阶段4(上):LangGraph、Function Calling、MCP(SDK 2.x)、Agent 评测与运维、Agent 设计专题;run_examples 设置 RUN_EXAMPLES=1
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---
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id: ai.agent-design.index
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title: Agent 设计:规划、上下文工程与多 Agent
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title: Agent 设计
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type: index
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domain: ai
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stack: [agent-design]
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tags: []
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tags: [ReAct, 规划, 上下文工程, Skills, 多 Agent, A2A, Agentic RAG]
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week: [10, 11, 13]
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---
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# Agent 设计:规划、上下文工程与多 Agent
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# Agent 设计
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ReAct、Planning、Context Engineering、Skills、多 Agent 与 A2A、Agentic RAG。
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Agent 岗位面试必问的设计问题:什么时候用 Agent、ReAct 和规划、上下文工程、Skills、多 Agent 和 A2A、Agentic RAG。BOSS直聘 2026-10-23 的调研中,约 22 个岗位要求 Agent 开发经验,其中不少明确列出了这些概念。
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> 本专题建设中:课程、企业场景、面试题和示例代码会陆续补充。
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## 学习路线
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| 顺序 | 课程 | 级别 | 预计 |
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| --- | --- | --- | --- |
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| 1 | [Agent 推理模式:ReAct、Plan-and-Execute、反思和 Agentic RAG](01-react-planning.md) | 进阶 | 3 小时 |
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| 2 | [上下文工程、Skills、多 Agent 和 A2A](02-context-skills-multiagent.md) | 高级 | 3.5 小时 |
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## 企业场景
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- [运营报表 Agent:规划、只读 SQL 工具、结构化输出和任务进度](scenarios/report-agent.md)
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## 面试题
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- [Agent 设计面试题](interview.md)
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## 示例代码
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- [examples/agent-patterns](examples/agent-patterns/):Plan-and-Execute + 失败重新规划、Skills 渐进式加载(含两个 `SKILL.md` 示例)、上下文预算和摘要压缩(只用标准库,带测试)
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## 在 16 周计划中
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- [第 10 周](../../../plan/week10-agent-m1-tools-mcp.md)、[第 11 周](../../../plan/week11-agent-m2-langgraph.md)、[第 13 周](../../../plan/week13-agent-m4-eval-lowcode.md)
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## 官方资料
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概念发展很快,以官方文档为准:
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- Anthropic《Building effective agents》:https://www.anthropic.com/engineering/building-effective-agents
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- LangGraph 多 Agent:https://docs.langchain.com/oss/python/langchain/multi-agent
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- Agent Skills:https://docs.anthropic.com/en/docs/agents-and-tools/agent-skills/overview
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- A2A 协议:https://a2a-protocol.org/
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