search-router

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

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "search-router" with this command: npx skills add parcadei/continuous-claude-v3/parcadei-continuous-claude-v3-search-router

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

Tool Output Size Best For

TLDR ~50-500 DEFAULT: Code symbols, call graphs, data flow

TLDR Semantic ~100-300 Conceptual queries (P6, embedding-based)

AST-grep ~50 tokens Function/class definitions, imports, decorators

Grep ~200-2000 LAST 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

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

discovery-interview

No summary provided by upstream source.

Repository SourceNeeds Review
General

math

No summary provided by upstream source.

Repository SourceNeeds Review
General

explore

No summary provided by upstream source.

Repository SourceNeeds Review
General

git-commits

No summary provided by upstream source.

Repository SourceNeeds Review