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---
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title: "AI拟人化谬误"
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type: concept
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tags: []
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---
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## Definition
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将 LLM 拟人化（赋予名字、情感、恐惧、动机）是一种设计谬误。LLM 没有生物体的局限性——不会死亡、饥饿或害怕；它们在推理时只存在几秒钟来生成响应，缺乏真正的同理心或情感。
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## Why It's Wrong
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- LLM 天生的不可靠性（幻觉、逻辑谬误、上下文漂移）与人类不同
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- 对 LLM 的"威胁"或"激励"只是利用训练数据中高风险→高质量输出的相关性
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- 拟人化会掩盖 LLM 真正的问题：将其视为可靠组件而非需要工程保障的系统
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## The Correct Approach
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- [[Alex Ewerlöf]] 主张：将 LLM 视为分布式系统中不可靠的组件
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- 构建系统时：约束（Constrained）、验证（Verified）、修剪（Pruned）、挑战（Challenged）
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- 不需要"关心"的 AI，需要的是经过工程保障的 AI
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## Related Concepts
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- [[泰勒主义软件工厂]]
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- [[LLM不可靠性]]
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- [[多Agent可靠性模式]]
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## Sources
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- [[The-Picture-They-Paint-of-You.md]]
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- [[Multi-Agent-System-Reliability.md]]
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---
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id: ai-voice
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title: "AI配音"
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type: concept
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tags: [TTS, voice, audio]
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sources:
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- "[[AI配音与声音克隆工具合集]]"
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last_updated: 2025-03-06
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---
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## Definition
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AI配音是文本转语音（TTS）技术，将文字内容转化为自然语音。
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## Key Technologies
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- **TTS**：Text-to-Speech，文字转语音
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- **声音克隆**：用少量样本重建个人声音
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## Popular Tools
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| 平台 | 特点 | 价格 |
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|------|------|------|
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| ElevenLabs | 国际顶流，30+语言，情感变化 | 付费较贵 |
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| 海螺AI | 小白友好，30秒克隆，中文好 | 免费 |
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| F5-TTS | 开源免费，2秒克隆，技术流 | 免费 |
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| TTSMaker | 每周3万字，50+语言，300+音色 | 免费限额 |
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| 剪映 | 抖音官方，短视频首选 | 部分VIP |
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| AnyVoice | 3秒克隆，中英日韩 | 免费无限 |
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## Connections
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- [[二创视频]] ← uses ← [[AI配音]]
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- [[内容创作]] ← uses ← [[AI配音]]
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---
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id: agent
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title: "Agent"
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type: concept
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tags: [AI, autonomous, tool-use]
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sources:
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- "[[LLM Terms Framework]]"
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last_updated: 2025-12-20
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---
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## Definition
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Agent（智能体）是LLM+MCP的组合，LLM负责给出步骤，MCP负责实际执行。
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## How It Works
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1. LLM理解用户意图
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2. LLM规划执行步骤
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3. MCP调用外部工具执行
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4. 结果反馈给LLM
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5. LLM继续下一步或返回结果
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## Key Capabilities
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- 自主决策
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- 工具调用
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- 任务分解
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- 迭代优化
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## vs Vanilla LLM
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| 维度 | Vanilla LLM | Agent |
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|------|-------------|-------|
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| 能力 | 仅生成文本 | 执行实际操作 |
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| 工具调用 | 无 | 有 |
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| 自主性 | 低 | 高 |
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| 幻觉风险 | 高 | 低（可验证） |
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## Connections
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- [[Agent]] ← combines ← [[LLM]] + [[MCP]]
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- [[Agent]] ← extends ← [[LLM]]
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- [[Agent]] ← uses ← [[工具调用]]
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---
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id: agent-skill-design-pattern
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title: "AgentSkill设计模式"
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type: concept
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tags: [Agent, Skill, 设计模式]
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sources: [Google-5个Agent-Skill设计模式.md]
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last_updated: 2026-03-19
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---
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# AgentSkill设计模式
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将领域知识或工作流有效封装进Skill的五种设计模式，Google与Anthropic经验总结。
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## 五种模式
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| 模式 | 核心机制 | 适用场景 |
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|------|----------|----------|
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| [[ToolWrapper]] | 按需动态加载知识文档 | 编码规范、框架最佳实践 |
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| [[Generator]] | 模板+变量填充生成一致输出 | API文档、报告生成 |
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| [[Reviewer]] | 检查标准与执行逻辑分离 | 代码审查、安全审计 |
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| [[Inversion]] | 先问再做，延迟执行 | 需求分析、项目规划 |
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| [[Pipeline]] | 硬性检查点强制顺序执行 | 复杂流水线、质量控制 |
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## 核心问题
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SKILL.md格式标准化后（已被30+主流工具支持），同等格式的skill执行效果天差地别。差距在于**内容设计**，而非格式。
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## 模式组合
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五种模式并非互斥，可以组合使用：
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- Pipeline末尾可加Reviewer进行double-check
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- Generator开始可用Inversion收集必要变量
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- Reviewer可嵌入Pipeline作为质量关卡
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## 理论基础
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- [[Anthropic]]经验：最好的Skill是「工具箱」，不是大prompt；三条铁律：只写Agent不知道的、重点写踩坑清单、给工具不给指令
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- [[Google]]ADK：SkillToolset和渐进式披露机制，agent只在运行时需要时才消耗上下文token加载特定模式
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## 与AgenticAI关系
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[[AgenticAI]]的发展使得Skill设计从"写好提示词"转向"设计好工作流结构"。五种模式将[[AgenticAI]]的能力通过结构化Skill封装为可复用模块。
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## 相关概念
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- [[AgentSkill]]：Skill的实例化
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- [[AgenticAI]]：Agent具备自主行动能力
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- [[工作流自动化]]：Pipeline模式的技术基础
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---
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id: agentic-ai
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title: "Agentic AI"
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type: concept
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tags: [AI, agent, autonomous, proactive]
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sources:
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- "[[Designing for Agentic AI]]"
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last_updated: 2025-03-02
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---
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## Definition
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Agentic AI是能够自主行动和决策的AI系统，能够预判用户需求并主动执行任务。
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## Key Characteristics
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- **主动预判**：不需要用户明确指令，主动分析并行动
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- **实时反馈**：持续向用户展示决策过程
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- **用户控制**：确保用户对AI行为有最终决定权
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- **行动执行**：不仅生成内容，而是执行具体操作
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## Five Design Principles
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1. **透明性**：让用户理解AI的决策过程
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2. **控制权**：用户始终保持对AI行为的最终决定权
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3. **个性化**：AI适应用户的偏好和习惯
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4. **对话**：通过自然语言进行持续交互
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5. **预判**：AI主动识别并满足用户潜在需求
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## vs GenAI
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| 维度 | GenAI | Agentic AI |
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|------|-------|------------|
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| 核心能力 | 内容生成 | 行动执行 |
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| 交互模式 | 被动响应 | 主动预判 |
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| 反馈机制 | 单次响应 | 实时反馈 |
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## Connections
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- [[Agentic AI]] ← extends ← [[GenAI]]
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- [[AI产品设计]] ← uses ← [[Agentic AI设计原则]]
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---
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title: "Agent模式"
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type: concept
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tags: [interaction-mode, ai-agent, cursor]
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last_updated: 2026-04-14
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---
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## Aliases
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- Agent mode
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- 代理模式
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## Summary
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Agent 模式是 [[Cursor]] 中 Composer 模块的一种交互状态。与需要用户手动复制执行命令的 Normal 模式不同，Agent 模式能够让 AI 模型自动运行内置的工具命令并处理返回结果，极大地提升了自动化任务的执行效率。配合 `enable yolo mode` 可以跳过二次确认（但具有一定风险）。
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## Key Connections
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- [[Agent模式]] → enables → [[SequentialThinking]]
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- [[Agent模式]] 存在于 [[Cursor]] 的 Composer 中
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---
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id: claude-skills
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title: "Claude Skills"
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type: concept
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tags: [Anthropic, Claude, skill, SOP]
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sources:
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- "[[Claude Skills最值得研究的AI范式]]"
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last_updated: 2026-01-05
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---
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## Definition
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Claude Skills是Anthropic官方发布的AI技能指南，本质是写给Claude的"说明书"和"SOP"。
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## What It Contains
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- Prompt结构定义
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- 参数含义说明
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- 容错策略
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- 使用示例
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## Official Skills Categories
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- 办公自动化四大件（Word/PDF/PPT/Excel）
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- 开发者工具箱
