Run this skill for Phase 3 of the evidence verification pipeline — the adversarial audit step. Use when you need to check the evidence data lake for bad data before ingestion: dead links, wrong URL formats (tree/ vs blob/), subjective wording ("elite", "high-quality"), stale migration notes, or skills whose star tier doesn't match their classified evidence level. Triggers on phrases like: "audit the data lake", "adversarial check", "ev-adversarial-audit", "check for noise in evidence", "flag bad evidence", "run the audit phase", "quality check the tier files", or any reference to Phase 3 of the pipeline. Deploys 4 parallel adversarial reviewer subagents across the tier files, then a 5th synthesis subagent to merge findings, and appends results to the daily source report.
$npx -y skills add gaia-research/gaia-skill-tree --skill ev-adversarial-auditInstalls into the current project.
Run `npx skills use "https://github.com/gaia-research/gaia-skill-tree" --skill "gaia-research/gaia-skill-tree/ev-adversarial-audit"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/gaia-research/gaia-skill-tree" that are relevant to the current task. Run `npx skills add "https://github.com/gaia-research/gaia-skill-tree"` and select the relevant skills, then follow their instructions.