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Multi-agent adversarial verification: two independent reviewers with the same rubric must both pass before output ships, with a fix-and-re-review convergence loop and human escalation cap. Use when gating publishing, production deploys, compliance or brand-sensitive content, or hallucination-prone claims before they ship.
santa-method is an agent skill entry in ChatHome Skills, sourced from GitHub Skill Search and scored 58/100. # Santa Method Multi-agent adversarial verification framework. Make a list, check it twice. If it's naughty, fix it until it's nice. The core insight: a single. As an agent skill, it packages a reusable instruction set that AI coding agents such as Codex and Claude Code can load to perform this task without hand-written glue code. ChatHome Skills discovered this entry through its daily ingest of official registries and GitHub discovery queries, and re-verifies repository facts, freshness signals, and install metadata on every run. The quality score weighs official-registry presence, a working install command, license clarity, GitHub star trajectory, and repository freshness — the full formula is on the Sources page. The install command above is ready to copy. Review the last-pushed date and repository status before adding santa-method to a production agent workflow; the snapshot facts below are point-in-time values from the most recent ingest.
codex skill install Userrnaame/absensi-sekolahReview the upstream source before running this command.
Scan coverage: Install metadata and the indexed document body.
Automated signals from install metadata and a bounded skill body — not a full code security audit and not a recursive source or dependency review.
# Santa Method Multi-agent adversarial verification framework. Make a list, check it twice. If it's naughty, fix it until it's nice. The core insight: a single agent reviewing its