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lingxling/scientific-agent-skills

v2.72.0MIT

Ready-to-use scientific and research Agent Skills for biology, chemistry, medicine, and related workflows.

datalad

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 to siblings such as a GitHub repository plus a storage remote. Also use to decide between DataLad and plain Git for a data-carrying repository.

Version
1.2
License
MIT
Compatibility
Requires Python 3.10+, DataLad 1.6.5, Git, and git-annex 10.x. Tested with git-annex 10.20260901 and datalad-container 1.2.6 on macOS ARM64. Containers additionally require Singularity, Apptainer, or Docker. Remote data access needs network access and may need provider credentials. Local filesystem workflows work offline.
Read SKILL.md at the source

Pinned to revision 68105dd992f1, so it is the text this page describes rather than whatever the author pushed since.

Pre-approved tools experimental

Experimental field. Support varies between clients, so this list is what the author declared, not what your client will enforce.

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Files

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