Add reranking, RRF fusion, bench harness, tag contexts, and data ingestion

Implements five of the six enhancements from docs/kb-enhancements-proposal.htm,
closing the retrieval-quality gap identified in the qmd review.

- Cross-encoder reranking: new kb/reranker.py loads an optional reranking
  model at startup (KB_RERANK_ENABLED, KB_RERANKER_MODEL,
  KB_RERANK_CANDIDATES). Search degrades gracefully to plain hybrid
  retrieval when the model is absent. Exposed via a "rerank" block in
  /status, a rerank flag on search, and --no-rerank in the CLI.
- RRF rank fusion: FTS and vector lists now merge by reciprocal rank
  fusion with a top-rank bonus, replacing the old score blend. Scores are
  comparable across queries.
- Bench harness and explain traces: kb bench runs a query fixture against
  each backend and reports precision@k, recall and MRR. --explain returns a
  per-result score breakdown.
- Tag context descriptions: tags carry an optional one-line description
  (kb tag-describe), returned as tag_contexts with search results. Adds a
  tags.description column migration.
- Structured data ingestion: .json/.yaml/.toml files ingest as text via the
  new "data" doc type, pretty-printing minified JSON before chunking.

Query expansion (proposal item 5) is deliberately left out pending bench
results. Requires engine v3.3.0.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>

mcp/engine.py

@@ -18,7 +18,8 @@ def _client() -> httpx.Client:
 
 def search(query: str, top: int = 10, tags: list[str] | None = None,
            doc_type: str | None = None, fts_only: bool = False,
-           vec_only: bool = False, threshold: float | None = None) -> dict:
+           vec_only: bool = False, threshold: float | None = None,
+           explain: bool = False, rerank: bool | None = None) -> dict:
     body: dict = {"query": query, "top": top}
     if tags:
         body["tags"] = tags
@@ -30,6 +31,10 @@ def search(query: str, top: int = 10, tags: list[str] | None = None,
         body["vec_only"] = True
     if threshold is not None:
         body["threshold"] = threshold
+    if explain:
+        body["explain"] = True
+    if rerank is not None:
+        body["rerank"] = rerank
     with _client() as c:
         r = c.post("/api/v1/search", json=body)
         r.raise_for_status()