datalad SKILL.md skillA
datalad from k-dense-ai/scientific-agent-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add k-dense-ai/scientific-agent-skills/datalad@v1.2Pins v1.2 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- k-dense-ai/scientific-agent-skills
- Path
skills/datalad/SKILL.md- Versions recorded
- 3
- Latest version
- v1.2, committed Oct 1, 2026
- First version recorded
- Sep 10, 2026
- Size
- 17,431 bytes
- Repository stars
- 56,497
- License
- MIT
Retrieves, versions, and publishes scientific datasets with DataLad and git-annex, and captures computational provenance with datalad run, rerun, and containers-run. Use when cloning or fetching data from OpenNeuro, DANDI, datasets.datalad.org, or any DataLad dataset; when a file in a dataset reads as a broken symlink or a small pointer instead of real data; when an analysis needs a machine-readable record of how each output was produced so it can be re-executed; or when publishing a dataset…
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# DataLad ## Overview DataLad is a data management layer over Git and git-annex. Git tracks the dataset structure, small text files, and the history. git-annex tracks the *content* of large files, storing each file as a key and keeping the bytes somewhere that is not necessarily the local repository. A normal clone retrieves Git history and the top-level file listing while leaving annexed bytes unfetched. Installed subdatasets have their own histories; a clone does not automatically populate them. Clone cost depends on Git history and file count, not just the data volume. Retrieve annexed bytes selectively with `datalad get`. The second thing DataLad adds is provenance. `datalad run` executes a command and commits the result together with a machine-readable record of the command, its inputs, and its outputs. `datalad rerun` reads that record back and re-executes it. This turns "how was this figure produced" from an archaeology problem into a command. ## When to use DataLad instead of plain Git Use DataLad when any of the following holds: - Files are too large for Git to handle comfortably, or the total exceeds what every collaborator wants on disk. …
Read the whole file at its exact version.
How to install
mdr add k-dense-ai/scientific-agent-skills/datalad@sha256:bb902427db0c501dThe line at the top of this page pins the label v1.2, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_lqtobpxparjtme3z)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 3 versions of this file, between Sep 10, 2026 and Oct 1, 2026, about one every 10 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.2 latest | 2026-10-01 | a92663a | 17,431 B | A | view · diff |
| v1.1 | 2026-09-30 | ce9e6e9 | 15,941 B | A | view · diff |
| v1.0 | 2026-09-10 | 34ad8b7 | 15,559 B | A | view |
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (17431 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
k-dense-ai/scientific-agent-skills · 56,497 stars · license MIT · pushed 2026-11-02 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_lqtobpxparjtme3z GET https://markdownregistry.com/api/v1/resolve?ref=k-dense-ai/scientific-agent-skills/datalad GET https://markdownregistry.com/api/v1/blob/bb902427db0c501db4187aafd3433eea67fa1071348cf07adcea2558ed49debb
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.