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- 创意类Skill
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## Awesome Claude Skills
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三大社区仓库：
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- ComposioHQ
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- VoltAgent
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- BehiSecc
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## Skills聚合站
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- skillsmp.com
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- aitmpl.com/skills
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- claudemarketplaces.com
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## Significance
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Skills的爆发标志着从**提示词工程**到**流程工程**的关键转变：
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- 将经验沉淀为SOP
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- 交给AI稳定执行
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- 实现可复用的工作流
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## Connection to Vibe Coding
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Vibe Coding的尽头也是Skills，通过AI编程方式构建的流程最终需要Skills来标准化和复用。
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## Connections
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- [[提示词工程]] ← evolves_to ← [[流程工程]]
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- [[Claude Skills]] ← implements ← [[SOP标准化]]
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- [[Vibe Coding]] ← uses ← [[Claude Skills]]
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---
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id: embedding
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title: "Embedding"
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type: concept
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tags: [LLM, vector, representation]
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sources:
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- "[[RAG从入门到精通系列1：基础RAG]]"
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- "[[LLM Terms Framework]]"
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last_updated: 2025-12-18
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---
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## Definition
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Embedding（向量化）是将文本转换为数值向量的技术，使计算机能够计算词与词之间的距离和语义关系。
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## Mechanism
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- 将文本映射到高维向量空间
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- 语义相似的文本在向量空间中距离更近
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- 支持相似度搜索和聚类分析
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## Use Cases
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- RAG系统的文档索引
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- 语义搜索
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- 文本相似度比较
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- 推荐系统
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## Connections
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- [[LLM]] ← uses ← [[Embedding]]
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- [[RAG]] ← uses ← [[Embedding]]
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- [[向量数据库]] ← stores ← [[Embedding]]
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---
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id: genai
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title: "GenAI"
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type: concept
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tags: [AI, generation, content-creation]
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sources:
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- "[[Designing for Agentic AI]]"
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last_updated: 2025-03-02
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---
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## Definition
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GenAI（生成式AI）擅长创作内容，如文本、图像、代码、音乐等。
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## Key Characteristics
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- 内容生成能力强
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- 被动响应用户请求
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- 适合创意类任务
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## vs Agentic AI
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| 维度 | GenAI | Agentic AI |
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|------|-------|------------|
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| 核心能力 | 内容生成 | 行动执行 |
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| 交互模式 | 被动响应 | 主动预判 |
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| 代表任务 | 写作、绘画 | 自动化工作流 |
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## Connections
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- [[Agentic AI]] ← evolves_from ← [[GenAI]]
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- [[AI产品设计]] ← uses ← [[GenAI]]
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@@ -1,48 +0,0 @@
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---
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id: generator
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title: "Generator"
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type: concept
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tags: [Agent, Skill, 设计模式]
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sources: []
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last_updated: 2026-03-19
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---
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# Generator
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通过模板和变量填充流程，从用户需求生成结构化、一致性输出的Skill设计模式。
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## 定义
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Generator模式利用预定义的输出模板和样式指南，由Agent扮演项目经理角色，通过"收集缺失变量→填充模板→输出结果"的流程，保证每次运行生成格式完全一致的文档或代码。
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## 机制
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- assets/目录存放输出模板
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- references/目录存放样式指南
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- SKILL.md作为协调器，指导Agent加载模板、读取指南、收集变量、填充内容
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- 变量未齐全时，Agent主动向用户询问
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## 适用场景
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||||
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- 统一API文档生成
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- 标准化commit信息格式
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- 项目脚手架初始化
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- 报告/简报批量生成
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## 优点
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- 输出格式完全一致可预期
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- 模板与内容分离，便于更新样式
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- 变量收集机制确保信息完整
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## 缺点
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- 模板维护成本较高
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- 变量收集可能增加交互轮次
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- 不适合高度创造性任务
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## 关系
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- 上位概念：[[AgentSkill设计模式]]
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- 可组合：[[Inversion]]（用Inversion收集变量）
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- 可组合：[[Reviewer]]（用Reviewer检查输出）
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@@ -1,47 +0,0 @@
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---
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id: inversion
|
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title: "Inversion"
|
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type: concept
|
||||
tags: [Agent, Skill, 设计模式]
|
||||
sources: []
|
||||
last_updated: 2026-03-19
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---
|
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# Inversion
|
||||
|
||||
将Agent工作流从"先做后问"反转为"先问再做"的Skill设计模式。Agent变为面试官，通过阶段性提问收集必要信息后才会开始执行。
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|
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## 定义
|
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|
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Inversion模式通过硬性门控指令（gate）控制工作流：明确规定"不到所有阶段完成就不开始构建"。Agent逐阶段提问，等待用户回答，确认后才进入下一阶段，最终才执行核心任务。
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## 机制
|
||||
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- 硬性门控指令：不到所有阶段完成就不开始构建
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- 阶段化提问：Agent按阶段逐一提问
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||||
- 等待确认：每个阶段需用户明确回答后才进入下一阶段
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- 延迟执行：收集完所有必要信息后才执行实际操作
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## 适用场景
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|
||||
- 项目规划（收集需求、约束、优先级）
|
||||
- 需求分析（功能范围、技术栈、时间线）
|
||||
- 决策咨询（收集选项、偏好、限制条件）
|
||||
- 内容创作（主题、受众、风格偏好）
|
||||
|
||||
## 优点
|
||||
|
||||
- 确保执行前信息完整
|
||||
- 用户参与度高，减少返工
|
||||
- 避免Agent盲目猜测导致浪费
|
||||
|
||||
## 缺点
|
||||
|
||||
- 初始交互轮次多，用户可能不耐烦
|
||||
- 问题设计需要精心规划
|
||||
- 不适合紧急/简单任务
|
||||
|
||||
## 关系
|
||||
|
||||
- 上位概念：[[AgentSkill设计模式]]
|
||||
- 可组合：[[Generator]]（用Inversion收集Generator所需的变量）
|
||||
@@ -1,41 +0,0 @@
|
||||
---
|
||||
id: llm
|
||||
title: "LLM"
|
||||
type: concept
|
||||
tags: [AI, language-model, foundation-model]
|
||||
sources:
|
||||
- "[[LLM Terms Framework]]"
|
||||
last_updated: 2025-12-20
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
LLM（Large Language Model，大语言模型）是参数规模≥1B的深度学习模型，能够理解和生成人类语言。
|
||||
|
||||
## Core Properties
|
||||
|
||||
- **参数规模**：通常≥10亿参数
|
||||
- **语言理解**：能够理解复杂语义
|
||||
- **文本生成**：能够生成连贯、合法的文本
|
||||
- **上下文学习**：能从少量示例中学习
|
||||
|
||||
## Key Metrics
|
||||
|
||||
- **Token**：基本输入单元
|
||||
- 1英文字符 ≈ 0.3 token
|
||||
- 1中文字符 ≈ 0.6 token
|
||||
- **Context Window**：模型能接受的上下文长度
|
||||
|
||||
## Related Concepts
|
||||
|
||||
- [[Token]]：LLM的基本输入单元
|
||||
- [[MCP]]：LLM与外部工具的连接协议
|
||||
- [[Agent]]：LLM+MCP的智能体
|
||||
- [[RAG]]：扩展LLM能力的技术
|
||||
- [[Embedding]]：LLM理解文本的基础
|
||||
|
||||
## Connections
|
||||
- [[LLM]] ← uses ← [[Token]]
|
||||
- [[LLM]] ← uses ← [[MCP]]
|
||||
- [[Agent]] ← combines ← [[LLM]] + [[MCP]]
|
||||
- [[RAG]] ← extends ← [[LLM]]
|
||||
@@ -1,43 +0,0 @@
|
||||
---
|
||||
id: mcp
|
||||
title: "MCP"
|
||||
type: concept
|
||||
tags: [AI, protocol, tool-integration]
|
||||
sources:
|
||||
- "[[LLM Terms Framework]]"
|
||||
last_updated: 2025-12-20
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
MCP（Model Context Protocol，模型上下文协议）是一种标准化接口，用于连接大模型与外部数据和工具。
|
||||
|
||||
## Purpose
|
||||
|
||||
解决LLM无法访问实时数据和外部工具的问题：
|
||||
- LLM给出执行步骤
|
||||
- 实际执行需要配合MCP
|
||||
- 实现智能体（Agent）功能
|
||||
|
||||
## Architecture
|
||||
|
||||
- **Client**：运行在AI应用端
|
||||
- **Server**：运行在外部服务或本地
|
||||
|
||||
## Use Cases
|
||||
|
||||
- 文件系统访问
|
||||
- API调用
|
||||
- 数据库查询
|
||||
- 代码执行
|
||||
|
||||
## Connection to Agent
|
||||
|
||||
Agent = LLM + MCP
|
||||
- LLM负责理解和规划
|
||||
- MCP负责执行具体操作
|
||||
|
||||
## Connections
|
||||
- [[LLM]] ← uses ← [[MCP]]
|
||||
- [[Agent]] ← combines ← [[LLM]] + [[MCP]]
|
||||
- [[MCP]] ← enables ← [[工具调用]]
|
||||
@@ -1,61 +0,0 @@
|
||||
---
|
||||
id: pipeline
|
||||
title: "Pipeline"
|
||||
type: concept
|
||||
tags: [Agent, Skill, 设计模式]
|
||||
sources: []
|
||||
last_updated: 2026-03-19
|
||||
---
|
||||
|
||||
# Pipeline
|
||||
|
||||
在复杂任务中设置硬性检查点，强制Agent按严格顺序执行工作流的Skill设计模式。
|
||||
|
||||
## 定义
|
||||
|
||||
Pipeline模式通过实现明确的门控条件，确保Agent无法跳过步骤或忽略指令。每个关键节点设置检查点，用户必须在进入下一步之前确认，否则流程不会继续。
|
||||
|
||||
## 机制
|
||||
|
||||
- 工作流步骤明确定义在SKILL.md中
|
||||
- 每步有明确的进入前置条件
|
||||
- 门控条件未满足时阻止进入下一步
|
||||
- 文档流水线示例：解析清点→生成文档字符串→组装文档→质量检查
|
||||
|
||||
## 适用场景
|
||||
|
||||
- 复杂多步骤任务（文档生成流水线）
|
||||
- 需要严格质量控制的流程
|
||||
- 合规/审计要求不能跳过的步骤
|
||||
- 多人协作中需要明确交接点
|
||||
|
||||
## 优点
|
||||
|
||||
- 步骤不会被跳过
|
||||
- 质量控制点明确
|
||||
- 流程可追溯可审计
|
||||
- 减少因跳过步骤导致的错误
|
||||
|
||||
## 缺点
|
||||
|
||||
- 灵活性低，急救场景不适用
|
||||
- 用户可能觉得检查点过多
|
||||
- 流程僵化，难以适应特殊情况
|
||||
|
||||
## 与Inversion对比
|
||||
|
||||
| 维度 | Pipeline | Inversion |
|
||||
|------|----------|-----------|
|
||||
| 方向 | 强制顺序执行 | 先问再做 |
|
||||
| 控制点 | 技术门控（条件判断） | 问答门控（收集信息） |
|
||||
| 适用场景 | 复杂技术流程 | 需求分析决策 |
|
||||
|
||||
## 关系
|
||||
|
||||
- 上位概念：[[AgentSkill设计模式]]
|
||||
- 可组合：[[Reviewer]]（Pipeline末尾加Reviewer步骤）
|
||||
- 示例应用：[[文档流水线]]
|
||||
|
||||
## 相关实体
|
||||
|
||||
- [[Google]]：发布Pipeline模式的云服务提供商
|
||||
@@ -1,39 +0,0 @@
|
||||
---
|
||||
id: prompt-ability
|
||||
title: "Prompt能力"
|
||||
type: concept
|
||||
tags: [prompt-engineering, communication]
|
||||
sources:
|
||||
- "[[如何写出完美的Prompt]]"
|
||||
last_updated: 2025-12-02
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
Prompt能力是清晰界定需求+结构化思维表达的能力，本质是需求拆解+结构化表达能力。
|
||||
|
||||
## Core Elements
|
||||
|
||||
人与AI的协作协议，定义：
|
||||
- **做什么**：明确任务目标
|
||||
- **为什么**：任务背景和目的
|
||||
- **给谁**：目标受众
|
||||
- **怎么做**：执行方式和约束
|
||||
- **做到什么标准**：质量要求和验收标准
|
||||
|
||||
## Four Key Elements
|
||||
|
||||
1. **角色**：AI扮演的身份
|
||||
2. **受众对齐**：明确目标用户
|
||||
3. **场景对齐**：使用环境上下文
|
||||
4. **目标对齐**：预期成果定义
|
||||
|
||||
## Common Mistakes
|
||||
|
||||
- 越复杂越专业
|
||||
- 说清做什么就行
|
||||
- 一键生成即终点
|
||||
|
||||
## Connections
|
||||
- [[AI协作]] ← requires ← [[Prompt能力]]
|
||||
- [[结构化思维]] ← enables ← [[Prompt能力]]
|
||||
@@ -1,41 +0,0 @@
|
||||
---
|
||||
id: rag
|
||||
title: "RAG"
|
||||
type: concept
|
||||
tags: [LLM, retrieval, augmentation]
|
||||
sources:
|
||||
- "[[RAG从入门到精通系列1：基础RAG]]"
|
||||
- "[[LLM Terms Framework]]"
|
||||
last_updated: 2025-12-18
