santa-method
Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.
npx skills add mturac/everything-openai-codex --skill santa-method --agent codex
Same command for any agent — swap --agent for claude-code, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 own output shares the same biases, knowledge gaps, and systematic errors that produced the output. Two independent reviewers with no shared context break this failure mode. ## When to Activate Invoke this skill when: - Output will be published, deployed, or consumed by end users - Compliance, regulatory, or brand constraints must be enforced - Code ships to production without human review - Content accuracy matters (technical docs, educational material, customer-facing copy) - Batch generation at scale where spot-checking misses systemic patterns - Hallucination risk is elevated (claims, statistics, API references, legal language) Do NOT use for internal drafts, exploratory research, or tasks with deterministic verification (use build/test/lint pipelines for those). ## Architecture ``` ┌─────────────┐ │ GENERATOR │ Phase 1: Make a List │ (Agent A) │ Produce the deliverable └──────┬───────┘ │ output ▼ ┌──────────────────────────────┐ │ DUAL INDEPENDENT REVIEW │ Phase 2: Check It Twice │ │ │ ┌───────────┐ ┌
- When to Activate
- Architecture
- Phase Details
- Phase 1: Make a List (Generate)
- Phase 2: Check It Twice (Independent Dual Review)
- Rubric Design
- Phase 3: Naughty or Nice (Verdict Gate)
- Phase 4: Fix Until Nice (Convergence Loop)
- Implementation Patterns
- Pattern A: OpenAI Codex Subagents (Recommended)
- Pattern B: Sequential Inline (Fallback)
- Pattern C: Batch Sampling
- Failure Modes and Mitigations
- Integration with Other Skills
In a OpenAI Codex session, use the Agent tool to spawn reviewers Both agents run in parallel for speed
What does the santa-method skill do?
Multi-agent adversarial verification with convergence loop. Two independent review agents must both pass before output ships.
How do I install it?
Run `npx skills add mturac/everything-openai-codex --skill santa-method --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From mturac/everything-openai-codex, a repository with 84 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.