nwb_validation

You can validate NWB files for DANDI compliance by running the NWB Inspector through an agent-based pipeline that identifies schema defects, interprets results, and provides structured correction recommendations automatically.

NWB Inspector is used for checking NWB data quality against the NWB schema to ensure compatibility. It surfaces defects and quality issues clearly while providing structured guidance for applying fixes.

To get correction recommendations for NWB metadata validation errors, the validation skill interprets NWB Inspector results and generates an automated correction context to support guided end-to-end correction loops.

Yes, the validation workflow leverages pynwb, hdmf, and pydantic dependencies to inspect NWB data quality, ensuring reproducible validation reports and structured correction guidance for research pipelines.

The best way to ensure DANDI-compliant NWB data is to run automated validation checks using NWB Inspector, which prioritizes issues and delivers structured correction contexts to resolve defects before publishing.

NWB files fail DANDI validation checks due to schema defects or metadata quality issues identified by the NWB Inspector, which then provides LLM-assisted explanations and recommendations to fix the specific problems.