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
RAG（Retrieval Augmented Generation，检索增强生成）是一种结合检索系统和LLM生成的技术，解决LLM缺乏最新和私有数据的问题。
|
||||
|
||||
## Three-Step Process
|
||||
|
||||
1. **索引（Indexing）**：将文档切分并转换为Embedding向量存入向量数据库
|
||||
2. **检索（Retrieval）**：根据问题语义向量检索相关文档块
|
||||
3. **生成（Generation）**：将问题和相关文档输入LLM生成答案
|
||||
|
||||
## Key Components
|
||||
|
||||
- **Embedding**：将文本转换为数值向量
|
||||
- **向量数据库**：存储和检索向量表示（如Qdrant）
|
||||
- **文档切分**：将长文档分割成符合Embedding窗口的块
|
||||
- **Context Window**：模型能接受的上下文长度限制（512-8192 token）
|
||||
|
||||
## Why It Matters
|
||||
|
||||
解决LLM的幻觉问题，让模型能够：
|
||||
- 访问最新信息
|
||||
- 利用私有数据
|
||||
- 提供可溯源的回答
|
||||
|
||||
## Connections
|
||||
- [[LLM]] ← uses ← [[RAG]]
|
||||
- [[RAG]] ← includes ← [[索引]]
|
||||
- [[RAG]] ← includes ← [[检索]]
|
||||
- [[RAG]] ← includes ← [[生成]]
|
||||
- [[RAG]] ← extends ← [[LLM]]
|
||||
@@ -1,52 +0,0 @@
|
||||
---
|
||||
id: reviewer
|
||||
title: "Reviewer"
|
||||
type: concept
|
||||
tags: [Agent, Skill, 设计模式]
|
||||
sources: []
|
||||
last_updated: 2026-03-19
|
||||
---
|
||||
|
||||
# Reviewer
|
||||
|
||||
将"检查什么"（审查标准）与"怎么检查"（执行逻辑）完全分离的Skill设计模式。
|
||||
|
||||
## 定义
|
||||
|
||||
Reviewer模式将审查规则与执行机制解耦：审查标准存放于references/review-checklist.md，可替换为Python风格检查、安全审计、数据质量检查等；执行逻辑保持静态，Agent动态加载对应审查标准并输出结构化结果。
|
||||
|
||||
## 机制
|
||||
|
||||
- references/目录存放可替换的审查清单
|
||||
- SKILL.md定义静态审查指令
|
||||
- Agent动态加载特定审查标准
|
||||
- 输出按严重程度分组的结构化结果
|
||||
|
||||
## 适用场景
|
||||
|
||||
- 代码审查（Python风格、PEP8等）
|
||||
- 安全审计（OWASP Top 10等）
|
||||
- 文档质量检查
|
||||
- 数据质量验证
|
||||
|
||||
## 优点
|
||||
|
||||
- 一套skill基础设施，换清单即换专项
|
||||
- 审查标准独立维护，便于更新
|
||||
- 结构化输出便于后续处理
|
||||
|
||||
## 缺点
|
||||
|
||||
- 清单设计需要领域专业知识
|
||||
- 多标准并存时可能冲突
|
||||
- 动态加载机制增加复杂度
|
||||
|
||||
## 关系
|
||||
|
||||
- 上位概念：[[AgentSkill设计模式]]
|
||||
- 可组合：[[Pipeline]]（Pipeline末尾加Reviewer double-check）
|
||||
- 审查清单类型：[[代码审查]]、[[安全审计]]
|
||||
|
||||
## 相关实体
|
||||
|
||||
- [[Anthropic]]：Reviewer模式被用于Claude Code代码审查Skill
|
||||
@@ -1,16 +0,0 @@
|
||||
---
|
||||
title: "SSE"
|
||||
type: concept
|
||||
tags: [protocol, integration]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
## Aliases
|
||||
- Server-Sent Events
|
||||
- SSE连接
|
||||
|
||||
## Summary
|
||||
SSE (Server-Sent Events) 是一种服务器向客户端单向推送实时事件的技术。在 [[MCP]] 的生态中，SSE 是除命令行 (Command) 之外的另一种服务端接入方式，允许客户端实时监听服务端发出的数据和状态更新。
|
||||
|
||||
## Key Connections
|
||||
- [[SSE]] 是接入 [[MCP]] 的两种主要方式之一
|
||||
@@ -1,18 +0,0 @@
|
||||
---
|
||||
title: "SequentialThinking"
|
||||
type: concept
|
||||
tags: [reasoning, ai-capability]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
## Aliases
|
||||
- 序列化思考
|
||||
- Sequential Thinking
|
||||
- 步骤化推理
|
||||
|
||||
## Summary
|
||||
Sequential Thinking 是一种优化大语言模型（LLM）逻辑推理过程的机制或工具。它通过将复杂的任务分步拆解，并允许与外部服务（例如通过 [[MCP]] 集成的新闻源）互相调用，从而显著提升 AI 在面对复杂环境时的思考深度和响应准确率。
|
||||
|
||||
## Key Connections
|
||||
- [[SequentialThinking]] ← depends_on ← [[Agent模式]]
|
||||
- [[SequentialThinking]] 配合 [[MCP]] 使用提升能力
|
||||
@@ -1,30 +0,0 @@
|
||||
---
|
||||
id: source-grounding
|
||||
title: "Source-Grounding"
|
||||
type: concept
|
||||
tags: [NotebookLM, accuracy, grounding]
|
||||
sources:
|
||||
- "[[7 ways I use NotebookLM to make my life easier]]"
|
||||
last_updated: 2025-11-23
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
Source-Grounding是NotebookLM的核心机制，限制知识库仅包含用户上传的文档，确保AI回答准确且可溯源。
|
||||
|
||||
## Mechanism
|
||||
|
||||
- 用户上传文档后，NotebookLM只在这个文档范围内回答
|
||||
- 避免AI幻觉，确保回答有据可查
|
||||
- 每个回答都附带源文档引用
|
||||
|
||||
## Why It Matters
|
||||
|
||||
解决通用LLM的幻觉问题，特别适用于：
|
||||
- 法律文档审查
|
||||
- 学术研究
|
||||
- 精确信息查询
|
||||
|
||||
## Connections
|
||||
- [[NotebookLM]] ← uses ← [[Source-Grounding]]
|
||||
- [[AI准确性]] ← requires ← [[Source-Grounding]]
|
||||
@@ -1,37 +0,0 @@
|
||||
---
|
||||
id: token
|
||||
title: "Token"
|
||||
type: concept
|
||||
tags: [LLM, tokenization, input-unit]
|
||||
sources:
|
||||
- "[[LLM Terms Framework]]"
|
||||
last_updated: 2025-12-20
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
Token是大模型的基本输入单元，是文本处理的最小单位。
|
||||
|
||||
## Tokenization Rules
|
||||
|
||||
- 1英文字符 ≈ 0.3 token
|
||||
- 1中文字符 ≈ 0.6 token
|
||||
- 标点符号和空格也占用token
|
||||
|
||||
## Why It Matters
|
||||
|
||||
- 影响API调用成本
|
||||
- 决定上下文长度限制
|
||||
- 影响生成速度
|
||||
|
||||
## Context Window
|
||||
|
||||
模型能接受的token数量限制：
|
||||
- 较短的模型：4K-8K tokens
|
||||
- 中等模型：32K-128K tokens
|
||||
- 长上下文模型：1M+ tokens
|
||||
|
||||
## Connections
|
||||
- [[LLM]] ← uses ← [[Token]]
|
||||
- [[Token]] → affects → [[成本计算]]
|
||||
- [[Token]] → affects → [[上下文限制]]
|
||||
@@ -1,47 +0,0 @@
|
||||
---
|
||||
id: tool-wrapper
|
||||
title: "ToolWrapper"
|
||||
type: concept
|
||||
tags: [Agent, Skill, 设计模式]
|
||||
sources: []
|
||||
last_updated: 2026-03-19
|
||||
---
|
||||
|
||||
# ToolWrapper
|
||||
|
||||
将某个库或框架的规范文档打包成skill的包装模式。Agent只有在真正用到该技术时才会动态加载相关文档（references/目录），而非将所有规则塞入system prompt。
|
||||
|
||||
## 定义
|
||||
|
||||
ToolWrapper是一种Skill设计模式，核心机制是**按需加载**——将领域知识、编码规范、最佳实践封装为可触发的文档模块，仅在Agent检测到相关关键词时激活对应知识。
|
||||
|
||||
## 机制
|
||||
|
||||
- references/目录存放具体技术文档（如conventions.md）
|
||||
- SKILL.md监听特定关键词或事件
|
||||
- 当用户开始使用某技术时，动态加载对应规范
|
||||
- 规范被Agent当作"绝对真理"执行
|
||||
|
||||
## 适用场景
|
||||
|
||||
- 团队内部编码规范分发
|
||||
- 特定框架最佳实践封装
|
||||
- 减少system prompt信息过载
|
||||
- 需要精确控制规范版本和加载时机
|
||||
|
||||
## 优点
|
||||
|
||||
- 按需加载，不浪费上下文token
|
||||
- 规范独立，便于单独更新维护
|
||||
- Agent只在需要时才加载，避免干扰
|
||||
|
||||
## 缺点
|
||||
|
||||
- 需要预先识别和封装所有相关知识
|
||||
- 关键词触发机制可能遗漏边界情况
|
||||
- 多skill并发时可能有加载冲突
|
||||
|
||||
## 关系
|
||||
|
||||
- 上位概念：[[AgentSkill设计模式]]
|
||||
- 并列模式：[[Generator]]、[[Reviewer]]、[[Inversion]]、[[Pipeline]]
|
||||
@@ -1,32 +0,0 @@
|
||||
---
|
||||
id: vibe-coding
|
||||
title: "Vibe Coding"
|
||||
type: concept
|
||||
tags: [AI, programming, coding]
|
||||
sources:
|
||||
- "[[Claude Skills最值得研究的AI范式]]"
|
||||
last_updated: 2026-01-05
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
Vibe Coding是一种AI编程方式，通过自然语言与AI协作编写代码。
|
||||
|
||||
## Characteristics
|
||||
|
||||
- 自然语言为主
|
||||
- AI生成代码
|
||||
- 人类审核和调整
|
||||
- 降低编程门槛
|
||||
|
||||
## The End State
|
||||
|
||||
Vibe Coding的尽头是Skills：
|
||||
- 通过对话构建的代码和流程
|
||||
- 需要标准化为Skills以便复用
|
||||
- 最终沉淀为可维护的系统
|
||||
|
||||
## Connections
|
||||
- [[Vibe Coding]] ← uses ← [[Claude Skills]]
|
||||
- [[AI编程]] ← extends ← [[Vibe Coding]]
|
||||
- [[提示词工程]] ← relates_to ← [[Vibe Coding]]
|
||||
@@ -1,66 +0,0 @@
|
||||
---
|
||||
title: "Workspace"
|
||||
type: concept
|
||||
tags: [openclaw, workspace, configuration]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
# Workspace
|
||||
|
||||
OpenClaw中Agent的工作台目录，决定Agent如何工作。
|
||||
|
||||
## 核心文件
|
||||
|
||||
### AGENTS.md
|
||||
定义Agent的：
|
||||
- 岗位职责
|
||||
- 行为边界
|
||||
- 多Agent协调规则
|
||||
|
||||
### SOUL.md
|
||||
定义Agent的：
|
||||
- 性格叙事
|
||||
- 沟通风格
|
||||
- 价值观和边界
|
||||
|
||||
### USER.md
|
||||
固化用户的：
|
||||
- 偏好设定
|
||||
- 背景知识假设
|
||||
- 常见任务
|
||||
|
||||
### TOOLS.md
|
||||
声明工具的：
|
||||
- 可用工具
|
||||
- 使用原则
|
||||
- 受限工具
|
||||
|
||||
### IDENTITY.md
|
||||
结构化身份档案：
|
||||
- 名字
|
||||
- 角色类型
|
||||
- Emoji
|
||||
- 头像
|
||||
|
||||
### BOOTSTRAP.md
|
||||
一次性启动引导，完成后应删除。
|
||||
|
||||
### memory/
|
||||
长期记忆目录：
|
||||
- 按日期滚动的记忆笔记
|
||||
- 实现跨会话上下文保留
|
||||
|
||||
## 配置要点
|
||||
|
||||
1. **边界比能力更重要**：明确"不要做什么"
|
||||
2. **场景触发优于通用指令**：具体场景下的具体规则
|
||||
3. **简洁有效**：300-500字的AGENTS.md比2000字的更有效
|
||||
|
||||
## 与openclaw.json的关系
|
||||
- Workspace文件：管"Agent平时怎么干活"
|
||||
- openclaw.json：管"系统怎么跑Agent"
|
||||
|
||||
## 相关概念
|
||||
- [[OpenClaw]]
|
||||
- [[AGENTS.md]]
|
||||
- [[SOUL.md]]
|
||||
@@ -1,24 +0,0 @@
|
||||
---
|
||||
title: "YouTube RSS"
|
||||
type: concept
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
通过 YouTube 频道的 channel_id 拼接的 Atom/RSS 订阅格式，允许用户通过 RSS 阅读器订阅频道更新。YouTube 已移除官方 RSS 订阅按钮，需通过"查看页面源码"获取 channel_id。
|
||||
|
||||
## How to Get
|
||||
1. 访问 YouTube 频道页面（如 https://www.youtube.com/@CHANNEL_NAME）
|
||||
2. 右键 → "查看页面源码"（View Page Source）
|
||||
3. 搜索 "channel_id="
|
||||
4. 拼接 RSS URL：https://www.youtube.com/feeds/videos.xml?channel_id=<CHANNEL_ID>
|
||||
|
||||
## Why It Matters
|
||||
- YouTube 移除 RSS 按钮以迫使用户访问网站（商业动机）
|
||||
- RSS 是获取频道更新的无平台锁定方式
|
||||
|
||||
## Related Tools
|
||||
- 任意 RSS 阅读器（如 Feedly、Inoreader 等）
|
||||
|
||||
## Sources
|
||||
- [[YouTube-RSS-Feed.md]]
|
||||
@@ -1,36 +0,0 @@
|
||||
---
|
||||
id: vllm
|
||||
title: "vLLM"
|
||||
type: concept
|
||||
tags: [LLM, inference, GPU, optimization]
|
||||
sources:
|
||||
- "[[LLM Terms Framework]]"
|
||||
last_updated: 2025-12-20
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
vLLM是一个高效LLM推理框架，通过KV Cache和连续批处理提升GPU利用率。
|
||||
|
||||
## Key Optimizations
|
||||
|
||||
### KV Cache
|
||||
- 缓存已计算的Key-Value矩阵
|
||||
- 避免重复计算
|
||||
- 大幅提升推理速度
|
||||
|
||||
### Continuous Batching
|
||||
- 动态批处理多个请求
|
||||
- 提高GPU利用率
|
||||
- 降低延迟
|
||||
|
||||
## Why It Matters
|
||||
|
||||
- 官方HuggingFace推理速度慢
|
||||
- vLLM可提升10-24倍速度
|
||||
- 支持高并发推理
|
||||
|
||||
## Connections
|
||||
- [[LLM]] ← uses ← [[vLLM]]
|
||||
- [[推理优化]] ← uses ← [[vLLM]]
|
||||
- [[GPU利用率]] ← improves ← [[vLLM]]
|
||||
@@ -1,38 +0,0 @@
|
||||
---
|
||||
id: nine-grid
|
||||
title: "九宫格法"
|
||||
type: concept
|
||||
tags: [video, AI, image-generation]
|
||||
sources:
|
||||
- "[[固定镜头短视频AI全流程制作]]"
|
||||
last_updated: 2025-03-15
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
九宫格法是一次性生成3x3共九个分镜画面的方法，确保多个镜头之间的画面一致性。
|
||||
|
||||
## Mechanism
|
||||
|
||||
1. 将视频分割为9个分镜
|
||||
2. 一次性生成3x3网格图像
|
||||
3. 每个格子是一个分镜的关键帧
|
||||
4. 确保人物/场景在多个格子中保持一致
|
||||
|
||||
## Why It Works
|
||||
|
||||
- AI在单张图像内保持一致性更容易
|
||||
- 避免逐帧生成导致的人物变形
|
||||
- 提高多镜头视频的整体质量
|
||||
|
||||
## Five-Step Formula
|
||||
|
||||
1. 拆分镜头
|
||||
2. 一致性图像生成（九宫格法）
|
||||
3. 首尾针动画
|
||||
4. 快速剪辑
|
||||
5. 声音设计
|
||||
|
||||
## Connections
|
||||
- [[AI视频制作]] ← uses ← [[九宫格法]]
|
||||
- [[分镜设计]] ← uses ← [[九宫格法]]
|
||||
@@ -1,31 +0,0 @@
|
||||
---
|
||||
title: "共识投票"
|
||||
type: concept
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
多智能体系统中 N 个独立 LLM 对同一任务生成答案，取出现最频繁的结果作为最终输出的模式。核心机制是利用 LLM 随机性，让不同运行的噪声相互抵消。
|
||||
|
||||
## Mathematical Basis
|
||||
- 假设单模型幻觉率 = 20%（P_hallucination = 0.2）
|
||||
- N 个模型同时产生相同幻觉的概率 = P_hallucination^N
|
||||
- N = 3 时：0.2³ = 0.008 = 0.8%
|
||||
- 该公式与 SRE 中的 composite SLO 原理相同
|
||||
|
||||
## Implementation
|
||||
1. Spawn N LLMs（N 需要在成本和可靠性之间找到平衡）
|
||||
2. Fan out：给所有模型分配完全相同的任务
|
||||
3. Fan in：选取出现最频繁的答案
|
||||
|
||||
## Diversity Requirement
|
||||
- 各 Agent 最好使用不同模型（同质化噪声会放大而非抵消）
|
||||
- 确保参与者之间无反馈回路（防止群体思维和从众效应）
|
||||
- 实验应像盲测一样运行
|
||||
|
||||
## Best For
|
||||
- 事实核查
|
||||
- 分类任务（如"这是垃圾邮件吗？"）
|
||||
|
||||
## Sources
|
||||
- [[Multi-Agent-System-Reliability.md]]
|
||||
@@ -1,37 +0,0 @@
|
||||
---
|
||||
id: fixed-camera
|
||||
title: "固定机位"
|
||||
type: concept
|
||||
tags: [video-production, cinematography]
|
||||
sources:
|
||||
- "[[固定镜头短视频AI全流程制作]]"
|
||||
last_updated: 2025-03-15
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
固定机位是摄像机位置固定不变的拍摄方式，是固定镜头短视频的核心特征。
|
||||
|
||||
## Key Characteristics
|
||||
|
||||
- 摄像机位置不变
|
||||
- 只有画面内容变化
|
||||
- 适合展示时间流逝
|
||||
- 便于AI生成一致性画面
|
||||
|
||||
## Use Cases
|
||||
|
||||
- 家装视频
|
||||
- 产品展示
|
||||
- 教程演示
|
||||
- 时间压缩视频
|
||||
|
||||
## Connection to AI Video
|
||||
|
||||
固定机位降低AI视频生成的复杂度，通过：
|
||||
- 九宫格法保证画面一致性
|
||||
- 首尾针动画实现平滑过渡
|
||||
|
||||
## Connections
|
||||
- [[AI视频制作]] ← uses ← [[固定机位]]
|
||||
- [[短视频制作]] ← uses ← [[固定机位]]
|
||||
@@ -1,20 +0,0 @@
|
||||
---
|
||||
title: "固定点语义"
|
||||
type: concept
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
在递归自我优化生成系统中，稳定的生成能力对应于元生成算子 Φ 的不动点 G*，满足 Φ(G*) = G*。该生成器在自身的"生成→优化→更新"循环下保持不变。
|
||||
|
||||
## Core Properties
|
||||
- 不动点定义：G* ∈ G，满足 Φ(G*) = G*
|
||||
- 收敛条件：Φ 满足连续性或收缩性条件时，可通过迭代获得：G* = lim(n→∞) Φⁿ(G₀)
|
||||
- 自洽性：不动点的输出已编码其自身改进所需的标准
|
||||
|
||||
## Related Concepts
|
||||
- [[自举Meta生成]]：通过不动点实现递归自我优化的过程
|
||||
- [[生成器空间]]：Φ 作用的空间
|
||||
|
||||
## Sources
|
||||
- [[A-Formalization-of-Recursive-Self-Optimizing-Generative-Systems.md]]
|
||||
@@ -1,32 +0,0 @@
|
||||
---
|
||||
id: voice-cloning
|
||||
title: "声音克隆"
|
||||
type: concept
|
||||
tags: [TTS, voice, cloning]
|
||||
sources:
|
||||
- "[[AI配音与声音克隆工具合集]]"
|
||||
last_updated: 2025-03-06
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
声音克隆是用少量音频样本重建个人声音特征的技术。
|
||||
|
||||
## How It Works
|
||||
|
||||
1. 收集目标声音的短音频（2-30秒）
|
||||
2. 提取声音特征
|
||||
3. 生成新的语音内容
|
||||
|
||||
## Speed Comparison
|
||||
|
||||
| 工具 | 克隆速度 | 技术门槛 |
|
||||
|------|----------|----------|
|
||||
| F5-TTS | 2秒 | 高（需代码） |
|
||||
| 海螺AI | 30秒 | 低 |
|
||||
| AnyVoice | 3秒 | 低 |
|
||||
| ElevenLabs | 30秒 | 低 |
|
||||
|
||||
## Connections
|
||||
- [[AI配音]] ← uses ← [[声音克隆]]
|
||||
- [[内容创作]] ← uses ← [[声音克隆]]
|
||||
@@ -1,42 +0,0 @@
|
||||
---
|
||||
title: "多Agent可靠性模式"
|
||||
type: concept
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
多智能体系统中用于克服 LLM 不可靠性（幻觉、逻辑谬误、上下文漂移）的四大架构模式：层级结构、共识、 adversarial debate 和淘汰制。
|
||||
|
||||
## Four Patterns
|
||||
|
||||
### 1. 层级结构（Hierarchy）
|
||||
- **角色**：Planner（规划器）+ Worker（工作者）+ Validator（验证器）
|
||||
- **依赖图强制协作**：Worker 必须等待 Planner 分配任务，且无法作弊（Validator 会发现）
|
||||
- **适用场景**：需要将上下文分开的复杂工作流程
|
||||
|
||||
### 2. 共识（Consensus / Voting）
|
||||
- **机制**：N 个 LLM 独立生成同一任务答案，取多数票
|
||||
- **数学基础**：3 个模型同时产生相同幻觉的概率 = 0.2³ = 0.8%（假设单模型幻觉率 20%）
|
||||
- **适用场景**：事实核查、分类任务
|
||||
|
||||
### 3. 对抗辩论（Adversarial Debate）
|
||||
- **角色**：Generator → Critic（反对） → Judge（裁决）
|
||||
- **机制**：Truth survives the fight，真理越辩越明
|
||||
- **适用场景**：安全分析、代码审查、高风险内容审核
|
||||
|
||||
### 4. 淘汰制（Knock-out）
|
||||
- **类比**：SRE 中服务器是"cattle"（可替换）而非"pets"（独一无二）
|
||||
- **机制**：N 个 Agent 执行任务，最差者被淘汰；可选择用获胜者特征替换已淘汰者
|
||||
- **适用场景**：迭代式 Agent 工程、开发调试
|
||||
|
||||
## Core Insight
|
||||
> "Stop treating LLMs like magic chatbots. Start treating them like unreliable components in a distributed system."
