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leann-search

Semantic search across codebase using LEANN vector index

不碰外部(只输出文字)无严重或高危命中parcadei/Continuous-Claude-v3

它会碰到什么

扫了多少1 个文本文件,2 KB
它会碰到什么不碰外部(只输出文字)
命中总数0 处
命中统计严重 0 · 高 0 · 中 0 · 低 0

这一栏是扫描器报的事实,不是结论。命中多不等于有毒(安全工具、规则库、示例脚本本来就会包含危险写法),命中少也不等于干净。它和你手上的凭据、文件、网络有什么关系,需要你自己看。

技能内容

LEANN Semantic Search

Use LEANN for meaning-based code search instead of grep.

When to Use

  • Conceptual queries: "how does authentication work", "where are errors handled"
  • Understanding patterns: "streaming implementation", "provider architecture"
  • Finding related code: code that's semantically similar but uses different terms

When NOT to Use

  • Exact matches: Use Grep for class Foo, def bar, specific identifiers
  • Regex patterns: Use Grep for error.handling, import.from
  • File paths: Use Glob for .test.ts, src/*/*.py

Commands

# 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

MCP Tool (in Claude Code)

leann_search(index_name="rigg", query="your semantic query", top_k=5)

Rebuilding the Index

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

How It Works

  1. LEANN uses sentence embeddings to understand meaning
  2. Searches find conceptually similar code, not just text matches
  3. Results ranked by semantic similarity score (0-1)

Grep vs LEANN Decision

| 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" |

想直接用这个技能?

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