Julian lechnerandClaude Opus 5.5
14e6588d4e
Expose the local Qwen search as a skill with an explicit trigger for concept questions, the command for both shells, result handling, and its limits. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2.4 KiB
2.4 KiB
name, description
| name | description |
|---|---|
| semantic-search | Use when you must find where a behavior, concept, or rule lives in a repository and do not know its identifiers or exact strings, or when a first rg search returned nothing useful. Returns ranked code and documentation chunks from the local Qwen index. |
Semantic Search
Search the current Git repository by meaning with the locally installed Qwen3 embedding and reranking models.
When to use
- Concept questions: "where are expired trials blocked", "how is the cache invalidated", "which code retries failed uploads".
- Unfamiliar repositories where names and conventions are unknown.
- After an
rgsearch for guessed terms returned nothing relevant or too many unrelated files.
Use rg or direct reads instead for known file paths, symbol names, exact strings, and error messages.
Run
PowerShell:
python "$HOME/.my-ai-configuration/semantic-retrieval/server.py" search --root . --data-dir "$HOME/.my-ai-configuration/semantic-retrieval/data" --model-cache "$HOME/.my-ai-configuration/semantic-retrieval/model-cache" --query "<question in natural language>" --top-k 5
Bash:
python3 "$HOME/.my-ai-configuration/semantic-retrieval/server.py" search --root . --data-dir "$HOME/.my-ai-configuration/semantic-retrieval/data" --model-cache "$HOME/.my-ai-configuration/semantic-retrieval/model-cache" --query "<question in natural language>" --top-k 5
The output is a JSON list of {path, symbol, text, score}, best match first.
Use the results
- Phrase the query as a full question about behavior, not as a keyword list.
- Open the top hits and verify them against the current files before acting; the index can lag behind uncommitted edits by one refresh.
- Follow the verified hit with
rgfor its symbols to find callers and tests.
Cost and limits
- The first search in a repository builds its index, which can take minutes; later searches refresh only changed files.
- Outside a sandbox a background daemon keeps the models loaded, so warm searches take seconds. Inside the Codex sandbox every search loads the models again and takes about half a minute; batch related questions into one precise query.
- Only Git-tracked and unignored files up to 512 KB are indexed, by default at most 2000 files per repository.
- If the command fails or the setup is missing, continue with
rgand state the limitation briefly.