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leann-search
Semantic search across codebase using LEANN vector index
Packaged view
This page reorganizes the original catalog entry around fit, installability, and workflow context first. The original raw source lives below.
Stars
3,611
Hot score
99
Updated
March 19, 2026
Overall rating
C5.0
Composite score
5.0
Best-practice grade
B81.2
Install command
npx @skill-hub/cli install parcadei-continuous-claude-v3-leann-search
Repository
parcadei/Continuous-Claude-v3
Skill path: .claude/skills/archive/leann-search
Semantic search across codebase using LEANN vector index
Open repositoryBest for
Primary workflow: Ship Full Stack.
Technical facets: Full Stack.
Target audience: everyone.
License: Unknown.
Original source
Catalog source: SkillHub Club.
Repository owner: parcadei.
This is still a mirrored public skill entry. Review the repository before installing into production workflows.
What it helps with
- Install leann-search into Claude Code, Codex CLI, Gemini CLI, or OpenCode workflows
- Review https://github.com/parcadei/Continuous-Claude-v3 before adding leann-search to shared team environments
- Use leann-search for development workflows
Works across
Claude CodeCodex CLIGemini CLIOpenCode
Favorites: 0.
Sub-skills: 0.
Aggregator: No.
Original source / Raw SKILL.md
--- name: leann-search description: Semantic search across codebase using LEANN vector index allowed-tools: [Bash, Read] --- # 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 ```bash # 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: ```bash 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" |