# Mixed query routing audit

Read-only implementation audit, 2026-10-13, source revision `5d9cfc4`.
These findings describe current behavior; they are not a retrieval-quality
measurement or an implemented ranking change.

## Current behavior

`HybridSearch::query_vector` selects Google's CodeRetrieval task only when
`SearchOptions::code_only` is true. All-files searches use the general task,
including natural-language queries asking for an implementation. The bounded
query-vector LRU distinguishes tasks, so vectors cannot be reused across them
accidentally. See `crates/searchi-service/src/lib.rs`.

The audio preference in `crates/searchi-service/src/routing.rs` recognizes words
such as speech, sound and music. Document and image cues veto that preference;
code cues currently do not. If the preferred audio search returns any qualifying
candidate, it becomes the exclusive semantic lane. Consequently a query such as
"code that detects speech" can exclude semantic code candidates in All files.
Lexical candidates still participate in hybrid fusion, and explicit Code scope
bypasses this audio preference. This is a risk to evaluate, not proof that every
such query fails.

## Cost of adding lanes

`crates/searchi-service/src/store.rs` retains one eligibility-cache entry.
Its key includes the generation, user filters, source type and code scope.
Changing a filter replaces the entry and scans/hashes matching passage metadata
again. Alternating general and code lanes would therefore perform repeated
eligibility work even when query vectors and the ANN graph are warm. The existing
empty-audio fallback can also alternate audio and general filters.

Incremental dirty-path updates apply when the cached filter matches and the
revision is still within the dirty-history floor. A replacement cache design
must preserve those freshness checks, generation invalidation, strict filtering
before candidate limits, and the total allocation budget.

## Next experiment

First complete the unchanged frozen mixed baseline described in
[MIXED-QUALITY.md](MIXED-QUALITY.md). Keep its labels and source bytes unchanged.
Then compare soft audio preference and task-specific rank fusion against that
baseline, retaining exact filename/symbol priority. Different task scores must
not be treated as calibrated probabilities or compared blindly.

Before introducing multiple lanes, measure a bounded multi-entry eligibility
cache against a shared validated snapshot with derived code/origin views.
Bound memory across all entries, rather than giving each the full chunk budget.
Reuse the existing worker and prepared ANN graph.

Report All-files and Code scope separately: top-1, recall@5, hard negatives and
no-answer behavior, plus query-vector cache misses, inference time, eligibility
scans/hash calls, memory and warm p95. Include mutation/deletion regressions.
The existing `semantic.eligibility` and
`semantic.eligibility_filtered_scan_and_hash` traces expose eligibility cost.
Use an independently reviewed held-out corpus for acceptance; the frozen
diagnostic alone must not become the optimization target.