search-hierarchy

# Search Tool Hierarchy Use the most token-efficient search tool for each query type. ## Decision Tree ``` Query Type? ├── STRUCTURAL (code patterns) │ → AST-grep (~50 tokens output) │ Examples: "def foo", "class Bar", "import X", "@decorator" │ ├── SEMANTIC (conceptual questions) │ → LEANN (~100 tokens if path-only) │ Examples: "how does auth work", "find error handling patterns" │ ├── LITERAL (exact identifiers) │ → Grep (variable output) │ Examples: "TemporalMemory", "check_evocation", regex patterns │ └── FULL CONTEXT (need complete understanding) → Read (1500+ tokens) Last resort after finding the right file ``` ## Token Efficiency Comparison | Tool | Output Size | Best For | |------|-------------|----------| | AST-grep | ~50 tokens | Function/class definitions, imports, decorators | | LEANN | ~100 tokens | Conceptual questions, architecture, patterns | | Grep | ~200-2000 | Exact identifiers, regex, file paths | | Read | ~1500+ | Full understanding after finding the file | ## Hook Enforcement The `grep-to-leann.sh` hook automatically: 1. Detects query type (structural/semantic/literal) 2. Blocks and suggests AST-grep for structural queries 3. Blocks and suggests LEANN for semantic queries 4. Allows literal patterns through to Grep ## DO - Start with AST-grep for code structure questions - Use LEANN for "how does X work" questions - Use Grep only for exact identifier matches - Read files only after finding them via search ## DON'T - Use Grep for conceptual questions (returns nothing) - Read files before knowing which ones are relevant - Use Read when AST-grep would give file:line - Ignore hook suggestions ## Examples ```bash # STRUCTURAL → AST-grep ast-grep --pattern "async def $FUNC($$$):" --lang python # SEMANTIC → LEANN leann search opc-dev "how does authentication work" --top-k 3 # LITERAL → Grep Grep pattern="check_evocation" path=opc/scripts # FULL CONTEXT → Read (after finding file) Read file_path=opc/scripts/z3_erotetic.py ``` ## Optimal Flow ``` 1. AST-grep: "Find async functions" → 3 file:line matches 2. Read: Top match only → Full understanding 3. Skip: 4 irrelevant files → 6000 tokens saved ```