data-versioning-manager

Skill for managing data versions and provenance

509 stars

Best use case

data-versioning-manager is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Skill for managing data versions and provenance

Teams using data-versioning-manager should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

You only need a quick one-off answer and do not need a reusable workflow.
You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/data-versioning-manager/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/science/scientific-discovery/skills/data-versioning-manager/SKILL.md"

Manual Installation

Download SKILL.md from GitHub
Place it in .claude/skills/data-versioning-manager/SKILL.md inside your project
Restart your AI agent — it will auto-discover the skill

How data-versioning-manager Compares

Feature / Agent	data-versioning-manager	Standard Approach
Platform Support	Not specified	Limited / Varies
Context Awareness	High	Baseline
Installation Complexity	Unknown	N/A

Frequently Asked Questions

What does this skill do?

Skill for managing data versions and provenance

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Data Versioning Manager Skill

## Purpose

Manage data versions, track provenance, and ensure data lineage for reproducible scientific research.

## Capabilities

- Version datasets
- Track data lineage
- Document transformations
- Enable rollback
- Support collaboration
- Generate provenance

## Usage Guidelines

1. Initialize versioning
2. Track data changes
3. Document transformations
4. Create snapshots
5. Manage branches
6. Export provenance

## Process Integration

Works within scientific discovery workflows for:
- Data management
- Reproducibility support
- Collaboration enabling
- Audit compliance

## Configuration

- Version control system
- Storage backends
- Metadata schemas
- Access controls

## Output Artifacts

- Version histories
- Provenance records
- Transformation logs
- Data snapshots

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