feat(agent): selectable fusion; adopt the measured 0.4/0.6 default weights

BENCHMARKS.md has recorded since the weight sweep that the 0.7/0.3 default is
strictly dominated by 0.4/0.6 over the full LongMemEval haystack, but the
shipping code never adopted it: unified_search and the OpenClaw backend both
passed 0.7/0.3. Re-running the sweep here (500 questions, real MiniLM
embeddings on a GPU) reproduces it — turn-level Hit@1 51.6% vs 44.2%, Hit@5
81.4% vs 79.2%, Hit@10 87.8% vs 85.8%, MRR 0.6430 vs 0.5856 — so both now use
hybrid::DEFAULT_FUSION, which is that operating point and carries the
reasoning. A unit test pins it.

Fusion is also selectable now. hybrid::Fusion is either Weighted { vector,
keyword } or Rrf { k }; hybrid::fuse applies either to one candidate list per
stage, and merge_vector_keyword / hybrid_search delegate to it, so the public
API is unchanged. New HDF5Memory::hybrid_search_with and
hybrid::hybrid_search_fused take a Fusion. Reciprocal rank fusion was
implemented but reachable only as a free function over a linear scan, so it
had never been compared with the weighted sum on equal terms; it is now a mode
in the LongMemEval bench (measurement to follow).

Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>

crates/clawhdf5-agent/src/openclaw.rs

@@ -531,11 +531,14 @@ impl MemoryBackend for ClawhdfBackend {
         query_embedding: &[f32],
         k: usize,
     ) -> Vec<MemorySearchResult> {
-        // 1. Hybrid retrieval (RRF-blended vector + BM25).
+        // 1. Hybrid retrieval (vector + BM25, fused by score).
         let candidates = k.saturating_mul(3).max(10);
-        let raw = self
-            .memory
-            .hybrid_search(query_embedding, query_text, 0.7, 0.3, candidates);
+        let raw = self.memory.hybrid_search_with(
+            query_embedding,
+            query_text,
+            crate::hybrid::DEFAULT_FUSION,
+            candidates,
+        );
 
         if raw.is_empty() {
             return Vec::new();