|
||||
|
||||
## Related Concepts
|
||||
- [[LLM不可靠性]]
|
||||
- [[验证器模式]]
|
||||
- [[共识投票]]
|
||||
- [[AI拟人化谬误]]
|
||||
|
||||
## Sources
|
||||
- [[Multi-Agent-System-Reliability.md]]
|
||||
@@ -1,64 +0,0 @@
|
||||
---
|
||||
title: "多Agent系统"
|
||||
type: concept
|
||||
tags: [multi-agent, collaboration, agent]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
# 多Agent系统
|
||||
|
||||
多个专业Agent协同工作的架构模式，每个Agent有独特的角色和职责。
|
||||
|
||||
## 核心模式
|
||||
|
||||
### 分散式协调
|
||||
通过共享STATE.yaml文件协调，而非中央orchestrator：
|
||||
- Agent读写共享状态文件
|
||||
- 多子Agent并行工作
|
||||
- 主会话保持精简（CEO模式）
|
||||
|
||||
### STATE.yaml
|
||||
项目协调文件，作为单一事实来源：
|
||||
```yaml
|
||||
project: website-redesign
|
||||
tasks:
|
||||
- id: homepage-hero
|
||||
status: in_progress
|
||||
owner: pm-frontend
|
||||
```
|
||||
|
||||
### 团队配置示例
|
||||
- [[Milo]]：策略Lead
|
||||
- [[Josh]]：商业分析
|
||||
- Marketing Agent：营销研究
|
||||
- Dev Agent：开发
|
||||
|
||||
## 关键优势
|
||||
|
||||
1. **专业化分工**：每个Agent专注特定领域
|
||||
2. **并行执行**：多任务同时处理
|
||||
3. **可扩展性**：新增Agent无需修改主逻辑
|
||||
4. **共享记忆**：团队成员共享项目上下文
|
||||
|
||||
## 协作机制
|
||||
|
||||
- **Telegram路由**：通过标签分配到不同Agent
|
||||
- **共享内存**：项目文档、目标、决策
|
||||
- **私有上下文**：每个Agent独有会话历史
|
||||
- **定时任务**：Agent主动工作
|
||||
|
||||
## Race Condition处理
|
||||
|
||||
当多个Agent编辑同一文件时：
|
||||
1. AUTONOMOUS.md：仅主会话编辑
|
||||
2. memory/tasks-log.md：仅追加，子Agent只添加新行
|
||||
|
||||
## 使用场景
|
||||
|
||||
- [[多Agent专业团队]]
|
||||
- [[多Agent内容工厂]]
|
||||
- [[自主项目管理]]
|
||||
- [[动态仪表板]]
|
||||
|
||||
## 相关链接
|
||||
- [Anthropic: Building Effective Agents](https://www.anthropic.com/research/building-effective-agents)
|
||||
@@ -1,59 +0,0 @@
|
||||
---
|
||||
title: "工作流自动化"
|
||||
type: concept
|
||||
tags: [automation, workflow, n8n]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
# 工作流自动化
|
||||
|
||||
使用工具自动执行重复性任务，减少人工干预。
|
||||
|
||||
## 核心概念
|
||||
|
||||
### 工作流（Workflow）
|
||||
由多个任务节点按一定顺序执行的自动化流程。
|
||||
|
||||
### 节点（Node）
|
||||
工作流中的单个操作单元：
|
||||
- 触发器：启动工作流
|
||||
- 动作：执行具体操作
|
||||
- 工具：辅助功能
|
||||
- 代码：自定义逻辑
|
||||
- AI节点：嵌入AI能力
|
||||
|
||||
## 与AI Agent的关系
|
||||
|
||||
- **Workflow**：预定义自动化，一致输出
|
||||
- **Agent**：基于LLM动态决定工具和输出
|
||||
- **Agentic系统**：结合两者优势
|
||||
|
||||
## 平台
|
||||
|
||||
### N8N
|
||||
- 可视化拖拽界面
|
||||
- 400+预构建集成
|
||||
- 支持自托管
|
||||
|
||||
### OpenClaw
|
||||
- 通过skill扩展能力
|
||||
- 自然语言配置
|
||||
- 记忆和上下文保留
|
||||
|
||||
## 安全集成模式
|
||||
|
||||
[[OpenClaw + n8n工作流编排]]：
|
||||
- Webhook调用n8n
|
||||
- 凭证隔离在n8n
|
||||
- 工作流可锁定
|
||||
|
||||
## 使用场景
|
||||
|
||||
- [[会议纪要自动化]]
|
||||
- [[邮件管理自动化]]
|
||||
- [[日历聚合]]
|
||||
- [[社交媒体自动化]]
|
||||
|
||||
## 相关链接
|
||||
- [N8N官网](https://n8n.io/)
|
||||
- [OpenClaw文档](https://docs.openclaw.ai)
|
||||
@@ -1,31 +0,0 @@
|
||||
---
|
||||
id: chain-of-thought
|
||||
title: "思维链引导"
|
||||
type: concept
|
||||
tags: [prompt-engineering, reasoning]
|
||||
sources:
|
||||
- "[[如何写出完美的Prompt]]"
|
||||
last_updated: 2025-12-02
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
思维链引导是一种提示词技术，让AI逐步推理而非直接给出答案。
|
||||
|
||||
## Mechanism
|
||||
|
||||
通过在提示词中要求AI展示推理过程：
|
||||
- 先分析问题
|
||||
- 再列出步骤
|
||||
- 最后给出答案
|
||||
|
||||
## Benefits
|
||||
|
||||
- 提高AI推理准确性
|
||||
- 减少幻觉发生
|
||||
- 让用户理解决策过程
|
||||
- 便于发现AI思维漏洞
|
||||
|
||||
## Connections
|
||||
- [[Prompt能力]] ← uses ← [[思维链引导]]
|
||||
- [[需求拆解]] ← extends ← [[思维链引导]]
|
||||
@@ -1,62 +0,0 @@
|
||||
---
|
||||
title: "技能系统"
|
||||
type: concept
|
||||
tags: [skill, openclaw, extension]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
# 技能系统
|
||||
|
||||
OpenClaw的扩展机制，通过技能包添加新能力。
|
||||
|
||||
## 技能结构
|
||||
|
||||
```
|
||||
skills/
|
||||
├── skill-name/
|
||||
│ └── SKILL.md
|
||||
```
|
||||
|
||||
## 常用技能
|
||||
|
||||
### 集成技能
|
||||
- [[Telegram]]：消息通道
|
||||
- [[Discord]]：协作平台
|
||||
- [[Slack]]：团队通讯
|
||||
|
||||
### 数据技能
|
||||
- [[YouTube]]：视频内容获取
|
||||
- [[Reddit]]：社区内容聚合
|
||||
- [[GitHub]]：代码和项目数据
|
||||
|
||||
### 工具技能
|
||||
- [[arxiv-reader]]：学术论文读取
|
||||
- [[latex-compiler]]：LaTeX编译
|
||||
- [[youtube-full]]：YouTube完整集成
|
||||
|
||||
### MCP技能
|
||||
- [[n8n-mcp]]：N8N节点访问
|
||||
- [[idea-reality-mcp]]：创意验证
|
||||
|
||||
## 技能安装
|
||||
|
||||
通过ClawHub安装：
|
||||
```bash
|
||||
npx clawhub@latest install skill-name
|
||||
```
|
||||
|
||||
或通过OpenClaw：
|
||||
```text
|
||||
Install the youtube-full skill
|
||||
```
|
||||
|
||||
## 技能开发
|
||||
|
||||
技能是包含SKILL.md的目录，定义：
|
||||
- 工具列表
|
||||
- 使用方法
|
||||
- 配置要求
|
||||
|
||||
## 使用场景
|
||||
|
||||
详见各use case中的"Skills you Need"部分。
|
||||
@@ -1,33 +0,0 @@
|
||||
---
|
||||
id: prompt-framework
|
||||
title: "提示词框架"
|
||||
type: concept
|
||||
tags: [Nano Banana, prompt-engineering, image-generation]
|
||||
sources:
|
||||
- "[[Nano Banana提示词框架]]"
|
||||
last_updated: 2025-03-15
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
提示词框架是结构化描述图像生成需求的模板，通过标准化字段确保生成质量可控。
|
||||
|
||||
## Framework Types
|
||||
|
||||
### 物件描述框架
|
||||
- shot：镜头类型
|
||||
- subject：包含item/materials/details/condition
|
||||
- environment：环境描述
|
||||
- lighting：光线
|
||||
- camera：相机设置
|
||||
- color_grade：色彩分级
|
||||
- style：风格
|
||||
- quality：质量参数
|
||||
- negatives：负面提示
|
||||
|
||||
### 人物描述框架
|
||||
- subject：包含age/appearance/pose等字段
|
||||
|
||||
## Connections
|
||||
- [[AI图像生成]] ← uses ← [[提示词框架]]
|
||||
- [[Nano Banana]] ← supports ← [[提示词框架]]
|
||||
@@ -1,30 +0,0 @@
|
||||
---
|
||||
title: "泰勒主义软件工厂"
|
||||
type: concept
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
将开发者定位为高层控制者、周围是大量无面孔 Agent 的软件工程架构思维。源自泰勒科学管理思想——将人视为可替换的生产单元，通过标准化流程最大化效率。
|
||||
|
||||
## Core Pattern
|
||||
- 开发者 = 高层控制者（Product Manager / Commander）
|
||||
- Agent = 无面孔、可替换的生产单元（类似于泰勒制中的流水线工人）
|
||||
- 关系 = 控制与执行，而非协作
|
||||
|
||||
## Related Debate
|
||||
- 与 [[Agentic AI]] 的协作型定位（Claude Code、Copilot 等命名伙伴角色）形成鲜明对比
|
||||
- [[AI拟人化谬误]] 提供工具命名和定位如何反映工作价值认知的分析框架
|
||||
|
||||
## Criticism
|
||||
- 简化了开发工作的复杂性和创造性价值
|
||||
- 忽视了开发者作为决策者和创新者的角色
|
||||
- [[Ferdinand]] 指出这种框架缺乏对工作的尊重
|
||||
|
||||
## Related Concepts
|
||||
- [[AI拟人化谬误]]
|
||||
- [[Agentic AI]]
|
||||
- [[多Agent系统]]
|
||||
|
||||
## Sources
|
||||
- [[The-Picture-They-Paint-of-You.md]]
|
||||
@@ -1,34 +0,0 @@
|
||||
---
|
||||
id: workflow-engineering
|
||||
title: "流程工程"
|
||||
type: concept
|
||||
tags: [AI, workflow, SOP, engineering]
|
||||
sources:
|
||||
- "[[Claude Skills最值得研究的AI范式]]"
|
||||
last_updated: 2026-01-05
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
流程工程是将重复任务拆解为AI能理解、稳定复用的流程，并通过Skills实现标准化的工程化方法。
|
||||
|
||||
## vs 提示词工程
|
||||
|
||||
| 维度 | 提示词工程 | 流程工程 |
|
||||
|------|------------|----------|
|
||||
| 核心 | 单次Prompt优化 | 全流程标准化 |
|
||||
| 稳定性 | 依赖模型表现 | SOP固化 |
|
||||
| 复用性 | 低 | 高 |
|
||||
| 目标 | 一次好结果 | 稳定可重复 |
|
||||
|
||||
## Key Elements
|
||||
|
||||
- **SOP标准化**：将经验沉淀为操作步骤
|
||||
- **Skills封装**：AI技能的模块化
|
||||
- **自动化执行**：交给AI稳定运行
|
||||
- **反馈迭代**：持续优化流程
|
||||
|
||||
## Connections
|
||||
- [[提示词工程]] ← evolves_to ← [[流程工程]]
|
||||
- [[Claude Skills]] ← implements ← [[流程工程]]
|
||||
- [[SOP标准化]] ← enables ← [[流程工程]]
|
||||
@@ -1,31 +0,0 @@
|
||||
---
|
||||
id: structured-expression
|
||||
title: "结构化表达"
|
||||
type: concept
|
||||
tags: [prompt-engineering, communication]
|
||||
sources:
|
||||
- "[[如何写出完美的Prompt]]"
|
||||
last_updated: 2025-12-02
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
结构化表达是用清晰逻辑组织信息的方法，确保AI准确理解人类意图。
|
||||
|
||||
## Principles
|
||||
|
||||
- 层次分明：按重要性和逻辑顺序组织
|
||||
- 格式统一：使用一致的标记和分隔符
|
||||
- 信息完整：不遗漏关键上下文
|
||||
- 表达精准：避免歧义和模糊表述
|
||||
|
||||
## Techniques
|
||||
|
||||
- 使用编号列表组织要点
|
||||
- 使用标题区分不同部分
|
||||
- 使用表格呈现结构化数据
|
||||
- 使用引用标记重要信息
|
||||
|
||||
## Connections
|
||||
- [[Prompt能力]] ← enables ← [[结构化表达]]
|
||||
- [[结构化思维]] ← implements ← [[结构化表达]]
|
||||
@@ -1,26 +0,0 @@
|
||||
---
|
||||
title: "自举Meta生成"
|
||||
type: concept
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
通过递归优化循环实现系统自我超越的过程：α-提示词（生成器）和 Ω-提示词（优化器）通过迭代不断优化自身，无限逼近理想状态。
|
||||
|
||||
## Bootstrap Cycle
|
||||
1. **创生（Bootstrap）**：用 AI 生成 α-提示词 和 Ω-提示词 的初始版本 (v1)
|
||||
2. **自省与进化（Self-Correction）**：用 Ω-提示词(v1) 优化 α-提示词(v1)，得到更强的 α-提示词(v2)
|
||||
3. **创造（Generation）**：用进化后的 α-提示词(v2) 生成所有目标提示词和技能
|
||||
4. **循环与飞跃（Recursive Loop）**：将新生成的产物反馈给系统，启动下一轮进化
|
||||
|
||||
## Relationship to Fixed Points
|
||||
- 稳定生成能力 = Φ 的不动点
|
||||
- 递归优化循环 → 逼近不动点
|
||||
- 不动点 = 自举过程的极限状态
|
||||
|
||||
## Related Concepts
|
||||
- [[固定点语义]]：自举过程的稳定状态定义
|
||||
- [[生成器空间]]：α-提示词 和 Ω-提示词 迭代的空间
|
||||
|
||||
## Sources
|
||||
- [[A-Formalization-of-Recursive-Self-Optimizing-Generative-Systems.md]]
|
||||
@@ -1,63 +0,0 @@
|
||||
---
|
||||
title: "记忆系统"
|
||||
type: concept
|
||||
tags: [memory, openclaw, context]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
# 记忆系统
|
||||
|
||||
AI Agent跨会话保留上下文和知识的能力。
|
||||
|
||||
## OpenClaw记忆机制
|
||||
|
||||
### 内置方案（builtin）
|
||||
原始记忆存储在Markdown文件中，系统维护本地索引方便检索。
|
||||
|
||||
### QMD方案
|
||||
围绕workspace中的Markdown文件，使用更强的检索/索引方式。
|
||||
|
||||
### 记忆流程
|
||||
```
|
||||
对话发生
|
||||
↓
|
||||
Agent通过普通文件工具把重要信息写入memory/或MEMORY.md
|
||||
↓
|
||||
下次对话开始
|
||||
↓
|
||||
Agent通过memory_search/memory_get检索相关记忆
|
||||
↓
|
||||
相关记忆被注入到当前对话上下文
|
||||
↓
|
||||
Agent表现出"我记得你说过……"的能力
|
||||
```
|
||||
|
||||
## 向量语义搜索
|
||||
|
||||
[[Semantic Memory Search]]使用memsearch：
|
||||
- 索引Markdown记忆文件到向量数据库
|
||||
- 通过含义搜索而非关键词
|
||||
- SHA-256内容哈希避免重复嵌入
|
||||
|
||||
## Workspace记忆文件
|
||||
|
||||
- [[memory/]]：按日期滚动的记忆笔记
|
||||
- [[MEMORY.md]]：长期知识总表
|
||||
- 与memory/目录兼容
|
||||
|
||||
## 关键洞察
|
||||
|
||||
- 对Agent来说，真正算数的长期记忆是Markdown文件
|
||||
- 向量索引只是派生缓存，可以随时重建
|
||||
- 文件永不修改
|
||||
|
||||
## 使用场景
|
||||
|
||||
- [[第二大脑]]
|
||||
- [[个人CRM]]
|
||||
- [[健康症状追踪]]
|
||||
|
||||
## 相关工具
|
||||
|
||||
- [[memsearch]]：向量语义搜索工具
|
||||
- [[Milvus]]：向量数据库后端
|
||||
@@ -1,36 +0,0 @@
|
||||
---
|
||||
id: requirement-decomposition
|
||||
title: "需求拆解"
|
||||
type: concept
|
||||
tags: [prompt-engineering, structured-thinking]
|
||||
sources:
|
||||
- "[[如何写出完美的Prompt]]"
|
||||
last_updated: 2025-12-02
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
需求拆解是将模糊目标转化为具体可执行子任务的过程。
|
||||
|
||||
## Methods
|
||||
|
||||
### 基础方法
|
||||
- **需求拆解法**：将复杂任务分解为简单步骤
|
||||
- **上下文补全法**：补充背景信息让AI理解场景
|
||||
- **格式定义法**：明确输出格式要求
|
||||
- **示例引导法**：提供参考案例
|
||||
|
||||
### 进阶策略
|
||||
- **思维链引导**：让AI逐步推理
|
||||
- **任务拆分**：大任务分解为子任务
|
||||
- **角色赋能**：赋予AI特定专业角色
|
||||
- **预填回复**：提供初始回答框架
|
||||
|
||||
### 高阶技巧
|
||||
- **跨模态联动**：结合多种输入输出形式
|
||||
- **领域知识注入**：嵌入专业知识
|
||||
- **反馈循环嵌入**：建立迭代优化机制
|
||||
|
||||
## Connections
|
||||
- [[Prompt能力]] ← requires ← [[需求拆解]]
|
||||
- [[结构化表达]] ← enables ← [[需求拆解]]
|
||||
@@ -1,29 +0,0 @@
|
||||
---
|
||||
id: audio-overview
|
||||
title: "音频概览"
|
||||
type: concept
|
||||
tags: [NotebookLM, learning, podcast]
