datalad-update

Fetch sibling changes and merge them into DataLad datasets recursively.

1|Updated Feb 25, 2026

Search Tags:#update #dataset #recursion #datalad #subdataset #sibling

Ready to run

npx skills add https://github.com/bcmcpher/my-skills --skill datalad-update

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: datalad-update
Source: https://github.com/bcmcpher/my-skills/tree/main/plugins/datalad-cli/skills/datalad-update
Command: npx skills add https://github.com/bcmcpher/my-skills --skill datalad-update

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Fetches changes from a sibling and optionally merges them into the current DataLad dataset.

Core Features & Use Cases

Handles updates across DataLad datasets with nested subdatasets.
Supports configurable merge strategies, explicit prompts, and recursive updates for reproducible workflows.
Use case: synchronize data across collaborators by pulling from a shared sibling while preserving the superdataset's pinned state.

Quick Start

Run the datalad-update command to fetch and integrate changes from a chosen sibling.

Frequently Asked Questions about datalad-update

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

FAQPage Schema

How do I update a DataLad dataset with nested subdatasets from a sibling?▼

To update a DataLad dataset with nested subdatasets, fetch changes from a sibling repository and optionally merge them recursively. This enforces explicit merge strategies and prompts for user decisions to keep worktrees consistent.

Can I recursively pull changes for DataLad subdatasets without losing the superdataset's pinned state?▼

Yes, you can recursively pull changes for DataLad subdatasets while preserving the superdataset's pinned state. Controlled follow policies and configurable merge strategies ensure the superdataset configuration remains intact during synchronization.

What merge strategies are supported when synchronizing DataLad worktrees?▼

When synchronizing DataLad worktrees, explicit merge strategies are enforced and user decisions are prompted during execution. The process fetches changes from a sibling and reports fetched refs and changes after applying the merge.

How does DataLad handle fetching and merging refs across multiple subdatasets?▼

DataLad handles fetching and merging refs across multiple subdatasets by applying recursive updates with controlled follow policies. It enforces explicit merge strategies, prompts for user decisions, and reports fetched refs and changes after execution.

Is there a way to synchronize data across collaborators by pulling from a shared DataLad sibling?▼

Yes, you can synchronize data across collaborators by pulling from a shared DataLad sibling. The update process fetches changes, optionally merges them into the current dataset, and preserves the superdataset's pinned state for reproducible workflows.