-investigation knowledge management by validating claims against verifiable evidence, reducing rumor-driven errors.
From a journalism KB, identify a claim and run the fact-checker to produce a verification report with linked evidence.
High-intent search queries and answers about installing and using this skill.
To verify claims in an investigative journalism knowledge base, you can run an automated fact-checker that identifies unverified assertions, gathers corroborating or contradicting evidence, and generates a structured verification report with linked sources.
Evidence-driven fact-checking is a process that evaluates unverified assertions by enforcing an evidence-first rule, automatically linking claims to gathered sources to update confidence levels with an auditable provenance chain.
Generating an auditable verification report involves evaluating claims against gathered evidence, updating claim statuses and confidence levels, and outputting a comprehensive summary with reasoning, sources, and uncertainties for editorial review.
Yes, you can use fact-checking tools to manage evidence provenance by enforcing an evidence-first workflow that links claims to specific sources, creating full traceability for editorial review and reducing rumor-driven errors.
Yes, the fact-checker supports MCP tools specifically for claim and evidence management, allowing you to identify unverified claims and update their status with traceable evidence across investigative workflows.
Automated claim verification limitations include handling uncertainties in gathered evidence, requiring a structured journalism knowledge base to function, and outputting confidence levels rather than absolute truths to support editorial review.
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