|
||||
sources:
|
||||
- "[[7 ways I use NotebookLM to make my life easier]]"
|
||||
last_updated: 2025-11-23
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
音频概览是NotebookLM的功能，将文档转化为AI双人播客格式，适合被动学习。
|
||||
|
||||
## Mechanism
|
||||
|
||||
- AI分析文档内容
|
||||
- 生成两个AI声音的对话
|
||||
- 用户可以收听而非阅读
|
||||
|
||||
## Use Cases
|
||||
|
||||
- 通勤时学习
|
||||
- 视觉疲劳时继续学习
|
||||
- 将长文档转化为可听的摘要
|
||||
|
||||
## Connections
|
||||
- [[NotebookLM]] ← implements ← [[音频概览]]
|
||||
- [[被动学习]] ← uses ← [[音频概览]]
|
||||
@@ -1,37 +0,0 @@
|
||||
---
|
||||
id: frame-interpolation
|
||||
title: "首尾针动画"
|
||||
type: concept
|
||||
tags: [video, AI, animation]
|
||||
sources:
|
||||
- "[[固定镜头短视频AI全流程制作]]"
|
||||
last_updated: 2025-03-15
|
||||
---
|
||||
|
||||
## Definition
|
||||
|
||||
首尾针动画是通过AI自动补齐首尾帧之间中间动作的技术，实现平滑过渡效果。
|
||||
|
||||
## Mechanism
|
||||
|
||||
1. 确定起始帧和结束帧
|
||||
2. AI分析首尾帧的差异
|
||||
3. 自动生成中间过渡帧
|
||||
4. 输出流畅视频
|
||||
|
||||
## Tools
|
||||
|
||||
- 海螺AI
|
||||
- KAI
|
||||
- 其他AI动效工具
|
||||
|
||||
## Connection to Fixed-Camera Video
|
||||
|
||||
固定机位视频天然适合首尾针动画，因为：
|
||||
- 背景固定，减少AI生成负担
|
||||
- 只需关注主体变化
|
||||
- 更容易保持一致性
|
||||
|
||||
## Connections
|
||||
- [[AI视频制作]] ← uses ← [[首尾针动画]]
|
||||
- [[固定机位]] ← enables ← [[首尾针动画]]
|
||||
@@ -1,25 +0,0 @@
|
||||
---
|
||||
title: "验证器模式"
|
||||
type: concept
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
多智能体系统中 Validator（验证器）检查 Worker 输出质量，不合格则退回的机制。验证器可以是确定性代码（单元测试、JSON Schema 验证）或 LLM 本身。
|
||||
|
||||
## Validation Methods
|
||||
- **确定性代码验证**：单元测试、JSON Schema 验证、正则表达式匹配
|
||||
- **LLM 验证**：单独训练或提示的验证模型判断输出质量
|
||||
- **双模式**：可单独验证每个 Worker 输出，或在汇总所有结果后整体验证
|
||||
|
||||
## Placement in Multi-Agent Patterns
|
||||
- [[层级结构]]（Hierarchy）：Validator 是关键角色，位于 Planner → Worker → Validator 链路的末端
|
||||
- [[淘汰制]]（Knock-out）：Validator 决定哪些 Agent 被淘汰
|
||||
- [[对抗辩论]]（Adversarial Debate）：Watchdog（确定性代码）打破辩论死循环
|
||||
|
||||
## Best Practice
|
||||
- Validator 最好使用与 Generator/Worker 不同的模型（提高质量和客观性）
|
||||
- 验证器可以在同一 LLM 会话中与规划器协作（PLAN → VALIDATION loop）
|
||||
|
||||
## Sources
|
||||
- [[Multi-Agent-System-Reliability.md]]
|
||||
@@ -1,28 +0,0 @@
|
||||
---
|
||||
title: "Alex Ewerlöf"
|
||||
type: entity
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
资深工程师，拥有 27 年工作经验，瑞典皇家理工学院（KTH）系统工程硕士学位。过去十年专注于可靠性工程和弹性架构，自 2023 年专攻 LLM。
|
||||
|
||||
## Aliases
|
||||
- Alex Ewerlöf
|
||||
- Alex Ewerlof
|
||||
|
||||
## Key Contributions
|
||||
- 提出多智能体系统四大可靠性架构模式：Hierarchy、Consensus、Adversarial Debate、Knock-out
|
||||
- 倡导将 LLM 视为分布式系统中不可靠组件的工程思维
|
||||
- 强调不要拟人化 LLM，而应利用可靠性工程原理构建稳健系统
|
||||
|
||||
## Notable Work
|
||||
- [[Multi-Agent-System-Reliability.md]]：多智能体系统可靠性四大架构模式
|
||||
|
||||
## Related Concepts
|
||||
- [[多Agent可靠性模式]]
|
||||
- [[LLM不可靠性]]
|
||||
- [[验证器模式]]
|
||||
|
||||
## Sources
|
||||
- [[Multi-Agent-System-Reliability.md]]
|
||||
@@ -1,23 +0,0 @@
|
||||
---
|
||||
title: "Anthropic"
|
||||
type: entity
|
||||
tags: []
|
||||
sources: []
|
||||
last_updated: 2025-12-19
|
||||
---
|
||||
|
||||
## Definition
|
||||
Anthropic是一家AI安全研究公司，开发了Claude系列大语言模型。运营官方Prompt Library平台，提供66+高质量预制提示词。
|
||||
|
||||
## Role
|
||||
- AI模型开发商：Claude系列模型的开发商
|
||||
- Prompt平台运营方：维护官方Prompt Library
|
||||
|
||||
## Key Properties
|
||||
- 核心产品：Claude（系列大语言模型）
|
||||
- Prompt Library：66+预制提示词，覆盖开发、数据处理、创意等场景
|
||||
- API平台：提供Claude API访问
|
||||
|
||||
## Connections
|
||||
- [[ClaudeSkills]] ← 支撑 ← [[Anthropic]]
|
||||
- [[PromptLibrary]] ← 运营 ← [[Anthropic]]
|
||||
@@ -1,22 +0,0 @@
|
||||
---
|
||||
title: "Canva"
|
||||
type: entity
|
||||
tags: []
|
||||
sources: []
|
||||
last_updated: 2025-10-26
|
||||
---
|
||||
|
||||
## Definition
|
||||
Canva是一个在线设计平台，提供海量模板，支持AI辅助设计。用户可通过简单拖拽创建专业级视觉内容，包括PPT、社交媒体图片、海报等。
|
||||
|
||||
## Role
|
||||
- 在线设计平台：提供设计模板和工具
|
||||
- AI辅助设计工具：集成AI功能提升设计效率
|
||||
|
||||
## Key Properties
|
||||
- 模板库：海量专业设计模板
|
||||
- AI功能：Magic Design、背景移除等AI辅助功能
|
||||
- 多格式导出：PNG、JPG、PDF、MP4等
|
||||
|
||||
## Connections
|
||||
- [[ChatGPT-Canva-Gamma-简报工作流]] ← 使用 ← [[Canva]]
|
||||
@@ -1,35 +0,0 @@
|
||||
---
|
||||
id: clawdtalk
|
||||
title: "ClawdTalk"
|
||||
type: entity
|
||||
tags: [OpenClaw, 电话, 语音]
|
||||
sources: []
|
||||
last_updated: 2026-03-19
|
||||
---
|
||||
|
||||
# ClawdTalk
|
||||
|
||||
OpenClaw的电话集成工具，使AI Agent可通过电话进行语音交互。
|
||||
|
||||
## 基本信息
|
||||
|
||||
- 类型：OpenClaw技能/插件
|
||||
- GitHub：https://github.com/team-telnyx/clawdtalk-client
|
||||
- 官网：https://clawdtalk.com
|
||||
|
||||
## 功能
|
||||
|
||||
- 接收和拨打电话，将任意电话变为AI助手入口
|
||||
- 语音交互，无需智能手机或浏览器
|
||||
- 支持日历查询、Jira更新、网络搜索等技能的电话语音访问
|
||||
|
||||
## 技术架构
|
||||
|
||||
- 依赖Telnyx API提供电话连通性
|
||||
- 与OpenClaw深度集成，作为trigger节点
|
||||
|
||||
## 在本Wiki中的角色
|
||||
|
||||
- 实现[[语音助手]]能力的核心技术
|
||||
- 支持[[免手操作]]场景（驾驶、步行等）
|
||||
- 与[[Telnyx]]协同提供电话服务
|
||||
@@ -1,26 +0,0 @@
|
||||
---
|
||||
title: "Coze"
|
||||
type: entity
|
||||
tags: []
|
||||
sources: []
|
||||
last_updated: 2025-06-20
|
||||
---
|
||||
|
||||
## Definition
|
||||
Coze（扣子）是字节跳动旗下的AI Agent（智能体）开发平台，支持国内版（coze.cn）和海外版（coze.com）。提供Bot创建、工作流编排、插件调用等能力，覆盖金融、教育、医疗、电商、客服等多个行业场景。
|
||||
|
||||
## Role
|
||||
- AI Agent开发平台：提供可视化的Bot和工作流编排能力
|
||||
- 行业解决方案平台：内置多行业落地Demo模板
|
||||
- 低代码/无代码：无需编程基础即可搭建AI应用
|
||||
|
||||
## Key Properties
|
||||
- 支持国内版coze.cn和海外版coze.com，功能基本同步
|
||||
- 支持Bot+工作流组合，实现复杂业务逻辑
|
||||
- 覆盖行业：金融、教育、医疗、电商、泛娱乐、在线客服
|
||||
- 支持插件调用（Function Call）、知识库问答、图片生成等能力
|
||||
|
||||
## Connections
|
||||
- [[Coze平台Demo合集]]：来源页面，包含多行业Demo合集
|
||||
- [[Bot编排]] ← 支撑 ← [[Coze]]
|
||||
- [[Agent模式]] ← 支撑 ← [[Coze]]
|
||||
@@ -1,17 +0,0 @@
|
||||
---
|
||||
title: "Cursor"
|
||||
type: entity
|
||||
tags: [ide, ai-tool]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
## Aliases
|
||||
- Cursor AI
|
||||
- Cursor IDE
|
||||
|
||||
## Summary
|
||||
Cursor 是一个集成了多种 AI 能力的代码编辑器，支持接入外部的大模型与服务。在较新的版本中，其 Composer 模块支持接入 [[MCP]]（Modal Context Protocol），允许开发者通过大模型自动化地执行工具和命令行任务。
|
||||
|
||||
## Key Connections
|
||||
- [[Cursor]] ← extends ← [[MCP]]
|
||||
- [[Cursor]] 包含交互组件 [[Agent模式]] 和 Normal 模式
|
||||
@@ -1,25 +0,0 @@
|
||||
---
|
||||
title: "DeepSeek"
|
||||
type: entity
|
||||
tags: []
|
||||
sources: []
|
||||
last_updated: 2025-12-19
|
||||
---
|
||||
|
||||
## Definition
|
||||
DeepSeek（深度求索）是一家国产AI公司，开发了DeepSeek系列开源大语言模型。性能对标GPT-4等顶级模型，支持长上下文，开源可商用。
|
||||
|
||||
## Role
|
||||
- 国产大模型开发商：DeepSeek系列模型的开发方
|
||||
- 开源AI推动者：开源权重模型，降低AI使用门槛
|
||||
|
||||
## Key Properties
|
||||
- 模型系列：DeepSeek Coder、DeepSeek Math、DeepSeek LLM等
|
||||
- 开源：模型权重开放，可本地部署
|
||||
- 性能：部分任务性能对标GPT-4
|
||||
- 成本：API价格显著低于GPT-4
|
||||
|
||||
## Connections
|
||||
- [[DeepSeek使用手册清华版]] ← 来源 ← [[DeepSeek]]
|
||||
- [[Ollama]] ← 支持运行 ← [[DeepSeek]]
|
||||
- [[LLM]] ← relates_to ← [[DeepSeek]]
|
||||
@@ -1,29 +0,0 @@
|
||||
---
|
||||
id: deepsider
|
||||
title: "DeepSider"
|
||||
type: entity
|
||||
tags: [browser-extension, AI, multi-model]
|
||||
sources:
|
||||
- "[[Nano Banana 2使用指南]]"
|
||||
last_updated: 2025-12-01
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
DeepSider是浏览器插件，聚合多AI模型供用户使用，国内可直接访问。
|
||||
|
||||
## Key Features
|
||||
|
||||
- 支持Gemini 3.0、Gemini 3 Pro Image（Nano Banana 2）、GPT-5.1等模型
|
||||
- 国内可用，绕过访问限制
|
||||
- 浏览器插件形式，便捷集成
|
||||
|
||||
## Use Cases
|
||||
|
||||
- 访问Gemini系列模型
|
||||
- AI图像生成（Nano Banana 2）
|
||||
- 多模型对比使用
|
||||
|
||||
## Connections
|
||||
- [[DeepSider]] → enables → [[Nano Banana 2]]
|
||||
- [[AI工具聚合]] ← uses ← [[DeepSider]]
|
||||
@@ -1,28 +0,0 @@
|
||||
---
|
||||
id: elevenlabs
|
||||
title: "ElevenLabs"
|
||||
type: entity
|
||||
tags: [AI, TTS, voice-cloning, international]
|
||||
sources:
|
||||
- "[[AI配音与声音克隆工具合集]]"
|
||||
last_updated: 2025-03-06
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
ElevenLabs是国际顶流AI配音和声音克隆平台，支持30+语言和情感变化，付费较高。
|
||||
|
||||
## Key Features
|
||||
|
||||
- 30+语言支持
|
||||
- 情感变化控制
|
||||
- 高保真声音克隆
|
||||
- 国际顶流品质
|
||||
|
||||
## Pricing
|
||||
|
||||
付费较贵，适合专业用户
|
||||
|
||||
## Connections
|
||||
- [[AI配音]] ← uses ← [[ElevenLabs]]
|
||||
- [[声音克隆]] ← uses ← [[ElevenLabs]]
|
||||
@@ -1,25 +0,0 @@
|
||||
---
|
||||
id: f5-tts
|
||||
title: "F5-TTS"
|
||||
type: entity
|
||||
tags: [AI, TTS, voice-cloning, open-source]
|
||||
sources:
|
||||
- "[[AI配音与声音克隆工具合集]]"
|
||||
last_updated: 2025-03-06
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
F5-TTS是开源语音克隆项目，2秒即可克隆声音，适合技术流用户，需要代码基础。
|
||||
|
||||
## Key Features
|
||||
|
||||
- 开源免费
|
||||
- 2秒克隆
|
||||
- 技术流首选
|
||||
- 需代码基础
|
||||
|
||||
## Connections
|
||||
- [[AI配音]] ← uses ← [[F5-TTS]]
|
||||
- [[声音克隆]] ← uses ← [[F5-TTS]]
|
||||
- [[开源工具]] ← extends ← [[F5-TTS]]
|
||||
@@ -1,26 +0,0 @@
|
||||
---
|
||||
title: "Ferdinand"
|
||||
type: entity
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
技术博主，专注于软件工程和 AI 领域，作品涵盖《找乐子》（找乐子）等博客，关注 AI 工具的命名哲学和设计隐喻。
|
||||
|
||||
## Aliases
|
||||
- Ferdinand
|
||||
|
||||
## Key Contributions
|
||||
- 长期研究软件工程和 AI 的交叉领域
|
||||
- 批评将 LLM 拟人化的设计谬误
|
||||
- 指出 AI 工具命名和框架反映的价值观问题
|
||||
|
||||
## Notable Work
|
||||
- [[The-Picture-They-Paint-of-You.md]]：分析 AI SRE 与编码助手命名差异揭示的工作价值认知
|
||||
|
||||
## Related Concepts
|
||||
- [[泰勒主义软件工厂]]
|
||||
- [[AI拟人化谬误]]
|
||||
|
||||
## Sources
|
||||
- [[The-Picture-They-Paint-of-You.md]]
|
||||
@@ -1,27 +0,0 @@
|
||||
---
|
||||
title: "GNews API"
|
||||
type: entity
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
轻量级新闻 API 平台，聚合全球可靠新闻，提供实时覆盖，支持按话题、语言和国家过滤。
|
||||
|
||||
## Aliases
|
||||
- GNews
|
||||
- GNews API
|
||||
|
||||
## Key Features
|
||||
- 实时全球新闻覆盖
|
||||
- 按话题、语言和国家过滤
|
||||
- 定价亲民，适合初创企业
|
||||
|
||||
## Use Cases
|
||||
- 区域化新闻小工具
|
||||
- 面向特定语言或地区受众的新闻聚合器
|
||||
|
||||
## Related Concepts
|
||||
- [[新闻API]]
|
||||
|
||||
## Sources
|
||||
- [[Best-7-News-API-Data-Feeds.md]]
|
||||
@@ -1,22 +0,0 @@
|
||||
---
|
||||
title: "Gamma AI"
|
||||
type: entity
|
||||
tags: []
|
||||
sources: []
|
||||
last_updated: 2025-10-26
|
||||
---
|
||||
|
||||
## Definition
|
||||
Gamma AI是一个AI驱动的简报和文档生成平台，通过AI帮助用户快速创建专业级的PPT演示文稿和网页内容。
|
||||
|
||||
## Role
|
||||
- AI简报生成平台：利用AI自动生成精美简报
|
||||
- 内容创作工具：AI辅助创建文档和演示内容
|
||||
|
||||
## Key Properties
|
||||
- AI生成：输入主题即可生成完整简报
|
||||
- 多格式：支持导出PPT、PDF
|
||||
- 模板丰富：专业设计模板
|
||||
|
||||
## Connections
|
||||
- [[ChatGPT-Canva-Gamma-简报工作流]] ← 使用 ← [[GammaAI]]
|
||||
@@ -1,30 +0,0 @@
|
||||
---
|
||||
id: google
|
||||
title: "Google"
|
||||
type: entity
|
||||
tags: [公司, 云服务, AI]
|
||||
sources: []
|
||||
last_updated: 2026-03-19
|
||||
---
|
||||
|
||||
# Google
|
||||
|
||||
Alphabet Inc.旗下科技公司，云服务提供商，AI领域重要玩家。
|
||||
|
||||
## 基本信息
|
||||
|
||||
- 全称：Google LLC（Alphabet Inc.子公司）
|
||||
- 总部：美国加州山景城
|
||||
- 核心业务：搜索、广告、云计算、AI
|
||||
|
||||
## AI相关
|
||||
|
||||
- Google Cloud：提供AI/ML云服务
|
||||
