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datalad-container-run

Automate container provenance capture for DataLad runs.

1|Updated Feb 25, 2026
Search Tags:#containerization#provenance#reproducibility#dataset#data-management#datalad#container-run
One-click install
npx skills add https://github.com/bcmcpher/my-skills --skill datalad-container-run
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: datalad-container-run
Source: https://github.com/bcmcpher/my-skills/tree/main/plugins/datalad-cli/skills/datalad-container-run
Command: npx skills add https://github.com/bcmcpher/my-skills --skill datalad-container-run

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Automates container provenance capture for DataLad runs.

Core Features & Use Cases

  • Workflow orchestration for containerized commands inside DataLad datasets, including dataset-context checks, container registration, parameter gathering, and execution reporting.
  • Attaches container image hashes and exact commands to commits to ensure reproducibility and full traceability through datalad rerun.
  • Supports management of registered containers (adding, listing, removing) and clear user prompts to guard dataset state before execution.

Quick Start

Identify the container and command you want to run, then execute the generated datalad container-run command within a DataLad dataset to start provenance tracking.

Frequently Asked Questions about datalad-container-run

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I capture container provenance for DataLad dataset runs?▼

To capture container provenance for DataLad runs, you automate the registration, parameter gathering, execution, and recording of containerized commands to ensure full traceability and reproducibility within a DataLad dataset.

How does datalad container-run track reproducibility for executed commands?▼

Datalad container-run tracks reproducibility by attaching container image hashes and exact commands to provenance-bearing commits, allowing you to reliably rerun workflows through datalad rerun.

What's the best way to register a container in a DataLad dataset before running it?▼

The best way to register a container in a DataLad dataset is using the datalad containers-add workflow, which gathers parameters and prompts you to guard the dataset state before execution.

Does DataLad container-run support managing registered containers?▼

Yes, DataLad container-run supports the management of registered containers, allowing you to add, list, and remove containers while maintaining provenance for containerized commands.

Can I use container-run to execute commands inside any DataLad dataset?▼

You can execute commands inside containers within a DataLad dataset, but the workflow applies dataset-context checks and clear user prompts to guard the dataset state before execution proceeds.

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