Guides agents in designing and operating data infrastructure, including databases, ETL/ELT pipelines, analytical SQL, data quality monitoring, migrations, storage, and model-assisted transformation controls.
Design and operate data infrastructure — database operations (vector, relational, graph, time-series), ETL/ELT pipeline design (dbt patterns, incremental loading), SQL analytical patterns, data quality monitoring, schema migration, and storage infrastructure management, including model-assisted transformation contracts, deterministic acceptance, bounded retries, and sink reconciliation. Do not use for statistical analysis or ML model development.
evals/evals.json
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README.md
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templates/ai-stage-contract.md
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references/ai-transformation-boundaries.md
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references/backup-and-recovery.md
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references/database-migrations.md
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references/data-quality.md
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references/dbt-patterns.md
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references/etl-pipeline-design.md
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references/graph-databases.md
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references/sql-analytical-patterns.md
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references/time-series-databases.md
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references/vector-db-operations.md
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SKILL.md
SKILL.md
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