Agent skill · Data & Analytics

preprocessing-data-with-automated-pipelines

Design and implement repeatable preprocessing pipelines for cleaning, encoding, transforming, and validating ML input data.

foryourhealth111-pixelgithub.com/foryourhealth111-pixelGitHub ↗
claude-codecodexcan modify filesships scriptsApache-2.0
Install
npx skills add foryourhealth111-pixel/Vibe-Skills --skill preprocessing-data-with-automated-pipelines --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 9
SKILL.md size: 1 KB
Bundled scripts: yes
Version: 1.0.0
Declared author: Jeremy Longshore <jeremy@intentsolutions.io>
Allowed tools: ReadWriteEditGrepGlobBash(cmd:*)
Path: bundled/skills/preprocessing-data-with-automated-pipelines/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,593
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Data Preprocessing Pipeline ## Positioning Use this skill as the direct owner for ML input-preparation pipelines. It covers preprocessing-heavy tasks where the requested deliverable is a repeatable pipeline for cleaning, encoding, transforming, and validating input data. ## When to Use Use this skill when: - Prepare raw data for machine learning models. - Automate data cleaning and transformatio

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About this skill
What does the preprocessing-data-with-automated-pipelines skill do?

Design and implement repeatable preprocessing pipelines for cleaning, encoding, transforming, and validating ML input data.

How do I install it?

Run `npx skills add foryourhealth111-pixel/Vibe-Skills --skill preprocessing-data-with-automated-pipelines --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From foryourhealth111-pixel/Vibe-Skills, a repository with 2,593 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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