What file types does this skill analyze?

The skill specifically scans and interprets .dig (Digdag) workflow files, .sql query files, and .yml configuration files within your project directory.

Why does this skill require codebase access?

To provide accurate documentation, the skill must extract real table names, SQL logic, and watermark configurations directly from your files rather than using generic placeholders.

Can I use the output for Confluence?

Yes, the skill generates structured Markdown that follows production-ready templates, making it easy to copy into Confluence, GitHub wikis, or other internal documentation tools.

What is a hist-union workflow?

A hist-union workflow is a data engineering strategy used to combine historical archived data with new incremental data into a single unified table structure.

APS Hist-Union Documentation Expert

Name: APS Hist-Union Documentation Expert
Author: treasure-data

bytreasure-data

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学習とドキュメンテーション

Generates comprehensive, production-ready documentation for data workflows that combine historical and incremental table strategies.

This skill automates the creation of detailed technical documentation for hist-union workflows by analyzing actual codebase artifacts like .dig, .sql, and .yml files. It extracts real schema definitions, watermark logic, and SQL UNION patterns to produce professional documentation for Confluence or internal wikis, ensuring that documentation accurately reflects the live implementation without relying on generic placeholders. It is specifically designed for developers managing complex data pipelines who need to maintain clear, accurate records of their data merging and backfill processes.

主な機能

012 GitHub stars

02Generates architectural overviews including directory trees and database purposes

03Maps watermark management and inc_log table structures automatically from source code

04Produces working SQL examples for incremental loads and full reloads directly from the codebase

05Documents historical and incremental data combination strategies and schema validation

06Analyzes Treasure Data workflows and SQL files to extract real implementation logic

ユースケース

01Creating standardized Confluence documentation for historical data backfill processes

02Validating and documenting schema consistency checks within hist-union layers

03Documenting complex data pipeline workflows for team knowledge sharing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add treasure-data/td-skills hist-union

For use in Claude.ai and ChatGPT

Download Skill