← Back to list

search-router
by parcadei
Context management for Claude Code. Hooks maintain state via ledgers and handoffs. MCP execution without context pollution. Agent orchestration with isolated context windows.
⭐ 3,352🍴 252📅 Jan 23, 2026
SKILL.md
name: search-router description: Choose the right search tool for each query type user-invocable: false
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
Score
Total Score
95/100
Based on repository quality metrics
✓SKILL.md
SKILL.mdファイルが含まれている
+20
✓LICENSE
ライセンスが設定されている
+10
✓説明文
100文字以上の説明がある
+10
✓人気
GitHub Stars 1000以上
+15
✓最近の活動
1ヶ月以内に更新
+10
✓フォーク
10回以上フォークされている
+5
✓Issue管理
オープンIssueが50未満
+5
✓言語
プログラミング言語が設定されている
+5
✓タグ
1つ以上のタグが設定されている
+5
Reviews
💬
Reviews coming soon

