perf: Tier 4c — optional rayon parallelism for HNSW prune_connections

Add a default-off `parallel` feature to clawhdf5-ann (rayon optional dep),
matching the convention already used in clawhdf5-format/clawhdf5-agent.
Gate prune_connections' per-neighbor distance computation on it — a pure
read-only map with no shared mutable state, sorted immediately after, so
swapping to rayon's par_iter is low-risk.

Deliberately not touching build_with_metric's outer insert loop per the
original plan: it has genuine cross-iteration data dependencies (graph
mutation, entry-point updates) and needs its own correctness-focused
design pass. The win here is likely small since neighbor lists are
bounded by m/m_max0 (typically small) — this is a low-risk completeness
item, not a headline perf change.

Verified identical results with default features and --features parallel
across the full HNSW test suite (23/23 both ways), including the
build+search end-to-end tests (build_small_index, search_accuracy_cosine,
incremental_insert_matches_batch_recall).

crates/clawhdf5-ann/src/hnsw.rs

@@ -857,6 +857,15 @@ fn prune_connections(
     if neighbors.len() <= max_conn {
         return;
     }
+    #[cfg(feature = "parallel")]
+    let mut scored: Vec<(usize, f32)> = {
+        use rayon::prelude::*;
+        neighbors
+            .par_iter()
+            .map(|&n| (n, compute_distance(&vectors[node], &vectors[n], metric)))
+            .collect()
+    };
+    #[cfg(not(feature = "parallel"))]
     let mut scored: Vec<(usize, f32)> = neighbors
         .iter()
         .map(|&n| (n, compute_distance(&vectors[node], &vectors[n], metric)))