api.py: tool-call retrieval, drop the keyword intent classifier

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.

scripts/test_retrieval.py

@@ -14,7 +14,7 @@ load_dotenv(Path.home() / "aaronai" / ".env", override=True)
 sys.path.insert(0, str(Path(__file__).parent))
 
 # Stub anthropic so api.py import doesn't fail without the SDK loaded.
-# We only need retrieve_context + classify_retrieval_intent.
+# We only need retrieve_context.
 import types
 sys.modules.setdefault("anthropic", types.ModuleType("anthropic"))
 sys.modules["anthropic"].Anthropic = lambda **kw: None
@@ -34,27 +34,20 @@ except Exception as e:
     print(f"(continuing despite api.py side-effect error: {e})")
 
 retrieve_context = api.retrieve_context
-classify_retrieval_intent = api.classify_retrieval_intent
 
 QUERIES = [
     "write me a bio",
     "my professional bio",
-    "draft a bio for the Utah application",
     "Aaron Nelson CV consulting and design work",
     "FWN3D consulting",
     "syllabi I have taught",
     "philosophy of teaching",
-    "what did I tell Claude about FWN3D",
-    "what did we discuss about the Utah job",
     "Hudson Valley Additive Manufacturing Center",
+    "Aaron Nelson is an artist and educator working in additive manufacturing",
 ]
 
 for q in QUERIES:
-    type_filter, folder_excludes = classify_retrieval_intent(q)
-    pieces, sources = retrieve_context(
-        q, type_filter=type_filter, folder_exclude_prefixes=folder_excludes,
-    )
+    pieces, sources = retrieve_context(q)
     print(f"\n=== {q!r} ===")
-    print(f"  type_filter: {type_filter}  folder_excludes: {folder_excludes}")
     for i, src in enumerate(sources, 1):
         print(f"  {i}. {src}")