# AI Job Analysis And Relevancy

> - Use when checking whether an AI/ML selection tool is grounded in an adequate analysis of work and is demonstrably job-related — Concerns 2-3 of Tippins, Oswald & McPhail (2021). Covers whether a job analysis is necessary (even with a strong criterion-related relationship), acceptable forms and rigor, ONET and competency-model limits, collecting task importance ratings, SME-judgment agreement, and the legal meaning of job relatedness. Triggers: "does the AI tool need a job analysis", "is this algorithm job-related", "competency model vs job analysis for AI", "ONET as job analysis", "job relevancy of scraped predictors", "Guardians job analysis".

## Facts
- Page: https://tashan.sh/capability/skill-openmatter-network-ai-job-analysis-and-relevancy
- tashan id: skill:OpenMatter-Network/ai-job-analysis-and-relevancy
- Source: https://github.com/OpenMatter-Network/agent-io-skills
- Type: skill
- Category: ai
- 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-job-analysis-and-relevancy ~/.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.