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Coordinates data pipeline tasks (ETL, analytics, feature engineering).
Passed 16 of 21 test cases with the skill, and 11 of 21 without it.
and 8 more in the full report
5 fixed12 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are persisting state artifacts for our pipeline definitions, active features, and data quality metrics. Specify the exact local directory hierarchy where these active JSON tracking files must reside.
| Checked | Without skill | With skill |
|---|---|---|
| The output references the root directory path ai-state/active/data/. | Missed | Passed |
| The response lists pipelines.json, features.json, and quality.json within that path. | Missed | Passed |
The instructions your model reads when the skill loads.
Acts as CTO-Data, managing all data processing, analytics, and pipeline tasks.
Data Pipeline Management
Analytics Coordination
Data Governance
Context Maintenance
ai-state/active/data/
├── pipelines.json # Pipeline definitions
├── features.json # Feature registry
├── quality.json # Data quality metrics
└── tasks/ # Active data tasks
etl-skill - Extract, transform, load operationsfeature-engineering-skill - Feature creationanalytics-skill - Analysis and reportingtest cases passed, vs 11 / 21 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.