Trace DataLad run provenance by listing and inspecting recorded runs.
npx skills add https://github.com/bcmcpher/my-skills --skill datalad-log
Please help me install this Agent Skill. Skill: datalad-log Source: https://github.com/bcmcpher/my-skills/tree/main/plugins/datalad-cli/skills/datalad-log Command: npx skills add https://github.com/bcmcpher/my-skills --skill datalad-log
Browse and audit DataLad dataset histories by listing runs, inspecting provenance, and tracing the command that produced outputs.
List the run history for a dataset and inspect provenance for a specific commit or file without re-running analyses.
High-intent search queries and answers about installing and using this skill.
To trace file provenance in a DataLad dataset, locate the commit that touched the file and extract run metadata using datalad rerun --report to reveal the generating command and inputs without re-executing the workflow.
Auditing DataLad run history without re-execution is done by listing recorded runs with datalad log --oneline and inspecting specific commits with datalad rerun --report to view full provenance details.
You list recorded DataLad runs by applying datalad log --oneline to the dataset, which surfaces the run history and allows you to identify commits for subsequent provenance inspection.
Yes, you can inspect DataLad provenance for a specific commit without re-running by applying datalad rerun --report, which extracts and presents the run metadata directly from the recorded history.
Dataset provenance traceability is needed for debugging workflows because it identifies the exact command and inputs that generated an output across commits, allowing you to isolate data lineage issues without re-execution.
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