Choose a code search tool based on whether you need symbols, structural patterns, conceptual answers, or exact text. The rules guide agents toward relevant files before reading full contents, helping limit unnecessary search output.
中文简介正在准备中。当前显示英语简介。
Choose the right search tool for each query type
安装前可以查看交给 AI 代理的指令内容。
Use the most token-efficient search tool for each query type.
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
| 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 |
# 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
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
/tldr-search - DEFAULT - Code exploration with 95% token savings/ast-grep-find - Structural code search/morph-search - Fast text search还没有评价。欢迎分享你的使用感受。
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Coordinate background agents through saved files, keeping lengthy work transcripts out of the main conversation. It defines how to pass results between agents, monitor progress, and verify completed work with tests.
中文简介正在准备中。当前显示英语简介。
Delegate implementation, file reading, and testing to separate agents, then bring concise summaries back to the main conversation. The rules explain when delegation helps and when a small edit is better handled directly.
中文简介正在准备中。当前显示英语简介。
Organize implementation work across research, planning, validation, implementation, and review agents. Each stage passes files to the next, while implementation starts with failing tests and the main conversation coordinates the workflow.
中文简介正在准备中。当前显示英语简介。
Connect Agentica SDK agents to Claude Code CLI through a proxy, an intermediary server. Use setup and debugging guidance to address file permissions, streamed responses, result formatting, and agents reporting success without performing the requested operations.
中文简介正在准备中。当前显示英语简介。
Consult Agentica APIs when building workflows where multiple AI agents cooperate. This reference covers eleven coordination patterns, agent tracking, shared state, handoffs, and ways to combine results, with pointers to detailed API specifications.
中文简介正在准备中。当前显示英语简介。
Write clearer instructions for Agentica and REPL agents by specifying roles, file operations, and output formats. Includes templates for dividing research, coordinating specialists, reviewing solutions, and passing results between agents through files.
中文简介正在准备中。当前显示英语简介。