代理模式

# 概述 — 智能体模式 — Veso Research 来源：https://veso.ai/research/agentic-patterns/ 研究 (https://veso.ai/research)智能体模式开始 所有前沿智能体系统中涌现出的通用架构。 ## 趋同 Claude Code, OpenAI Codex, Gemini CLI, LangGraph, CrewAI, Google ADK, Amazon Bedrock — 由不同公司、使用不同语言、在各自约束条件下构建。它们却汇聚到了相同的设计上。 并非因为相互抄袭，而是因为约束条件如同物理定律一般不变：有限的上下文窗口、需要协议的工具、不能依赖模型服从的安全要求、以及单个调用无法完成的复杂任务。任何持续构建的团队最终都会到达这里。 --- ## 你正在构建哪种系统？ 本指南中的模式普遍适用，但其*权重*取决于你在智能体生态系统中所处的具体接缝。请按照与你问题相匹配的顺序阅读。 | 如果你正在构建... | 你最关心... | 从...开始 | | --- | --- | --- | | **领域上下文基座**（一个MCP服务器，为任意智能体提供对某个领域——如代码库、屏幕、系统——的结构化访问） | 确定性提取、固定本体、用户项目中的行为契约 | `/tool-protocols`、`/instructions`、`/anti-patterns` | | **个人AI运行时**（一个由用户拥有的智能体，在后台运行，具有长期状态） | 内存架构、压缩驻留状态、钩子、调度器门控的后台工作 | `/memory`、`/enforcement`、`/multi-agent` | | **多智能体外壳**（一个协调他人智能体的编排器，具有聊天平台覆盖范围） | 适配器模式、隔离的子智能体工具注册表、设置架构、成本控制 | `/multi-agent`、`/enforcement`、`/cost-management` | 这些分类并非绝对——许多系统会模糊其间界限。但明确哪一个是你的*承重*关切，可以避免过度应用不适合你接缝的模式。 --- ## 8条基本原则 这些不是建议，而是每个生产级智能体系统的承重墙。违反它们，你将重新发现它们存在的原因。 | # | 原则 | 该做什么 | | --- | --- | --- | | 1 | **从持久化指令文件开始** | 在编写任何智能体配置之前先创建 `CLAUDE.md`、`AGENTS.md` 或 `GEMINI.md`。涵盖约定、技术栈、测试、git 和安全。保持在200行以内。 | | 2 | **在提示词之外执行安全** | 将样式偏好放在指令文件中。将 linting 放在钩子中。将破坏性命令拦截放在权限中。永远不要依赖模型记住安全规则。 | | 3 | **预算上下文窗口** | 预留10-15%用于指令，30-40%用于对话，20-30%用于工具结果。在使用率达到70%时压缩，80%时清除。将可缓存内容与可压缩内容分离。 | | 4 | **基于MCP构建工具** | 使用 `.mcp.json` 进行工具连接。每月下载量超过9700万次，覆盖所有主要平台。如果需要在系统间进行智能体间通信，添加 A2A——但先从 MCP 开始。 | | 5 | **通过共享状态协调** | 在系统内部，智能体读取和写入共享状态——而不是相互发送消息。在系统或组织之间，使用消息协议（A2A）。默认使用状态；仅在必要时才使用消息。 | | 6 | **在到达极限前分解任务** | 智能体在长时间会话后连贯性会下降。阈值随着每代模型而移动。不要去找到极限——保持在极限之下。将工作分解为在安全区域内完成的子任务。 | | 7 | **从第一天起追踪每个任务的成本** | 为每次会话设置令牌预算。将简单工作路由到廉价模型。缓存稳定提示。在预算达到50%、75%和90%时使用警报监控。成本管理是基础设施，而不是优化。 | | 8 | **以周为单位渐进增加复杂度** | 第1周：指令文件。第2周：钩子。第3周：MCP 工具。第4周：技能。第二个月+：子智能体。如果你的团队有分布式系统经验，可以更快——但在增加下一层之前仍要验证每一层。 | --- ## 架构 %3b%7d%23mermaid-0 .cluster rect%7bfill:white%3bstroke:%23f97316%3bstroke-width:1px%3b%7d%23mermaid-0 .cluster text%7bfill:%23f97316%3b%7d%23mermaid-0 .cluster 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