# Databricks Mlflow Evaluation

> MLflow 3 GenAI agent evaluation. Use when writing mlflow.genai.evaluate() code, creating @scorer functions, using built-in scorers (Guidelines, Correctness, Safety, RetrievalGroundedness), building eval datasets from traces, setting up trace ingestion and production monitoring, aligning judges with MemAlign from domain expert feedback, or running optimizeprompts() with GEPA for automated prompt improvement.

## Facts
- Page: https://tashan.sh/capability/skill-databricks-databricks-mlflow-evaluation
- tashan id: skill:databricks/databricks-mlflow-evaluation
- Source: https://github.com/databricks/databricks-agent-skills
- Type: skill
- Category: security
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: not measured
- Freshness: not measured
- Evidence coverage: not measured
- Health: not measured
- Instruction depth: not yet graded
- Official: no

## Install

```sh
cp -r databricks-mlflow-evaluation ~/.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.

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Measured 2026-08-04 by tashan (https://tashan.sh) from public evidence. Scorer s5.