Find relevant code by describing what it does, even when identifiers use different words. The skill explains LEANN's meaning-based search, when to use exact text search instead, and how to rebuild the project's search index.
Semantic search across codebase using LEANN vector index
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
Use LEANN for meaning-based code search instead of grep.
class Foo, def bar, specific identifierserror.*handling, import.*from*.test.ts, src/**/*.py# Search the current project's index
leann search <index-name> "<query>" --top-k 5
# List available indexes
leann list
# Example
leann search rigg "how do providers handle streaming" --top-k 5
leann_search(index_name="rigg", query="your semantic query", top_k=5)
When codebase changes significantly:
cd /path/to/project
leann build <project-name> --docs src tests scripts \
--file-types '.ts,.py,.md,.json' \
--no-recompute --no-compact \
--embedding-mode sentence-transformers \
--embedding-model all-MiniLM-L6-v2
| Query Type | Tool | Example |
|---|---|---|
| Natural language | LEANN | "how does caching work" |
| Class/function name | Grep | "class CacheManager" |
| Pattern matching | Grep | error|warning |
| Find implementations | LEANN | "rate limiting logic" |
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