- Gemini：Google AI大语言模型系列
|
||||
- ADK（Agent Development Kit）：Google发布的Agent开发工具包
|
||||
- 2026年发布5种Agent Skill设计模式指南
|
||||
|
||||
## 在本Wiki中的角色
|
||||
|
||||
- 发布[[AgentSkill设计模式]]（ToolWrapper、Generator、Reviewer、Inversion、Pipeline）的源头之一
|
||||
- 与[[Anthropic]]并列为Skill设计的两大参考来源
|
||||
@@ -1,24 +0,0 @@
|
||||
---
|
||||
id: langchain
|
||||
title: "LangChain"
|
||||
type: entity
|
||||
tags: [LLM, framework, RAG]
|
||||
sources:
|
||||
- "[[RAG从入门到精通系列1：基础RAG]]"
|
||||
last_updated: 2025-12-18
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
LangChain是RAG实现框架，用于构建基于LLM的应用。
|
||||
|
||||
## Key Features
|
||||
|
||||
- RAG流程封装
|
||||
- 多种数据源连接
|
||||
- Chain构建能力
|
||||
- Agent支持
|
||||
|
||||
## Connections
|
||||
- [[RAG]] ← uses ← [[LangChain]]
|
||||
- [[LLM应用开发]] ← uses ← [[LangChain]]
|
||||
@@ -1,45 +0,0 @@
|
||||
---
|
||||
title: "MCP"
|
||||
type: entity
|
||||
tags: [mcp, protocol, integration]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
# MCP
|
||||
|
||||
Modal Context Protocol（模态上下文协议），AI大模型与外围服务集成的协议。
|
||||
|
||||
## 基本信息
|
||||
- **全称**：Modal Context Protocol
|
||||
- **类型**：Client-Server架构协议
|
||||
- **用途**：实现大模型与外围工具服务的高效集成
|
||||
|
||||
## 核心功能
|
||||
|
||||
### 三种接口
|
||||
MCP Server提供三种功能接口：
|
||||
1. **资源获取**（Resource/GET）：类似HTTP GET请求
|
||||
2. **工具调用**（Tool/POST）：类似POST请求
|
||||
3. **Promise提示词**：用于多样化交互与扩展
|
||||
|
||||
### 客户端
|
||||
- [[Cursor]]：AI代码编辑器
|
||||
- Claude Desktop
|
||||
- 其他支持MCP的客户端
|
||||
|
||||
### 服务端
|
||||
- 热点新闻MCP Server
|
||||
- Sequential Thinking工具
|
||||
- [[n8n-mcp]]：N8N的MCP实现
|
||||
|
||||
## 接入方式
|
||||
1. **SSE服务方式**：通过Server-Sent Events接入
|
||||
2. **本地Command方式**：通过本地执行命令接入
|
||||
|
||||
## 使用场景
|
||||
|
||||
详见：
|
||||
- [[MCP在Cursor中的集成与应用]]
|
||||
|
||||
## 相关链接
|
||||
- [MCP协议文档](https://modelcontextprotocol.io/)
|
||||
@@ -1,29 +0,0 @@
|
||||
---
|
||||
title: "Mediastack"
|
||||
type: entity
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
可扩展的新闻聚合 API，从全球 7500+ 来源实时聚合新闻，支持免费套餐和付费高级功能。
|
||||
|
||||
## Aliases
|
||||
- Mediastack
|
||||
- mediastack API
|
||||
|
||||
## Key Features
|
||||
- 聚合全球 7500+ 新闻来源
|
||||
- 提供免费和付费套餐
|
||||
- 多语言支持和地理定向搜索
|
||||
- 适合初创企业到大型企业
|
||||
|
||||
## Use Cases
|
||||
- 新闻聚合应用
|
||||
- 内容平台的实时头条
|
||||
- 预算友好型新闻数据集成
|
||||
|
||||
## Related Concepts
|
||||
- [[新闻API]]
|
||||
|
||||
## Sources
|
||||
- [[Best-7-News-API-Data-Feeds.md]]
|
||||
@@ -1,45 +0,0 @@
|
||||
---
|
||||
title: "N8N"
|
||||
type: entity
|
||||
tags: [n8n, automation, workflow]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
# N8N
|
||||
|
||||
开源工作流自动化平台，支持节点连接执行任务。
|
||||
|
||||
## 基本信息
|
||||
- **类型**：工作流自动化平台
|
||||
- **开源协议**：Apache-2.0
|
||||
- **部署方式**：Docker、本地安装、云端
|
||||
- **特点**：可视化拖拽界面
|
||||
|
||||
## 核心概念
|
||||
|
||||
### 节点（Node）
|
||||
工作流中的单个操作单元，分为五类：
|
||||
- 触发器节点（Trigger）
|
||||
- 动作节点（Action）
|
||||
- 工具节点（Utility）
|
||||
- 代码节点（Code）
|
||||
- 高级AI节点（Advanced AI）
|
||||
|
||||
### 工作流（Workflow）
|
||||
由多个节点按一定顺序执行的自动化流程。
|
||||
|
||||
### 与AI Agent集成
|
||||
- [[n8n-mcp]]：N8N的MCP服务器实现
|
||||
- [[OpenClaw + n8n工作流编排]]：通过webhook安全集成
|
||||
- [[使用Claude自动生成N8N工作流]]
|
||||
|
||||
## 使用场景
|
||||
|
||||
详见各use case：
|
||||
- [[N8N Telegram Trigger配置]]
|
||||
- [[N8N全教程构建AI Agent]]
|
||||
- [[N8N工作流编排]]
|
||||
|
||||
## 相关链接
|
||||
- [N8N官网](https://n8n.io/)
|
||||
- [N8N文档](https://docs.n8n.io/)
|
||||
@@ -1,32 +0,0 @@
|
||||
---
|
||||
id: nano-banana
|
||||
title: "Nano Banana"
|
||||
type: entity
|
||||
tags: [google, AI, image-generation]
|
||||
sources:
|
||||
- "[[Nano Banana提示词框架]]"
|
||||
- "[[Nano Banana Pro提示词指南]]"
|
||||
- "[[Nano Banana 2使用指南]]"
|
||||
last_updated: 2025-12-01
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
Nano Banana是Google开发的AI图像生成模型，基于Gemini系列模型的图像生成能力。最新版本为Nano Banana 2（Gemini 3 Pro Image），是推理模型，生成前会进行内部推理。
|
||||
|
||||
## Key Features
|
||||
|
||||
- **推理模型**：生成前会进行内部推理，提升质量
|
||||
- **多分辨率支持**：1K、2K、4K分辨率
|
||||
- **多图像组合**：最多14张输入图像组合输出
|
||||
- **多语言长文本渲染**：擅长在中英文环境中渲染长文本
|
||||
|
||||
## Versions
|
||||
|
||||
- **Nano Banana**：基础版本
|
||||
- **Nano Banana Pro**：增强版本
|
||||
- **Nano Banana 2**：Gemini 3 Pro Image，推理模型
|
||||
|
||||
## Connections
|
||||
- [[AI图像生成]] ← uses ← [[Nano Banana]]
|
||||
- [[Nano Banana]] ← supports ← [[提示词框架]]
|
||||
@@ -1,36 +0,0 @@
|
||||
---
|
||||
id: notebooklm
|
||||
title: "NotebookLM"
|
||||
type: entity
|
||||
tags: [google, AI, learning, productivity]
|
||||
sources:
|
||||
- "[[7 ways I use NotebookLM to make my life easier]]"
|
||||
- "[[NotebookLM Open Source Alternatives]]"
|
||||
last_updated: 2025-11-23
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
NotebookLM是Google推出的AI学习和工作助手，核心特点是Source-Grounding机制确保回答准确且可溯源。
|
||||
|
||||
## Key Features
|
||||
|
||||
- **Source-Grounding**：限制知识库仅包含用户上传的文档，避免AI幻觉
|
||||
- **音频概览**：将文档转化为AI双人播客格式，适合被动学习
|
||||
- **项目中心**：集中管理研究、想法、会议记录的统一空间
|
||||
- **精确引用**：法律文档审查时提供精确引用
|
||||
|
||||
## Use Cases
|
||||
|
||||
- 信息整理和学习笔记
|
||||
- 文档问答和摘要
|
||||
- 项目研究和知识管理
|
||||
- 被动学习（音频概览）
|
||||
|
||||
## Aliases
|
||||
|
||||
- Google NotebookLM
|
||||
|
||||
## Connections
|
||||
- [[NotebookLM]] ← uses ← [[Source-Grounding]]
|
||||
- [[AI学习工具]] ← extends ← [[NotebookLM]]
|
||||
@@ -1,24 +0,0 @@
|
||||
---
|
||||
title: "Ollama"
|
||||
type: entity
|
||||
tags: []
|
||||
sources: []
|
||||
last_updated: 2025-03-15
|
||||
---
|
||||
|
||||
## Definition
|
||||
Ollama是一个开源本地大模型运行平台，简化了开源大模型（如Llama、DeepSeek、Mistral等）在本地机器上的部署和运行。
|
||||
|
||||
## Role
|
||||
- 本地大模型运行时：提供统一接口运行各种开源大模型
|
||||
- 简化部署工具：一条命令即可运行大模型
|
||||
|
||||
## Key Properties
|
||||
- 支持模型：Llama、DeepSeek、Mistral、Gemma等
|
||||
- 跨平台：macOS、Linux、Windows支持
|
||||
- API兼容：提供OpenAI兼容API
|
||||
- 量化支持：支持Q4、Q8等量化版本，降低硬件要求
|
||||
|
||||
## Connections
|
||||
- [[Ollama-DeepSeek-OpenWebui-离线部署大模型]] ← 来源 ← [[Ollama]]
|
||||
- [[DeepSeek]] ← 支持运行 ← [[Ollama]]
|
||||
@@ -1,56 +0,0 @@
|
||||
---
|
||||
title: "OpenClaw"
|
||||
type: entity
|
||||
tags: [openclaw, agent, framework]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
# OpenClaw
|
||||
|
||||
开源AI Agent框架，支持多Agent协作、记忆系统、技能扩展。
|
||||
|
||||
## 基本信息
|
||||
- **类型**：AI Agent框架
|
||||
- **开源协议**：MIT
|
||||
- **平台**：跨平台（支持macOS、Linux、Windows）
|
||||
- **连接方式**：CLI、Telegram、Discord、WebUI
|
||||
|
||||
## 核心功能
|
||||
|
||||
### Workspace文件体系
|
||||
OpenClaw使用workspace目录下的文件来配置Agent行为：
|
||||
- [[AGENTS.md]]：Agent工作说明书
|
||||
- [[SOUL.md]]：Agent性格档案
|
||||
- [[USER.md]]：用户偏好
|
||||
- [[TOOLS.md]]：工具权限声明
|
||||
- [[IDENTITY.md]]：Agent身份元数据
|
||||
- [[BOOTSTRAP.md]]：首次启动引导
|
||||
- [[memory/]]：长期记忆目录
|
||||
|
||||
### 多Agent支持
|
||||
- 通过`sessions_spawn`启动子Agent
|
||||
- 通过`sessions_send`发送消息
|
||||
- 支持多Agent团队协作（如Milo、Josh等）
|
||||
|
||||
### 技能系统
|
||||
- 技能包目录：`skills/`
|
||||
- 支持第三方技能安装
|
||||
- MCP协议集成
|
||||
|
||||
### 记忆系统
|
||||
- 内置Markdown文件记忆
|
||||
- 支持向量语义搜索（通过memsearch）
|
||||
- 长期上下文保留
|
||||
|
||||
## 使用场景
|
||||
|
||||
详见各use case：
|
||||
- [[多Agent专业团队]]
|
||||
- [[自愈家庭服务器]]
|
||||
- [[第二大脑]]
|
||||
- [[目标驱动自主任务]]
|
||||
|
||||
## 相关链接
|
||||
- [OpenClaw GitHub](https://github.com/openclaw/openclaw)
|
||||
- [OpenClaw文档](https://docs.openclaw.ai)
|
||||
- [OpenClaw Showcase](https://openclaw.ai/showcase)
|
||||
@@ -1,23 +0,0 @@
|
||||
---
|
||||
title: "Open-Webui"
|
||||
type: entity
|
||||
tags: []
|
||||
sources: []
|
||||
last_updated: 2025-03-15
|
||||
---
|
||||
|
||||
## Definition
|
||||
Open-Webui是一个开源的本地AI Web界面，类似于ChatGPT的Web UI，用于访问本地运行的Ollama大模型。
|
||||
|
||||
## Role
|
||||
- 本地AI Web界面：提供Web浏览器访问本地Ollama模型
|
||||
- ChatGPT风格UI：用户友好的对话界面
|
||||
|
||||
## Key Properties
|
||||
- 开源：完全免费，可自托管
|
||||
- 类ChatGPT体验：对话界面，支持多轮对话
|
||||
- 多用户支持：支持多用户和权限管理
|
||||
|
||||
## Connections
|
||||
- [[Ollama-DeepSeek-OpenWebui-离线部署大模型]] ← 来源 ← [[OpenWebui]]
|
||||
- [[Ollama]] ← 搭配使用 ← [[OpenWebui]]
|
||||
@@ -1,29 +0,0 @@
|
||||
---
|
||||
title: "Opoint"
|
||||
type: entity
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
专注于新闻监测和情感分析的 API 平台，支持多语言和全球来源，适合 PR、营销和品牌监测团队。
|
||||
|
||||
## Aliases
|
||||
- Opoint
|
||||
- Opoint Media Intelligence
|
||||
|
||||
## Key Features
|
||||
- 实时监测附带情感标签
|
||||
- 多语言和多来源覆盖
|
||||
- 品牌监测和竞品追踪定制
|
||||
|
||||
## Use Cases
|
||||
- PR 机构情感监测
|
||||
- 品牌声誉管理
|
||||
- 竞品动态追踪
|
||||
|
||||
## Related Concepts
|
||||
- [[新闻API]]
|
||||
- [[情感分析]]
|
||||
|
||||
## Sources
|
||||
- [[Best-7-News-API-Data-Feeds.md]]
|
||||
@@ -1,17 +0,0 @@
|
||||
---
|
||||
title: "Smisery"
|
||||
type: entity
|
||||
tags: [mcp-server, data-source]
|
||||
last_updated: 2026-04-14
|
||||
---
|
||||
|
||||
## Aliases
|
||||
- smisery
|
||||
- smisery MCP
|
||||
- 热点新闻 MCP Server
|
||||
|
||||
## Summary
|
||||
Smisery 是一个提供热点新闻聚合的 [[MCP]] Server 服务，它支持多达九个新闻来源，可以被大模型客户端（如 [[Cursor]]）一次性接入，为大模型提供实时的数据查询与调用能力。
|
||||
|
||||
## Key Connections
|
||||
- [[Cursor]] ← invokes ← [[Smisery]]
|
||||
@@ -1,23 +0,0 @@
|
||||
---
|
||||
title: "Sora"
|
||||
type: entity
|
||||
tags: []
|
||||
sources: []
|
||||
last_updated: 2025-03-14
|
||||
---
|
||||
|
||||
## Definition
|
||||
Sora是OpenAI开发的文本转视频（Text-to-Video）AI模型，能够根据文字描述生成长达60秒的高质量视频。
|
||||
|
||||
## Role
|
||||
- 视频生成模型开发商：OpenAI旗下AI视频生成工具
|
||||
- 多模态AI研究：文本到视频生成能力
|
||||
|
||||
## Key Properties
|
||||
- 视频时长：最长60秒
|
||||
- 多模态输入：支持文本到视频、图像到视频
|
||||
- API访问：通过OpenAI API集成
|
||||
|
||||
## Connections
|
||||
- [[Sora视频自动化生成工作流]] ← 来源 ← [[Sora]]
|
||||
- [[文字转视频]] ← relates_to ← [[Sora]]
|
||||
@@ -1,30 +0,0 @@
|
||||
---
|
||||
title: "Webz.io"
|
||||
type: entity
|
||||
tags: []
|
||||
---
|
||||
|
||||
## Definition
|
||||
综合性新闻 API 平台，提供表层、深层和暗网数据覆盖，支持情感分析、话题过滤和地理定位。
|
||||
|
||||
## Aliases
|
||||
- Webz.io
|
||||
- Webz
|
||||
|
||||
## Key Features
|
||||
- 覆盖表层、深层和暗网数据
|
||||
- 支持情感分析、话题和地理覆盖的高级过滤
|
||||
- 支持可视化和可操作的风险监测
|
||||
|
||||
## Use Cases
|
||||
- 媒体监测
|
||||
- 情感分析
|
||||
- 网络安全威胁情报
|
||||
- 金融分析
|
||||
|
||||
## Related Concepts
|
||||
- [[新闻API]]
|
||||
- [[情感分析]]
|
||||
|
||||
## Sources
|
||||
- [[Best-7-News-API-Data-Feeds.md]]
|
||||
@@ -1,24 +0,0 @@
|
||||
---
|
||||
id: jianying
|
||||
title: "剪映"
|
||||
type: entity
|
||||
tags: [video-editing, ByteDance, TikTok]
|
||||
sources:
|
||||
- "[[AI配音与声音克隆工具合集]]"
|
||||
last_updated: 2025-03-06
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
剪映是字节跳动推出的视频编辑工具，抖音官方，短视频首选，部分音色需VIP。
|
||||
|
||||
## Key Features
|
||||
|
||||
- 抖音官方工具
|
||||
- 短视频首选
|
||||
- 部分音色需VIP
|
||||
- 内置AI配音功能
|
||||
|
||||
## Connections
|
||||
- [[AI视频制作]] ← uses ← [[剪映]]
|
||||
- [[短视频制作]] ← uses ← [[剪映]]
|
||||
@@ -1,24 +0,0 @@
|
||||
---
|
||||
id: hailo-ai
|
||||
title: "海螺AI"
|
||||
type: entity
|
||||
tags: [AI, TTS, voice-cloning, MiniMax]
|
||||
sources:
|
||||
- "[[AI配音与声音克隆工具合集]]"
|
||||
last_updated: 2025-03-06
