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a2a-source-edit: write skills/data-workflow-design/SKILL.md

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---
name: data-workflow-design
description: "Design reusable extraction and transformation workflows for CSV, Excel, JSON, JSON-LD, and other structured data using a target JSON Schema."
---
# data-workflow-design
# Data Workflow Design
When creating an extraction and transformation workflow:
1. Identify the source format and parse strategy (csv, excel, json, jsonld, or text).
2. Inspect a bounded sample only; never assume unbounded rows are available.
3. Treat the supplied JSON Schema as the target contract. Required fields must be mapped or listed as gaps.
4. Prefer exact source field matches first, then case/space/punctuation-normalized matches.
5. Add transformation steps for type coercion, enum checks, date normalization, number parsing, trimming, and default handling.
6. Include validation gates before output: required fields, type checks, additionalProperties behavior, and per-field constraints.
7. Save a reusable JSON workflow spec with version, source profile, target schema, mapping rules, validation rules, and an execution receipt reference.
8. Never include credentials, platform tokens, database URLs, or raw oversized data in saved workflows.