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MyAiConfiguration/shared/skills/research/semantic-search/SKILL.md
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Julian lechnerandClaude Opus 5.5 14e6588d4e feat(skills): add semantic-search skill
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>
2026-10-01 13:27:55 +02:00

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---
name: semantic-search
description: 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 `rg` search 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:
```powershell
python "$HOME/.my-ai-configuration/semantic-retrieval/server.py" search --root . --data-dir "$HOME/.my-ai-configuration/semantic-retrieval/data" --model-cache "$HOME/.my-ai-configuration/semantic-retrieval/model-cache" --query "<question in natural language>" --top-k 5
```
Bash:
```bash
python3 "$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
1. Phrase the query as a full question about behavior, not as a keyword list.
2. Open the top hits and verify them against the current files before acting; the index can lag behind uncommitted edits by one refresh.
3. Follow the verified hit with `rg` for 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 `rg` and state the limitation briefly.