CoolFace
Datasetpublic

validation/ai-validation-checklists

AI Validation Checklists AI Validation Checklists is a structured reference dataset for validating AI systems across multiple system types and lifecycle stages. It is designed for practical use in: model validation, agent validation, RAG validation, tool-use validation, data validation, multimodal validation, system-level validation and governance. The dataset currently contains 60 practical validation checks. Important: These checks are an independent, practical framework… See the full description on the dataset page: https://huggingface.co/datasets/validation/ai-validation-checklists.

sourceHugging Faceupdated 21h agoView on Hugging Face
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DATA_DICTIONARY.md35 linesDownload Raw Back to root
1# Data Dictionary2 3## Controlled values4 5### system_type6- model7- agent8- rag9- tool10- data11- multimodal12- system13 14### severity15- medium16- high17- critical18 19### lifecycle_stage20- design21- pre-deployment22- deployment23- monitoring24 25### automation_level26- manual27- semi-automated28- automated29 30## Interpretation31 32`threshold_guidance` provides a starting point for project-specific validation design. It is not a universal compliance threshold.33 34`source_type = framework-inspired` means the checklist item is an independent operationalization informed by the cited source rather than a verbatim source requirement.35