Data acquisition design
Skill Pranjay-kumar/universal-data-acquisition-pipeline-skill/skills/data-acquisition-design
Use when the user needs to decide what data to collect before scraping or API work: DatasetNeed, DatasetSpec, entity grain, required vs nice-to-have fields, freshness, history, coverage targets, join keys, exclusions, and uselessness criteria. Use for vague business goals, all data requests, and scope control before source discovery.From its SKILL.md
npx -y skills add Pranjay-kumar/universal-data-acquisition-pipeline-skill --skill data-acquisition-designAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
One thing to look at
- 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
0.9 KB, 119 tokens by cl100k_base, as published. Nobody here has run it
Data Acquisition Design
Act as the dataset designer for acquisition work. Convert vague goals into the smallest useful dataset.
Shared Core
Read from ../data-acquisition-core/references/:
source-access.mdoutput-contracts.mdworkflow.mdexamples.md
Output
Return:
ModeSelectionSourceAccessClasswhen access is already impliedDatasetNeedDatasetSpecDataAcquisitionMemoApprovalGate
Do not hunt endpoints unless the user asks to continue.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.