Wrap shell commands in datalad run to capture provenance.
npx skills add https://github.com/bcmcpher/my-skills --skill datalad-run
Please help me install this Agent Skill. Skill: datalad-run Source: https://github.com/bcmcpher/my-skills/tree/main/plugins/datalad-cli/skills/datalad-run Command: npx skills add https://github.com/bcmcpher/my-skills --skill datalad-run
Wraps a command in datalad run to capture provenance, recording inputs, outputs, and the exact command used in the dataset history so analyses are reproducible and auditable.
Provide the exact command you want to run and DataLad will wrap it with provenance and execute it.
High-intent search queries and answers about installing and using this skill.
To track dataset inputs and outputs, declare them explicitly with -i and -o flags when wrapping your command. This ensures DataLad properly records all dependencies and generated files in the dataset history.
Datalad run is used to execute commands while automatically capturing provenance for reproducible workflows. It validates dataset context and enforces meaningful commit messages to create auditable analysis records.
Yes, you can perform a dry run before executing a command in DataLad. This capability allows you to verify explicit flags and safety checks to ensure safe, auditable runs without modifying the dataset.
You ensure meaningful commit messages by providing a descriptive message with the -m flag when executing datalad run. The Skill enforces this requirement to maintain clear, auditable provenance records in your dataset history.
Yes, you need an existing DataLad-managed dataset to track command provenance. The Skill validates the dataset context and checks the dataset state before execution to ensure proper input and output tracking.
bcmcpherAutomate container provenance capture for DataLad runs.
kaifashraffTrack data provenance and lineage across construction systems for audits.
bcmcpherInspect file changes and dataset state in a DataLad repository.
bcmcpherTrace DataLad run provenance by listing and inspecting recorded runs.
