aaron
9e86297e2a
Removes classify_retrieval_intent and the type/folder filter parameters on retrieve_context. The keyword classifier was the same anti-pattern as the formatting-driven docx chunker: a heuristic that locks the user into specific phrasings and fails silently on anything novel. A scope enum (personal / library / conversations / memory) would have been the same heuristic in a fancier wrapper — the categories themselves are mine, not Aaron's. New shape: a retrieve_documents tool exposed to Claude. Tool takes a single query argument; the model decides when to call it, what to search for, and how many times per turn (multi-query falls out naturally for compound asks). Pre-LLM retrieval is gone — memory still rides as ground truth in the prompt, but corpus content is fetched on demand by the model with concrete queries it crafts itself, not the user's raw phrasing. retrieve_context is now pure: hybrid retrieval + cross-encoder rerank + dedup, no filters. The reranker ranks, the model judges relevance. When ranking fails (e.g. abstract instructional queries pulling philosophy books), the right fix is a better reranker, not another query-time taxonomy. That work is acknowledged but deferred. System prompt updated to teach the model about the tool and to prefer concrete tokens (named entities, project names, course codes) over abstract phrasing when constructing search queries.