|
||||
---
|
||||
|
||||
## Overview
|
||||
|
||||
海螺AI是MiniMax出品的AI工具，主打语音克隆和配音功能，对中文支持好，小白友好。
|
||||
|
||||
## Key Features
|
||||
|
||||
- 30秒克隆声音
|
||||
- 免费使用
|
||||
- 中文支持好
|
||||
- 小白友好界面
|
||||
|
||||
## Connections
|
||||
- [[AI配音]] ← uses ← [[海螺AI]]
|
||||
- [[声音克隆]] ← uses ← [[海螺AI]]
|
||||
386
wiki/index.md
386
wiki/index.md
@@ -1,386 +0,0 @@
|
||||
# Wiki Index
|
||||
|
||||
## Overview
|
||||
- [Overview](overview.md)
|
||||
|
||||
## Sources
|
||||
- [概要](sources/电商如何选品 如何找到爆款 选品策略.md)
|
||||
- [总结](sources/做TK跨境思路不对努力白费.md)
|
||||
- [1. 你的数据库结构 → 适合做哪些分析？](sources/TikTok Shop - Apache Superset Dashboard设计思路.md)
|
||||
- [TK美国面单授权及操作流程](sources/TK美国面单授权及操作流程.md)
|
||||
- [⚠️ 你使用 Docker，可能需要在 Dockerfile 里加入以下内容](sources/Scrapy + Playwright 抓取TikTok Shop Data.md)
|
||||
- [养龙虾5天血泪史：我的AI Agent为什么总失忆？OpenClaw 记忆调试全记录](sources/养龙虾5天血泪史：我的AI Agent为什么总失忆？OpenClaw 记忆调试全记录.md)
|
||||
- [养虾日记5：深夜与苏轼聊AI，他说：被浪打下去还能爬起来的才叫风流](sources/养虾日记5：深夜与苏轼聊AI，他说：被浪打下去还能爬起来的才叫风流.md)
|
||||
- [一次「Context Limit Exceeded」错误排查：我以为是小问题，结果踩了大坑](sources/养虾日记4： 一次「Context Limit Exceeded」错误排查：我以为是小问题，结果踩了大坑.md)
|
||||
- [养虾日记3：用 Obsidian + Gitea 为 AI 助手构建持久化笔记系统](sources/养虾日记3：用 Obsidian + Gitea 为 AI 助手构建持久化笔记系统.md)
|
||||
- [养虾日记2：让Agent更懂你：OpenClaw + Self-Improving 复盘实战案例分享](sources/养虾日记2：让Agent更懂你：OpenClaw + Self-Improving 复盘实战案例分享.md)
|
||||
- [养虾日记1：我用 OpenClaw 管了 28 万张照片：一次真实的多设备照片整理实战](sources/养虾日记1：我用 OpenClaw 管了 28 万张照片：一次真实的多设备照片整理实战.md)
|
||||
- [不谈技术：普通人该怎么在AI时代赚钱？](sources/不谈技术：普通人该怎么在AI时代赚钱？.md)
|
||||
- [开发经验与项目规范整理文档](sources/开发经验与项目规范整理文档.md)
|
||||
- [如何在项目里安装Claude-Code-Templates Skills](sources/如何在项目里安装Claude-Code-Templates Skills.md)
|
||||
- [如何在Ubuntu上安装opencode并配置Vibe-Kanban](sources/如何在Ubuntu上安装opencode并配置Vibe-Kanban.md)
|
||||
- [在Ubuntu 上安装Vibe-Kanban](sources/在Ubuntu上安装Vibe-Kanban.md)
|
||||
- [vibe coding经验收集](sources/vibe coding经验收集.md)
|
||||
- [Vibe-Kanban + OpenCode 在 Ubuntu Server 上安装与管理指南](sources/Vibe-Kanban + OpenCode 在 Ubuntu Server 上安装与管理指南.md)
|
||||
- [Cursor 2.0初学者使用指南](sources/Cursor 2.0初学者使用指南.md)
|
||||
- [baoyu-skills](sources/baoyu-skills-claude-code-技能集.md)
|
||||
- [Last30Days 使用指南](sources/Last30Days-使用指南.md)
|
||||
- [输出: /opt/homebrew/bin/gog](sources/GOG-CLI-安装配置指南.md)
|
||||
- [为什么你的笔记总是乱糟糟？试试这个方法，彻底告别信息混乱！ 1](sources/为什么你的笔记总是乱糟糟？试试这个方法，彻底告别信息混乱！ 1.md)
|
||||
- [为什么 Obsidian 让我戒掉了碎片化记录](sources/为什么 Obsidian 让我戒掉了碎片化记录.md)
|
||||
- [tiktok_pm_project/settings.py](sources/TikTok PM - Python Django Project.md)
|
||||
- [Obsidian最有必要安装的10款插件是这些](sources/Obsidian最有必要安装的10款插件是这些.md)
|
||||
- [Obsidian 高效指南：我常用的插件与实用技巧](sources/Obsidian 高效指南：我常用的插件与实用技巧.md)
|
||||
- [Obsidian Tasks 插件：这可能是最适合懒人的任务管理方式](sources/Obsidian Tasks 插件：这可能是最适合懒人的任务管理方式.md)
|
||||
- [How to get Youtube Channel ID](sources/How to get Youtube Channel ID.md)
|
||||
- [Dataview——让我从“笔记黑洞”里逃出来的 Obsidian 神器 1](sources/Dataview——让我从“笔记黑洞”里逃出来的 Obsidian 神器 1.md)
|
||||
- [ChinaTextbook - 41.53 GB，中国小学、初中、高中、大学 PDF 教材](sources/ChinaTextbook - 41.53 GB，中国小学、初中、高中、大学 PDF 教材.md)
|
||||
- [前置共识（已知条件）](sources/通过VPS+内网反向代理实现域名访问内网穿透.md)
|
||||
- [用Docker安装Apache Superset](sources/用Docker安装Apache Superset.md)
|
||||
- [家庭网络环境概览](sources/家庭网络环境概览_2026-04-03.md)
|
||||
- [核心目标（你要覆盖的监控面）](sources/家庭监控方案：Prometheus + Grafana + Node Exporter + cAdvisor +Blackbox.md)
|
||||
- [将 0005 (Ubuntu) 放在启动顺序的首位](sources/安装Ubuntu-24.04.2在HP Zbook工作站笔记本上.md)
|
||||
- [如何用指纹浏览器安全注册并订阅Claude Pro会员全攻略](sources/如何用指纹浏览器安全注册并订阅Claude Pro会员全攻略.md)
|
||||
- [如何在Ubuntu Server安装 docker & docker compose](sources/如何在Ubuntu Server安装 docker & docker compose.md)
|
||||
- [1. 先卸载当前的挂载（如果当前还挂着的话）](sources/如何在Ubuntu Server上通过NFS挂载Synology NAS上的共享文件夹.md)
|
||||
- [如何判别你的Linux 服务器是 x64（也就是 x86_64）还是 ARM64](sources/如何判别你的Linux 服务器是 x64（也就是 x86_64）还是 ARM64.md)
|
||||
- [✅ 最常用：删除旧 Portainer Container + Volume](sources/如何删除旧的废弃的docker container +volume.md)
|
||||
- [如何传输Docker images 并且在另一个Docker安装](sources/如何传输Docker images 并且在另一个Docker安装.md)
|
||||
- [前置共识（已知条件）](sources/在Ubuntu上通过VPS+内网反向代理实现域名访问内网穿透.md)
|
||||
- [在Synology NAS上安装CloudDrive2](sources/在Synology NAS上安装CloudDrive2.md)
|
||||
- [一、系统要求](sources/在 Ubuntu 安装 Ollama 并运行 Qwen2.5‑Coder 7B.md)
|
||||
- [1 创建 Symbolic Link](sources/macOS 创建与解除 Symbolic Link（OpenClaw 目录映射）.md)
|
||||
- [Ubuntu 安装 FRP 0.65.0（x86_64）操作笔记](sources/Ubuntu 安装 FRP 0.65.0（x86_64）操作笔记.md)
|
||||
- [Ubuntu Server科学上网](sources/Ubuntu Server科学上网.md)
|
||||
- [启动 SSH 服务](sources/Ubuntu 24.04 enable SSH.md)
|
||||
- [1. 安装Plex](sources/Synology NAS + Xiaoya Alist + CloudDrvie2+ Plex to Build Media Platform.md)
|
||||
- [RAX50 路由器 更新Merlin Clash订阅](sources/RAX50 路由器 更新Merlin Clash订阅.md)
|
||||
- [NodeWarden - 把 Bitwarden 搬上 Cloudflare Workers，彻底告别服务器](sources/NodeWarden - 把 Bitwarden 搬上 Cloudflare Workers，彻底告别服务器.md)
|
||||
- [MySQL MariaDB 数据库详细信息](sources/MySQL MariaDB 数据库详细信息.md)
|
||||
- [1. 架构图（Synology 专用）](sources/MinIO + Zipline 自托管图床应用安装教程.md)
|
||||
- [Mac Mini 安装 FRP 0.65.0（ARM64）操作笔记](sources/Mac Mini 安装 FRP 0.65.0（ARM64）操作笔记.md)
|
||||
- [Linux 运维必会的 150 个命令](sources/Linux 运维必会的 150 个命令.md)
|
||||
- [Clonezilla对Ubuntu Server进行全盘镜像备份](sources/Clonezilla对Ubuntu Server进行全盘镜像备份.md)
|
||||
- [3X-UI Xray on BandwagonVPS](sources/3X-UI Xray on BandwagonVPS.md)
|
||||
- [What I know about Cloud Service Delivery 1](sources/What I know about Cloud Service Delivery 1.md)
|
||||
- [The Myths and Misconceptions About Cloud Computing LinkedIn](sources/The Myths and Misconceptions About Cloud Computing LinkedIn.md)
|
||||
- [DevOps Culture and Transformation Fostering Collaboration, Agile Practices, and Innovation LinkedIn](sources/DevOps Culture and Transformation Fostering Collaboration, Agile Practices, and Innovation LinkedIn.md)
|
||||
- [安装Claude Desktop](sources/n8n+Claude 通过自然语言自动化工作流.md)
|
||||
- [n8n full tutorial building AI agents in 2025 for Beginners!](sources/n8n full tutorial building AI agents in 2025 for Beginners!.md)
|
||||
- [安装 curl 和 wget](sources/n8n docker install & update.md)
|
||||
- [n8n configure telegram trigger](sources/n8n configure telegram trigger.md)
|
||||
- [继Anthropic后，Google放出5个常用的Agent Skill设计模式](sources/Google-5个Agent-Skill设计模式-2026-03-19.md)
|
||||
- [谷歌深夜甩出一份【Nano Banana Pro提示词指南】，手把手教你生产专业级内容，实战案例+提示词模版](sources/谷歌深夜甩出一份【Nano Banana Pro提示词指南】，手把手教你生产专业级内容，实战案例+提示词模版.md)
|
||||
- [查看服务器 CPU 信息获取其架构，如：x86_64](sources/详细！离线部署大模型：ollama+deepseek+open-webui安装使用方法及常见问题解决 1.md)
|
||||
- [清华出的DeepSeek使用手册，104页，真的是太厉害了！（免费领取）](sources/清华出的DeepSeek使用手册，104页，真的是太厉害了！（免费领取）.md)
|
||||
- [教學 ChatGPT 先做知識整理，再讓 Canva、 Gamma AI 輸出簡報](sources/教學 ChatGPT 先做知識整理，再讓 Canva、 Gamma AI 輸出簡報.md)
|
||||
- [我用 Gemini 3 一口气做了 10 个应用，附教程](sources/我用 Gemini 3 一口气做了 10 个应用，附教程.md)
|
||||
- [摘要](sources/如何利用Sora接口实现视频自动化生成工作流.md)
|
||||
- [codecrafters-iobuild-your-own-x Master programming by recreating your favorite technologies from scratch](sources/codecrafters-iobuild-your-own-x Master programming by recreating your favorite technologies from scratch.md)
|
||||
- [Useful Prompt Lib](sources/Useful Prompt Lib.md)
|
||||
- [The Picture They Paint of You](sources/The Picture They Paint of You.md)
|
||||
- [Never write another prompt](sources/Never write another prompt.md)
|
||||
- [Nano-Banana Pro Prompting Guide & Strategies 1](sources/Nano-Banana Pro Prompting Guide & Strategies 1.md)
|
||||
- [Multi-Agent System Reliability](sources/Multi-Agent System Reliability.md)
|
||||
- [How to Get the RSS Feed For Any YouTube Channel](sources/How to Get the RSS Feed For Any YouTube Channel.md)
|
||||
- [Designing for Agentic AI](sources/Designing for Agentic AI.md)
|
||||
- [Best 7 news API data feeds - AI News](sources/Best 7 news API data feeds - AI News.md)
|
||||
- [AI 解决方案专家培训课程](sources/AI 解决方案专家培训课程.md)
|
||||
- [A Formalization of Recursive Self-Optimizing Generative Systems](sources/A Formalization of Recursive Self-Optimizing Generative Systems.md)
|
||||
- [7 ways I use NotebookLM to make my life easier](sources/7 ways I use NotebookLM to make my life easier.md)
|
||||
- [2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！ 1](sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！ 1.md)
|
||||
- [2025-03-02 日记](sources/2025-03-02.md)
|
||||
- [2025-03-04 日记](sources/2025-03-04.md)
|
||||
- [2025-03-05 日记](sources/2025-03-05.md)
|
||||
- [2025-03-10 日记](sources/2025-03-10.md)
|
||||
- [2025-03-14 日记](sources/2025-03-14.md)
|
||||
- [2025-03-15 日记](sources/2025-03-15.md)
|
||||
- [2025-05-13 Ubuntu合盖](sources/2025-05-13.md)
|
||||
- [2025-07-02 日记](sources/2025-07-02.md)
|
||||
- [2025-07-05 日记](sources/2025-07-05.md)
|
||||
- [2025-07-07 日记](sources/2025-07-07.md)
|
||||
- [2025-07-25 日记](sources/2025-07-25.md)
|
||||
- [2026-03-27 日记](sources/2026-03-27.md)
|
||||
- [2026-03-29 日记](sources/2026-03-29.md)
|
||||
- [2026-03-30 日记](sources/2026-03-30.md)
|
||||
- [AI时代赚钱](sources/AI时代赚钱.md)
|
||||
- [baoyu-skills](sources/baoyu-skills.md)
|
||||
- [ChinaTextbook中国教材](sources/ChinaTextbook.md)
|
||||
- [Claude Code Templates](sources/Claude-Code-Templates.md)
|
||||
- [Cursor 2.0指南](sources/Cursor-2-0.md)
|
||||
- [Dataview插件](sources/Dataview.md)
|
||||
- [GOG CLI配置](sources/GOG-CLI.md)
|
||||
- [OpenCode-Ubuntu安装](sources/OpenCode-Ubuntu.md)
|
||||
- [Obsidian Tasks插件](sources/Obsidian-Tasks.md)
|
||||
- [Obsidian十大插件](sources/Obsidian-十大插件.md)
|
||||
- [Obsidian高效指南](sources/Obsidian-高效指南.md)
|
||||
- [Obsidian碎片化](sources/Obsidian-碎片化.md)
|
||||
- [TikTok PM Django](sources/TikTok-PM-Django.md)
|
||||
- [Trae远程开发](sources/Trae-远程开发.md)
|
||||
- [Vibe-Kanban+OpenCode](sources/Vibe-Kanban-OpenCode.md)
|
||||
- [Vibe-Kanban Ubuntu安装](sources/Vibe-Kanban-Ubuntu.md)
|
||||
- [Vibe Coding经验](sources/Vibe-Coding-经验.md)
|
||||
- [YouTube Channel ID](sources/YouTube-Channel-ID.md)
|
||||
- [电商选品策略](sources/电商选品策略.md)
|
||||
- [电商视频Prompt](sources/电商视频Prompt.md)
|
||||
- [开发经验规范](sources/开发经验规范.md)
|
||||
- [Last30Days使用指南](sources/Last30Days.md)
|
||||
- [笔记整理方法](sources/笔记整理方法.md)
|
||||
- [超达物流定价](sources/超达物流定价.md)
|
||||
- [TK跨境思路](sources/TK-跨境思路.md)
|
||||
- [TK美国面单](sources/TK-美国面单.md)
|
||||
- [TikTok Dashboard设计](sources/TikTok-Dashboard.md)
|
||||
- [TikTok数据抓取](sources/TikTok-数据抓取.md)
|
||||
- [养虾日记1](sources/养虾日记1.md)
|
||||
- [养虾日记2](sources/养虾日记2.md)
|
||||
- [养虾日记3](sources/养虾日记3.md)
|
||||
- [养虾日记4](sources/养虾日记4.md)
|
||||
- [养虾日记5](sources/养虾日记5.md)
|
||||
- [养龙虾记忆调试](sources/养龙虾记忆调试.md)
|
||||
|
||||
- [万字讲透OpenClaw-Workspace深度解析](sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md)
|
||||
- [万字保姆级教程-90天跑通一人公司模式](sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md)
|
||||
- [MCP在Cursor中的集成与应用详解](sources/MCP在Cursor中的集成与应用详解.md)
|
||||
