feat: add Google code retrieval across desktop CLI and MCP

docs/CODE-QUALITY.md

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+# Source-code relevance checkpoint
+
+Recorded 2026-10-12 using the actual verified Google EmbeddingGemma 2 Q8_0
+model, rebuilt native worker, shared hybrid service and MCP protocol. Windows
+VM, CPU only, one inference thread. No simulated provider or injected vectors.
+
+Google describes local code retrieval in its
+[launch blog](https://blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/).
+Its [model card](https://ai.google.dev/gemma/docs/embeddinggemma/model_card_2)
+specifies `task: code retrieval | query: {query}` for queries and
+`title: {filename} | text: {code}` for indexed source. searchi uses that pairing
+in Code scope. Google's published benchmark measures their full-precision
+checkpoint; it is not a searchi benchmark.
+
+## Frozen small regression
+
+[The evaluator](../tools/code-eval/evaluate.py) fixes the implementations,
+queries and expected files before inference. Eight short source files use
+generic filenames; a ninth ordinary document deliberately contains search
+terms. All nine files are indexed, so code filtering must exclude that document
+before ranking. The expected code excerpts are checked byte-for-byte through
+MCP `read_source`, including line locations. Fixture hashes and every returned
+rank are recorded in [raw CPU evidence](evidence/code-search-cpu.json).
+
+| Query intent | Source | Lexical rank | Hybrid rank |
+| --- | --- | --- | --- |
+| Streaming file SHA256 | Python | absent | 1 |
+| Lower bound in sorted numbers | C++ | absent | 1 |
+| Sum amounts by category | TypeScript | absent | 1 |
+| Retry requests with exponential backoff | Python | absent | 1 |
+| Release semaphore after async failure | C# | absent | 1 |
+| Escape unsafe HTML characters | PHP | absent | 1 |
+| Ten most expensive records | Python | absent | 1 |
+| File verification without full memory load, German | Python | absent | 1 |
+| Exact `refreshAccessToken` symbol | Rust | 1 | 1 |
+
+Top-1 success: **9/9 hybrid, 1/9 lexical**. Every expected hybrid source was
+verified and no ordinary document leaked into Code scope. Measured MCP
+roundtrips for these nine uncached code queries ranged from **63.88–228.21 ms**,
+median **110.76 ms**. Those timings exclude process/model startup and describe
+this tiny corpus only; they are not desktop first-use or large-project targets.
+
+## Defect discovered and fixed
+
+The first actual indexing attempt failed on TypeScript: Google's tokenizer
+normalized source characters, invalidating a detokenization-based byte-offset
+assumption. The worker now retains original UTF-8 source, checks the complete
+prefixed token budget, and splits normalized long inputs on original character
+boundaries. It returns exact original slices with bounded overlap and complete
+tail coverage. Short code that fits uses a direct fast path. A separate actual
+CPU regression covers the failing TypeScript plus roughly 38 KB of repeated
+code with German, Japanese and emoji. Fixtures were not edited to hide failure.
+
+Additional checks cover strict filtering before lexical/ANN candidate limits,
+named build files, overlapping routine context, schema upgrades, task-specific
+query caching, actual code/general vector separation and debug-vector parity.
+
+## Reproduce and limits
+
+Build the CLI and provision the pinned CPU worker/model as documented in
+[BUILDING.md](BUILDING.md) and [SEMANTIC.md](SEMANTIC.md), then run:
+
+```powershell
+$env:SEARCHI_FORCE_CPU = '1'
+python tools/code-eval/evaluate.py
+```
+
+The script uses the repository's generated `.searchi/code-eval` folder and
+default local runtime/model paths. It does not index private project folders.
+Outputs stay in that generated folder until deliberately reviewed and copied
+into documentation evidence.
+
+These are synthetic, short implementations with one intended answer per query.
+They do not prove general project accuracy, declaration-first ranking,
+call-graph understanding or reliable no-answer detection. Extraction is
+line-based, not an AST parser. Independent real repositories, difficult
+near-duplicates, more languages, native UI interaction, other operating systems
+and actual GPU execution remain open evaluation gates.