Fetch annexed content and initialize subdatasets in DataLad datasets.
npx skills add https://github.com/bcmcpher/my-skills --skill datalad-get
Please help me install this Agent Skill. Skill: datalad-get Source: https://github.com/bcmcpher/my-skills/tree/main/plugins/datalad-cli/skills/datalad-get Command: npx skills add https://github.com/bcmcpher/my-skills --skill datalad-get
DataLad contexts often include missing file content or absent subdatasets. This Skill retrieves annexed content and initializes subdatasets so work can proceed without manual dataset setup.
Fetch the missing content or initialize an absent subdataset by targeting the desired path.
High-intent search queries and answers about installing and using this skill.
To fetch annexed content from a DataLad dataset, target the desired file or directory path to retrieve missing data from configured siblings. This initializes absent subdatasets and downloads content without requiring manual dataset setup.
Initializing absent subdatasets requires targeting the desired path within your DataLad dataset. This action prepares the dataset structure and retrieves metadata, allowing you to inspect the hierarchy before committing to a full data download.
Yes, you can retrieve DataLad dataset metadata without downloading full content by using the -n retrieval mode. This read-only mode fetches structural information and initializes subdatasets while avoiding the bandwidth costs of full file retrieval.
Yes, datalad-get supports recursive retrieval for nested subdatasets using the -r mode. This allows you to fetch annexed data content and initialize absent subdatasets across the entire dataset hierarchy to your specified depth.
You can selectively download annexed files by targeting specific file or directory paths within your DataLad dataset. This selective retrieval mode fetches only the required content, balancing bandwidth usage against the depth of your data fetch.
DataLad files are missing content after cloning because datasets often contain annexed file pointers rather than actual data. You must fetch the annexed content from configured siblings to retrieve the missing files and initialize any absent subdatasets.
bcmcpherPush saved DataLad dataset state to a configured remote.
bcmcpherDrop or remove annexed files from local DataLad datasets.
bcmcpherAutomate saving changes in DataLad datasets with datalad save.
a-takCommit changes, push to origin, and create a GitHub Pull Request.
