NLWeb Schema.org Grounding

Before writing code

Fetch live references:

1. Fetch https://schema.org/ for the canonical Schema.org vocabulary.
2. Fetch https://github.com/nlweb-ai/NLWeb/blob/main/config/site_types.xml in the live repo for the exact list of supported Schema.org types and the tool inheritance tree per type.
3. Fetch https://github.com/nlweb-ai/NLWeb/blob/main/docs/nlweb-prompts.md for how per-type prompts and <returnStruc> shapes work.
4. Web-search schema.org JSON-LD validator — Google's Rich Results Test is a quick way to validate before ingest.
5. Check AskAgent/python/methods/recipe_substitution.py, accompaniment.py, compare_items.py for examples of how type-specific tools consume the schema_object.

Conceptual Architecture

Why Schema.org Matters to NLWeb

NLWeb's defining design choice: results carry their full Schema.org object back to the agent. Unlike a generic RAG system that returns text chunks, NLWeb returns structured JSON-LD — so an agent receiving a Recipe result gets ingredients, cookTime, nutrition, recipeYield, not just a paragraph of text. This is what makes NLWeb results agent-actionable.

R.V. Guha (NLWeb's author) co-created Schema.org for exactly this reason — the data was already structured; NLWeb finally exposes it to agents.