adni-skill

ADNI data orchestration stages raw NIfTI files into BIDS-ready datasets by defining a high-level workflow contract that enforces dataset organization, logging, and artifact generation. It coordinates data validation before delegating execution to tool skills.

Yes, you can run fMRIPrep preprocessing and DK68 ROI extraction in one workflow. The orchestration spans full fMRIPrep-based preprocessing with DK68 ROI extraction and quality control, moving from raw NIfTI staging to downstream analysis outputs.

The best way to generate VQA datasets from ADNI histories is using the optional VQA generation feature. It creates VQA datasets for longitudinal analysis and task-based assessments directly from task outputs and longitudinal ADNI histories.

Yes, ADNI workflow execution requires claw-shell tool skills. The Skill itself defines what to do and coordinates data organization, while delegating all heavy lifting execution, including fMRIPrep preprocessing, to claw-shell tool skills.

Yes, you need pandas installed to run the ADNI data orchestration workflow. Pandas is a required dependency for executing the scripts that coordinate the staging, preprocessing, and ROI extraction processes.

The plan-driven contract limits direct execution control, as the Skill defines the workflow plan and delegates heavy lifting to claw-shell tool skills. Users cannot manually bypass the enforced dataset organization, logging, and artifact generation steps during processing.