| name | 0.3.4-understand-pinecone_query |
| description | [0.3.4] A read operation that returns approximate nearest neighbors to a query vector with optional metadata filtering |
understand-pinecone_query
CALL NUMBER: deep_vector_database.pinecone_query
DEFINITION: A read operation that returns approximate nearest neighbors to a query vector with optional metadata filtering and namespace scoping.
Invoke this skill to understand pinecone_query down to its primitives. The RELATIVE ROOT below is the least-fixed-point closure of everything it bundles from — the full import cone, grouped by the lib each prim comes from. Projected from a prover-typed KB (MAP/SWI-Prolog consistency gate): every reference below resolves.
THE RELATIVE ROOT (the import cone, by lib)
from ?
- reads_from_pinecone_index (d1): The data access relationship where fetch or query operations retrieve stored records from a Pinecone index by id or vector similarity.
- receives_query_vector (d1): The input relationship where a query operation accepts an embedding vector as the basis for nearest-neighbor similarity search.
- returns_pinecone_similarity_score (d1): The output relationship where a query operation yields relevance scores indicating how closely each result matches the query vector.
- uses_approximate_nearest_neighbor_search (d1): The algorithm relationship where a Pinecone query executes ANN search to efficiently return near neighbors rather than exact matches.
Projected from the vector databases and embeddings KB (262 concepts / 150 relations) — consistency-typed by MAP; the facet list after the colon IS the cross-lib dependency web.
(leaf — this is an actual skill.)
