LLM代理设计模式

LLM代理设计模式是一个命名的、可重用的形状，用于解决LLM驱动软件中的重复问题。代理循环、工具的调用方式、内存的分页方式、如何将批评反馈回去——这些不是实现细节，而是有名称的承诺。给它们命名使工程师能够在特定的基础上进行比较、组合和拒绝。

本目录以克里斯托弗·亚历山大（1977年）和四人帮（1994年）的方式分解每个模式：意图、上下文、问题、力量、因此、解决方案、后果（好处 + 负担）、约束（模型不允许违反的严格禁止），以及相关[] — 与其他模式的类型边缘。约束槽是LLM时代的新增内容；它是模式在强大生成器存在下保持模式的方式。

Field-tested patterns to start with

• ReAct — Interleave a single thought, a single tool call, and a single observation per step so the agent reasons over fresh evidence.
• Tool Use — Let the LLM produce typed calls against an external toolkit instead of producing free-form text the surrounding system has to parse.
• Plan-and-Execute — Plan all the steps once with a strong model, then execute each step with a cheaper model under the plan.
• Reflection — Have the model review its own output and produce a revised version in one or more passes.
• Step Budget — Cap the number of tool calls or loop iterations the agent is allowed within a single request.
• Chain of Thought — Elicit multi-step reasoning by prompting the model to produce intermediate steps before its final answer.
• Augmented LLM — Build the foundational agent block as an LLM augmented with retrieval, tools, and memory that the model actively chooses to use, rather than a bare-model call.
• Agent-as-a-Judge — Evaluate an agent's full trajectory (steps, tool calls, intermediate states) by another agent rather than scoring only the final output.
• Subagent Isolation — Run subagents in isolated workspaces so their writes do not collide and parallelism is safe.

Recommended reading

• Reasoning — 20 patterns
• Planning & Control Flow — 45 patterns
• Tool Use & Environment — 51 patterns
• Verification & Reflection — 32 patterns

Or open the full contents for all 565 patterns in 14 books.

Related guides

• AI Agents Patterns — AI agents patterns: named, reusable shapes for building AI agents that reason, use tools, coordinate, and stay safe — single-agent loops an…
• AI Agents Patterns Catalog — The AI agents patterns catalog: a complete, GoF-formal pattern language for AI agents across reasoning, planning, tool use, retrieval, memo…
• Agentic Design Patterns — A GoF-formal catalog of agentic design patterns — named, reusable shapes for building autonomous AI agents: agent loops, tool use, planning…
• Agentic AI Design Patterns — Agentic AI design patterns for systems already in production — what to ship, what to observe, what to budget, what to gate. Augmented LLM,…
• AI Agent Design Patterns — How to build an AI agent: the named shapes you reach for during design and implementation — reasoning (ReAct, plan-and-execute, reflection)…
• Agent Design Patterns — Agent design patterns treat the agent loop as a software-engineering primitive: an observe→reason→act cycle wrapped in tools, memory, super…
• Agentic Patterns — A complete pattern language for agentic systems, organised in Alexander-style books across reasoning, planning, tool use, retrieval, verifi…
• Agentic AI Architecture — How to structure agentic AI: the architectural patterns that hold an LLM-powered system together. Supervisor, orchestrator-workers, augment…
• RAG Agent Patterns — Patterns for building retrieval-augmented generation agents: naive RAG, agentic RAG, hybrid search, cross-encoder reranking, contextual ret…
• Multi-Agent Patterns — Patterns for coordinating multiple LLM agents: supervisor, orchestrator-workers, handoff, debate, hierarchical agents, swarm, role assignme…
• AI Agent Safety Patterns — Safety patterns for LLM agents: step budget, kill switch, constitutional charter, approval queue, sandbox isolation, input/output guardrail…