mcpField
S
search-router

search-router

github.com/parcadeiDevelopment3.9k487 installsUpdated 39w ago
Repository

About search-router

A search-routing skill that selects a code search method based on the query, favoring TLDR for code exploration and using structural or text search for other needs. It is intended for developers locating implementations, identifiers, and code relationships while limiting unnecessary output.

Key features

  1. 01Routes queries by search type
  2. 02TLDR-based code exploration
  3. 03AST pattern search guidance
  4. 04Semantic search guidance
  5. 05Token-conscious search workflow

Use cases

  1. 01Finding a symbol or implementation
  2. 02Tracing call chains and data flow
  3. 03Locating functions or imports by structure
  4. 04Searching non-code text or regular expressions

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/parcadei/continuous-claude-v3 --skill search-router

After installing, type/search-routerin Claude Code to confirm it loaded.

Details

From the project README

Search Tool Router

Use the most token-efficient search tool for each query type.

When to Use

  • Searching for code patterns
  • Finding where something is implemented
  • Looking for specific identifiers
  • Understanding how code works

Decision Tree

Query Type?
├── CODE EXPLORATION (symbols, call chains, data flow)
│   → TLDR Search - 95% token savings
│   DEFAULT FOR ALL CODE SEARCH - use instead of Grep
│   Examples: "spawn_agent", "DataPoller", "redis usage"
│   Command: tldr search "query" .
│
├── STRUCTURAL (AST patterns)
│   → AST-grep (/ast-grep-find) - ~50 tokens output
│   Examples: "def foo", "class Bar", "import X", "@decorator"
│
├── SEMANTIC (conceptual questions)
│   → TLDR Semantic - 5-layer embeddings (P6)
│   Examples: "how does auth work", "find error handling patterns"
│   Command: tldr semantic search "query"
│
├── LITERAL (exact text, regex)
│   → Grep tool - LAST RESORT
│   Only when TLDR/AST-grep don't apply
│   Examples: error messages, config values, non-code text
│
└── FULL CONTEXT (need complete understanding)
    → Read tool - 1500+ tokens
    Last resort after finding the right file

Token Efficiency Comparison

ToolOutput SizeBest For
TLDR~50-500DEFAULT: Code symbols, call graphs, data flow
TLDR Semantic~100-300Conceptual queries (P6, embedding-based)
AST-grep~50 tokensFunction/class definitions, imports, decorators
Grep~200-2000LAST RESORT: Non-code text, regex
Read~1500+Full understanding after finding the file

Examples

# CODE EXPLORATION → TLDR (DEFAULT)
tldr search "spawn_agent" .
tldr search "redis" . --layer call_graph

# STRUCTURAL → AST-grep
/ast-grep-find "async def $FUNC($$$):" --lang python

# SEMANTIC → TLDR Semantic
tldr semantic search "how does authentication work"

# LITERAL → Grep (LAST RESORT - prefer TLDR)
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

Related Skills

  • /tldr-search - DEFAULT - Code exploration with 95% token savings
  • /ast-grep-find - Structural code search
  • /morph-search - Fast text search

Comments

Markdown supported