ci: wire up CI, fix no_std build, fix stale package names in scripts

- Add .gitea/workflows/ci.yml running scripts/ci-test.sh (fmt, clippy,
  test, no_std check) on push/PR to main.
- Fix stale rustyhdf5-py/rustyhdf5-format package names in
  ci-test.sh/check-nostd.sh, which had been silently no-op'ing those
  checks (cargo warns but doesn't fail on an unknown --exclude/-p
  target).
- With those checks actually running, fix the real issues they surface:
  - clippy: useless_conversion in chunked_write.rs, byte_char_slices in
    global_heap.rs/object_header.rs.
  - cargo fmt: apply formatting across the workspace (whitespace only).
  - no_std (thumbv7em-none-eabihf) build errors in clawhdf5-format:
    core::sync::atomic::AtomicU64 doesn't exist on that target (no
    native 64-bit atomics) — switch profiling.rs's counters to
    portable-atomic, which falls back to a CAS-based emulation there
    and is a no-op wrapper elsewhere. Add missing alloc imports for
    Box (filters.rs), Vec (filters_szip.rs), and format! (dict_encoding.rs)
    on no_std paths. Replace f64::powi (std/libm-only) with a small
    local exponentiation-by-squaring helper in the scale-offset filter.

crates/clawhdf5-agent/src/search.rs

@@ -26,9 +26,7 @@ impl HDF5Memory {
     ) -> Vec<(usize, f32)> {
         self.ensure_hnsw_fresh();
         match self.hnsw.as_ref() {
-            Some(index)
-                if !index.is_empty() && index.dimension() == query_embedding.len() =>
-            {
+            Some(index) if !index.is_empty() && index.dimension() == query_embedding.len() => {
                 // Over-fetch so the merge sees a useful vector pool; cosine
                 // distance from the index converts back to similarity (1 - d).
                 let pool = (k * 8).max(64);
@@ -38,7 +36,13 @@ impl HDF5Memory {
                     .map(|(id, dist)| (id, 1.0 - dist))
                     .collect();
                 let kw_scores = bm25.search(query_text, self.cache.len());
-                hybrid::merge_vector_keyword(vec_scores, kw_scores, vector_weight, keyword_weight, k)
+                hybrid::merge_vector_keyword(
+                    vec_scores,
+                    kw_scores,
+                    vector_weight,
+                    keyword_weight,
+                    k,
+                )
             }
             _ => hybrid::hybrid_search(
                 query_embedding,