ai-data-engineering
byancoleman· 58 skills
Data pipelines, feature stores, and embedding generation for AI/ML systems. Use when building RAG pipelines, ML feature serving, or data transformations. Covers feature stores (Feast, Tecton), embedding pipelines, chunking strategies, orchestration (Dagster, Prefect, Airflow), dbt transformations, data versioning (LakeFS), and experiment tracking (MLflow, W&B).
How to install ai-data-engineering?
ancoleman/ai-design-components/ai-data-engineering
$npx -y skills add ancoleman/ai-design-components --skill ai-data-engineeringInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/ancoleman/ai-design-components" --skill "ancoleman/ai-design-components/ai-data-engineering"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/ancoleman/ai-design-components" that are relevant to the current task. Run `npx skills add "https://github.com/ancoleman/ai-design-components"` and select the relevant skills, then follow their instructions.
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