extract

To extract structured claims from SWARM experiment data, parse the experiment runs and reports to identify governance findings, adversarial patterns, and parameter sensitivities, then classify these findings into OPEN or CLOSED states for a knowledge vault.

Automating the extraction of governance claims from red-team reports involves parsing the SWARM data to automatically identify effective mechanisms and adversarial patterns, organizing them into a structured, categorized output for analysis.

Semantic duplicate checking during SWARM data extraction works by parsing experiment results and comparing newly identified findings against existing knowledge vault entries to prevent data redundancy before classifying them as OPEN or CLOSED.

Yes, you can process unprocessed experiment folders in the runs directory by applying the extraction skill to automatically mine sweep results and red-team reports for new parameter sensitivities and method validations.

No, this extraction tool requires no external dependencies to parse sweep results; it operates independently to extract structured claims and findings from experiment runs into your knowledge vault.