nwb_validation

Run NWB Inspector validation and generate correction recommendations for NWB files.

1|1|Updated Aug 11, 2025

Search Tags:#validation #qa #metadata #nwb #nwbinpector #dandi #neurodata

Ready to run

npx skills add https://github.com/Python-AI-Solutions/agentic-neurodata-conversion --skill nwb-validation

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: nwb_validation
Source: https://github.com/Python-AI-Solutions/agentic-neurodata-conversion/tree/main/skill_documentation/nwb_validation
Command: npx skills add https://github.com/Python-AI-Solutions/agentic-neurodata-conversion --skill nwb-validation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires nwbinspector, pynwb, hdmf, pydantic.

What problem does it solve?

NWB validation is essential to ensure data quality and DANDI compatibility. This skill automates the NWB Inspector workflow, surfaces issues clearly, and provides structured guidance for fixes.

Core Features & Use Cases

NWB Inspector integration for compliance checks against the NWB schema
LLM-assisted issue prioritization, explanations, and correction recommendations
Automated correction context generation to support correction loops
Clear validation status and reports for reproducible data pipelines
End-to-end support for research workflows and NWB data quality assurance

Quick Start

Request a NWB validation by providing the path to an NWB file to the evaluation agent.

Frequently Asked Questions about nwb_validation

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

FAQPage Schema

How do I validate NWB files for DANDI compliance automatically?▼

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.

What is NWB Inspector used for in neurodata quality assurance?▼

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.

How do I get correction recommendations for NWB metadata validation errors?▼

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.

Can I use pydantic and pynwb to check NWB data quality in research pipelines?▼

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.

What is the best way to ensure DANDI-compliant NWB data before publishing?▼

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.

Why does my NWB file fail DANDI validation checks?▼

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.