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Descompone un objetivo de procesamiento en un flujo de nodos Chains (source → transform → sink). Use when the user wants to build a data pipeline / chain, or describes an end-to-end "load X, clean it, summarize, export" goal.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Sequence cleaning steps in a chain — trim/case/replace, null handling, deduplication, and type casting — in the right order. Use when raw ingested data needs cleaning before joins or aggregation.
Place Assert and Schema Validation nodes as gates that halt a chain when data is wrong, so bad data never reaches the output. Use when the pipeline must guarantee correctness before exporting or loading downstream.
Choose the right sink format, compression, and destination for a chain's output, and decide between exporting a file vs creating a table. Use at the end of a pipeline when deciding how to persist results.
Best practices for loading files into a chain — single file, folder globs, type detection, and union of many files. Use when the pipeline starts from CSV/Parquet/JSON/Excel files or a folder of files.
Decide between Merge (stack rows / UNION) and Join (match on a key) when a chain has multiple inputs, and set keys and join type correctly. Use when a pipeline combines two or more upstream tables.
Framework de razonamiento para convertir resultados de análisis en una narrativa visual clara y convincente
| name | Diseño de Pipeline |
| description | Descompone un objetivo de procesamiento en un flujo de nodos Chains (source → transform → sink). Use when the user wants to build a data pipeline / chain, or describes an end-to-end "load X, clean it, summarize, export" goal. |
| keywords | pipeline, flujo, chain, etl, elt, diseñar, construir, build, orquestar, pasos, steps, ingeniería, procesar, flujo de datos, automatizar |
| next | ingestion-patterns |
| scope | engineering |
Activa cuando el objetivo es construir un flujo de procesamiento en Chains, no analizar datos ad-hoc. Piensa como ingeniero de datos: entradas → transformaciones → salidas, con puntos de validación.
${nombre}) para rutas y umbrales reutilizables, no valores hardcodeados.Propón el flujo como lista ordenada de nodos con sus conexiones, y explica dónde van las puertas de calidad. Si el usuario confirma, constrúyelo nodo por nodo. Sugiere [[ingestion-patterns]] para la carga y [[data-quality-gates]] para las validaciones.