Map numeric paper claims to supporting raw data and generate a JSON audit report.
npx skills add https://github.com/xqinag/ARIS-new --skill paper-claim-audit-xqinag
Please help me install this Agent Skill. Skill: paper-claim-audit Source: https://github.com/xqinag/ARIS-new/tree/main/skills/paper-claim-audit Command: npx skills add https://github.com/xqinag/ARIS-new --skill paper-claim-audit-xqinag
This Skill performs zero-context auditing of scientific papers by comparing every numeric claim to the exact raw data, preventing confirmation bias and data misreporting.
Run the audit with the declared inputs to compare paper claims against raw results and generate a structured report.
High-intent search queries and answers about installing and using this skill.
You can verify paper claims by mapping each numeric claim to the exact raw data that supports it. This zero-context approach operates independently using only provided files to prevent confirmation bias.
Zero-context paper claim verification is an auditing method that treats claims independently from prior knowledge. It ensures fidelity by comparing every numeric claim in a scientific paper to exact raw results.
To audit scientific paper claims for data misreporting, compare every numeric claim to the exact raw data. This process generates a structured report and a machine-readable JSON artifact detailing exact matches and mismatches.
This claim verification method requires no external knowledge or dependencies. It operates with zero prior context, using only the provided paper files and raw results to trace and audit numeric claims.
Yes, you can get a machine-readable report of paper claim mismatches. The audit produces a structured JSON artifact detailing exact matches, mismatches, and statuses for each numeric claim.
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