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DataLad Data Management

Fetch, version, and publish large datasets with DataLad, and record reproducible provenance for analyses.

Source Download skill
Repository
K-Dense-AI/scientific-agent-skills
Stars
55,780
Licence
MIT
Files
4 files

What it does

This skill teaches the agent how to work with DataLad, a tool that versions large scientific datasets on top of Git and git-annex. Once installed, the agent knows to fetch real file contents before reading data (instead of treating a placeholder link as the file), to use datalad run and rerun so each output has a machine-readable record of the command that produced it, and to decide when DataLad is worth using over plain Git. It also covers publishing datasets to sibling repositories and storage remotes.

Great for

  • Researchers cloning public datasets from OpenNeuro, DANDI, or datasets.datalad.org
  • Lab members who need reproducible, re-runnable analysis records for methods sections
  • Data stewards deciding how to version and publish large research datasets

Skip it if

  • Code-only or small text repositories, where DataLad adds complexity without benefit (the skill itself says plain Git is better there)
  • Users who cannot install git-annex or Git, since the workflows depend on them
  • Sensitive or protected data handled without checking access rules, because fetching and publishing move real data over the network

Try asking

  • “Clone the OpenNeuro dataset ds000001 and fetch just the anatomical files for subject 01”
  • “Record an FSL brain-extraction step with datalad run so the output can be re-executed later”
  • “Figure out why my NIfTI file says 'not a gzip file' after cloning a DataLad dataset”
  • “Publish my dataset to a GitHub repository plus an S3 storage remote”
Step-by-step guide: how to use DataLad Data ManagementInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 4 original files, the MIT licence and an attribution note.

    datalad.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip datalad.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip datalad.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Run datalad wtf --section dependencies first when behaviour seems impossible, since an old or missing git-annex causes many confusing errors.
  • Fetch data explicitly with datalad get before any analysis, and do not assume a file that exists is complete.
  • Review the commands datalad run will execute before approving them, since they run on your machine and may write or overwrite outputs.

What's inside

  • references/data-access.md
  • references/provenance.md
  • references/publishing.md
  • SKILL.md

Redistributed unmodified from K-Dense-AI/scientific-agent-skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.