# AI Audit Meta Components

> - Use when auditing the cross-cutting "meta" considerations of an AI/ML personnel assessment that apply across every other component — Components 10-12 of the Landers & Behrend (2023) framework: cultural context (power differentials, cross-cultural transfer, community participation), respect (conformance to accepted ethical standards — the Standards, SIOP Principles, OECD Principles, UGAI), and research designs (whether the studies behind every empirical claim are methodologically defensible). Triggers: "cross-cultural AI hiring", "power differentials in algorithm design", "ethical standards conformance audit", "are the studies behind the claims valid", "research design integrity of an AI audit", "community participation in AI design".

## Facts
- Page: https://tashan.sh/capability/skill-openmatter-network-ai-audit-meta-components
- tashan id: skill:OpenMatter-Network/ai-audit-meta-components
- Source: https://github.com/OpenMatter-Network/agent-io-skills
- Type: skill
- Category: design
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 71.0
- Freshness: 76.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- License: MIT
- Official: no

## Install

```sh
cp -r ai-audit-meta-components ~/.claude/skills/
```

## Security audit
Not scanned. We audit npm-published capabilities; this one has no npm package we can resolve, or has not reached the queue. This is not a clean bill of health.

---
Measured 2026-08-15 by tashan (https://tashan.sh) from public evidence. Scorer s5.