DTLS Extractor

DTLS extractor processes unstructured tool descriptions to generate a formal metadata model with fields such as name, inputs, outputs, features, scope, and localization. It normalizes terminology, maps synonyms to canonical terms, and outputs machine-readable JSON-ready structures suitable for catalogs and APIs. The tool supports multi-language inputs and consistent schema output to enable bulk processing of large tool inventories. Use cases include new tool submissions, content audits, and data migrations where standardized, query-friendly metadata is required. Core capabilities include field discovery, schema normalization, validation rules, and localization mapping to regional units and languages. Benefits include faster onboarding of tools into directories, improved search indexing through consistent metadata, and easier integration with AI-assisted content workflows. Typical outputs are structured data blocks with precise types and units, enabling programmatic ingestion by search engines and catalog front-ends. Examples: extracting an inputs field with name, type, and units from a description; extracting outputs with expected results and formats; generating a localized description template for multiple regions. This tool differentiates itself by enforcing a formal data model, handling localization at the field level, and supporting scalable, repeatable extraction across large tool sets.