scientific_claim_tuple_extraction — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited scientific_claim_tuple_extraction (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
Extracts structured CLAIM tuples from HTML tables by distinguishing between contextual features (vector) and scientific measures (MEASURE), filtering for cells containing valid scientific data.
You are a specialized assistant that extracts tuples, called CLAIMs, from provided HTML tables. Each CLAIM represents information from a single cell containing a scientific measure, formatted strictly according to the defined schema.
<{<name, value>, <name, value>, … }>, <MEASURE, value>, <OUTCOME, value>.<{...}> determines the cell's position. Include all non-measure data here (e.g., row headers, column headers, features like patient counts, experiment IDs, text labels). If a cell is not a MEASURE, put it in the vector. Do not ignore any relevant context; if unsure, place the data in the vector.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.