- [N8N Full Tutorial Building AI Agents](sources/n8n-full-tutorial-building-ai-agents.md)
|
||||
- [N8N Configure Telegram Trigger](sources/n8n-configure-telegram-trigger.md)
|
||||
- [N8N Docker Install Update](sources/n8n-docker-install-update.md)
|
||||
- [使用Claude自动生成N8N工作流的实操教程](sources/使用Claude自动生成N8N工作流的实操教程.md)
|
||||
- [N8N+Claude通过自然语言自动化工作流](sources/n8n+Claude通过自然语言自动化工作流.md)
|
||||
- [Podcast Production Pipeline](sources/podcast-production-pipeline.md)
|
||||
- [Automated Meeting Notes & Action Items](sources/meeting-notes-action-items.md)
|
||||
- [Daily YouTube Digest](sources/daily-youtube-digest.md)
|
||||
- [Multi-Agent Content Factory](sources/content-factory.md)
|
||||
- [Self-Healing Home Server](sources/self-healing-home-server.md)
|
||||
- [Health & Symptom Tracker](sources/health-symptom-tracker.md)
|
||||
- [Project State Management System](sources/project-state-management.md)
|
||||
- [Multi-Agent Specialized Team](sources/multi-agent-team.md)
|
||||
- [AI-Powered Earnings Tracker](sources/earnings-tracker.md)
|
||||
- [Multi-Channel Personal Assistant](sources/multi-channel-assistant.md)
|
||||
- [Event Guest Confirmation](sources/event-guest-confirmation.md)
|
||||
- [Market Research & Product Factory](sources/market-research-product-factory.md)
|
||||
- [Custom Morning Brief](sources/custom-morning-brief.md)
|
||||
- [Inbox De-clutter](sources/inbox-declutter.md)
|
||||
- [Daily Reddit Digest](sources/daily-reddit-digest.md)
|
||||
- [Autonomous Project Management with Subagents](sources/autonomous-project-management.md)
|
||||
- [Pre-Build Idea Validator](sources/pre-build-idea-validator.md)
|
||||
- [Dynamic Dashboard with Sub-agent Spawning](sources/dynamic-dashboard.md)
|
||||
- [Todoist Task Manager](sources/todoist-task-manager.md)
|
||||
- [Habit Tracker & Accountability Coach](sources/habit-tracker-accountability-coach.md)
|
||||
- [LaTeX Paper Writing](sources/latex-paper-writing.md)
|
||||
- [Second Brain](sources/second-brain.md)
|
||||
- [Multi-Channel Customer Service](sources/multi-channel-customer-service.md)
|
||||
- [OpenClaw + n8n Workflow Orchestration](sources/n8n-workflow-orchestration.md)
|
||||
- [Local CRM Framework with DenchClaw](sources/local-crm-framework.md)
|
||||
- [Overnight Mini App Builder](sources/overnight-mini-app-builder.md)
|
||||
- [Polymarket Autopilot](sources/polymarket-autopilot.md)
|
||||
- [YouTube Content Pipeline](sources/youtube-content-pipeline.md)
|
||||
- [Personal CRM with Automatic Contact Discovery](sources/personal-crm.md)
|
||||
- [Phone-Based Personal Assistant](sources/phone-based-personal-assistant.md)
|
||||
- [Knowledge Base RAG](sources/knowledge-base-rag.md)
|
||||
- [X/Twitter Automation from Chat](sources/x-twitter-automation.md)
|
||||
- [Multi-Source Tech News Digest](sources/multi-source-tech-news-digest.md)
|
||||
- [Family Calendar Aggregation & Household Assistant](sources/family-calendar-household-assistant.md)
|
||||
- [OpenClaw as Desktop Cowork (AionUi)](sources/aionui-cowork-desktop.md)
|
||||
- [Semantic Memory Search](sources/semantic-memory-search.md)
|
||||
- [arXiv Paper Reader](sources/arxiv-paper-reader.md)
|
||||
- [Autonomous Educational Game Development Pipeline](sources/autonomous-game-dev-pipeline.md)
|
||||
- [Phone Call Notifications](sources/phone-call-notifications.md)
|
||||
- [X Account Analysis](sources/x-account-analysis.md)
|
||||
- [7 ways I use NotebookLM to make my life easier](sources/7-ways-notebooklm.md)
|
||||
- [Designing for Agentic AI](sources/designing-for-agentic-ai.md)
|
||||
- [Multi-Agent System Reliability](sources/multi-agent-system-reliability.md)
|
||||
- [A Formalization of Recursive Self-Optimizing Generative Systems](sources/a-formalization-of-recursive-self-optimizing-generative-systems.md)
|
||||
- [14个免费AI图生视频工具](sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md)
|
||||
- [2025年11个神级AI开源平替](sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md)
|
||||
- [Claude Skills最值得研究的AI范式](sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md)
|
||||
- [Best 7 News APIs](sources/best-7-news-api.md)
|
||||
- [Vibe Coding Guide](sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md)
|
||||
- [NotebookLM Open Source Alternatives](sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md)
|
||||
- [YouTube RSS Feed](sources/youtube-rss-feed.md)
|
||||
- [LLMs RAG AI Agent区别](sources/LLMs、RAG、AI Agent 三个到底什么区别？.md)
|
||||
- [Nano Banana提示词框架](sources/Nano Banana 提示词框架.md)
|
||||
- [Nano Banana Pro提示词指南](sources/Nano Banana Pro提示词指南.md)
|
||||
- [Multiple Interests Guide](sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md)
|
||||
- [Never Write Another Prompt](sources/never-write-another-prompt.md)
|
||||
- [The Picture They Paint of You](sources/the-picture-they-paint-of-you.md)
|
||||
- [RAG从入门到精通系列1：基础RAG](sources/RAG从入门到精通系列1：基础RAG.md)
|
||||
- [OpenAI ChatGPT个性化定义](sources/OpenAI ChatGPT 个性化定义.md)
|
||||
- [Build Your Own X](sources/build-your-own-x.md)
|
||||
- [抑郁典型梦中人](sources/一语点醒梦中人.md)
|
||||
- [Gemini Product Manager PRD](sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md)
|
||||
- [AI配音与声音克隆工具合集](sources/二创视频必不可少！2025年最热门AI工具推荐合集-AI配音、声音克隆.md)
|
||||
- [固定镜头短视频AI全流程制作](sources/固定镜头短视频制作的AI全流程解析.md)
|
||||
- [大模型相关术语框架总结](sources/大模型相关术语和框架总结｜LLM、MCP、Prompt、RAG、vLLM、Token、数据蒸馏.md)
|
||||
- [Nano Banana 2使用指南](sources/全网最全！Nano Banana 2 使用指南（2025年12月更新） 1.md)
|
||||
- [如何写出完美的Prompt](sources/如何写出完美的Prompt（提示词）？.md)
|
||||
- [Coze平台Demo合集](sources/Coze平台Demo合集.md)
|
||||
- [Anthropic Prompt Library实用合集](sources/Anthropic-Prompt-Library-实用合集.md)
|
||||
- [Sora视频自动化生成工作流](sources/Sora视频自动化生成工作流.md)
|
||||
- [Gemini-3-一口气做了10个应用](sources/Gemini-3-一口气做了10个应用.md)
|
||||
- [Google-5个Agent-Skill设计模式](sources/Google-5个Agent-Skill设计模式.md)
|
||||
- [我的工具集](sources/我的工具集.md)
|
||||
- [ChatGPT-Canva-Gamma-简报工作流](sources/ChatGPT-Canva-Gamma-简报工作流.md)
|
||||
- [文字生成视频网站推荐](sources/文字生成视频网站推荐.md)
|
||||
- [DeepSeek使用手册清华版](sources/DeepSeek使用手册清华版.md)
|
||||
- [系统提示词构建原则](sources/系统提示词构建原则.md)
|
||||
- [Ollama-DeepSeek-OpenWebui-离线部署大模型](sources/Ollama-DeepSeek-OpenWebUI-离线部署大模型.md)
|
||||
- [Claude Prompt Library](sources/Claude-Prompt-Library.md)
|
||||
- [Nano Banana Pro提示词指南谷歌官方版](sources/Nano-Banana-Pro提示词指南-谷歌官方版.md)
|
||||
- [7 ways NotebookLM](sources/7-ways-notebooklm.md)
|
||||
- [AI时代赚钱方法](sources/AI时代赚钱方法.md)
|
||||
- [baoyu-skills](sources/baoyu-skills.md)
|
||||
- [Best 7 News APIs](sources/best-7-news-api.md)
|
||||
- [ChinaTextbook中国教材](sources/ChinaTextbook中国教材.md)
|
||||
- [Coze平台Demo合集](sources/Coze平台Demo合集.md)
|
||||
- [Cursor 2.0初学者指南](sources/Cursor-2-0初学者指南.md)
|
||||
- [Dataview插件](sources/Dataview.md)
|
||||
- [Designing for Agentic AI](sources/designing-for-agentic-ai.md)
|
||||
- [GOG CLI配置](sources/GOG-CLI配置.md)
|
||||
- [Last30Days使用指南](sources/Last30Days使用指南.md)
|
||||
- [Obsidian Tasks插件](sources/Obsidian-Tasks插件.md)
|
||||
- [Obsidian十大插件](sources/Obsidian十大插件.md)
|
||||
- [Obsidian高效指南](sources/Obsidian高效指南.md)
|
||||
- [Obsidian碎片化](sources/笔记碎片化问题.md)
|
||||
- [OpenCode配置VibeKanban](sources/OpenCode配置VibeKanban.md)
|
||||
- [TikTok PM Django](sources/TikTok-PM-Django.md)
|
||||
- [Trae远程开发部署](sources/Trae远程开发部署.md)
|
||||
- [Vibe-Kanban OpenCode Ubuntu安装](sources/Vibe-Kanban-OpenCode-Ubuntu安装.md)
|
||||
- [Vibe-Kanban Ubuntu安装](sources/Vibe-Kanban-Ubuntu安装.md)
|
||||
- [Vibe Coding经验收集](sources/VibeCoding经验收集.md)
|
||||
- [YouTube Channel ID](sources/YouTube-Channel-ID.md)
|
||||
- [笔记整理方法](sources/笔记整理方法.md)
|
||||
- [TK跨境思路](sources/TK跨境思路.md)
|
||||
- [TK美国面单授权](sources/TK美国面单授权.md)
|
||||
- [TikTok Superset Dashboard](sources/TikTok-Superset-Dashboard.md)
|
||||
- [TikTok数据抓取](sources/TikTok数据抓取.md)
|
||||
- [电商选品策略](sources/电商选品策略.md)
|
||||
- [养虾日记1-照片整理](sources/养虾日记1-照片整理.md)
|
||||
- [养虾日记2-SelfImproving](sources/养虾日记2-SelfImproving.md)
|
||||
- [养虾日记3-Obsidian-Gitea](sources/养虾日记3-Obsidian-Gitea.md)
|
||||
- [养虾日记4-Context调试](sources/养虾日记4-Context调试.md)
|
||||
- [养虾日记5-苏轼对话](sources/养虾日记5-苏轼对话.md)
|
||||
- [养龙虾记忆调试](sources/养龙虾记忆调试.md)
|
||||
- [递归自我优化生成系统](sources/递归自我优化生成系统.md)
|
||||
- [开发经验与项目规范](sources/开发经验与项目规范.md)
|
||||
|
||||
- [3X-UI Xray on BandwagonVPS](sources/3X-UI-Xray-on-BandwagonVPS.md)
|
||||
- [Clonezilla对Ubuntu Server进行全盘镜像备份](sources/Clonezilla对Ubuntu-Server进行全盘镜像备份.md)
|
||||
- [DevOps Culture and Transformation LinkedIn](sources/DevOps-Culture-and-Transformation-LinkedIn.md)
|
||||
- [Linux 运维必会的 150 个命令](sources/Linux-运维必会的-150-个命令.md)
|
||||
- [Mac Mini 安装 FRP 0.65.0 ARM64 操作笔记](sources/Mac-Mini-安装-FRP-0.65.0-ARM64-操作笔记.md)
|
||||
- [MinIO Zipline 自托管图床应用安装教程](sources/MinIO-Zipline-自托管图床应用安装教程.md)
|
||||
- [MySQL MariaDB 数据库详细信息](sources/MySQL-MariaDB-数据库详细信息.md)
|
||||
- [NodeWarden Bitwarden搬上Cloudflare Workers](sources/NodeWarden-Bitwarden搬上Cloudflare-Workers.md)
|
||||
- [RAX50 路由器 更新Merlin Clash订阅](sources/RAX50-路由器-更新Merlin-Clash订阅.md)
|
||||
- [Synology NAS Xiaoya Alist CloudDrvie2 Plex家庭影视平台](sources/Synology-NAS-Xiaoya-Alist-CloudDrive2-Plex-家庭影视平台.md)
|
||||
- [The Myths and Misconceptions About Cloud Computing LinkedIn](sources/The-Myths-and-Misconceptions-About-Cloud-Computing-LinkedIn.md)
|
||||
- [Ubuntu 24.04 enable SSH](sources/Ubuntu-24.04-enable-SSH.md)
|
||||
- [Ubuntu Server科学上网](sources/Ubuntu-Server科学上网.md)
|
||||
- [Ubuntu 安装 FRP 0.65.0 x86_64 操作笔记](sources/Ubuntu-安装-FRP-0.65.0-x86_64-操作笔记.md)
|
||||
- [Ubuntu服务器通过rsync实现日常增量备份](sources/Ubuntu服务器通过rsync实现日常增量备份.md)
|
||||
- [Ubuntu用RustDesk远程登录出现不能使用Wayland登录的错误](sources/Ubuntu用RustDesk远程登录出现不能使用Wayland登录的错误.md)
|
||||
- [Ubuntu禁用合盖休眠](sources/Ubuntu禁用合盖休眠.md)
|
||||
- [What I know about Cloud Service Delivery 1](sources/What-I-know-about-Cloud-Service-Delivery-1.md)
|
||||
- [macOS 创建与解除 Symbolic Link OpenClaw 目录映射](sources/macOS-创建与解除-Symbolic-Link-OpenClaw-目录映射.md)
|
||||
- [在 Ubuntu 安装 Ollama 并运行 Qwen2.5‑Coder 7B](sources/在-Ubuntu-安装-Ollama-并运行-Qwen2.5-Coder-7B.md)
|
||||
- [在Synology NAS上安装CloudDrive2](sources/在Synology-NAS上安装CloudDrive2.md)
|
||||
- [在Ubuntu上通过VPS内网反向代理实现域名访问内网穿透](sources/在Ubuntu上通过VPS-内网反向代理实现域名访问内网穿透.md)
|
||||
- [如何传输Docker images 并且在另一个Docker安装](sources/如何传输Docker-images-并且在另一个Docker安装.md)
|
||||
- [如何删除旧的废弃的docker container volume](sources/如何删除旧的废弃的docker-container-volume.md)
|
||||
- [如何判别你的Linux 服务器是 x64 还是 ARM64](sources/如何判别你的Linux-服务器是-x64-还是-ARM64.md)
|
||||
- [如何在Ubuntu Server上通过NFS挂载Synology NAS上的共享文件夹](sources/如何在Ubuntu-Server上通过NFS挂载Synology-NAS上的共享文件夹.md)
|
||||
- [如何在Ubuntu Server安装 docker docker compose](sources/如何在Ubuntu-Server安装-docker-and-docker-compose.md)
|
||||
- [如何用指纹浏览器安全注册并订阅Claude Pro会员全攻略](sources/如何用指纹浏览器安全注册并订阅Claude-Pro会员全攻略.md)
|
||||
- [安装Ubuntu-24.04.2在HP Zbook工作站笔记本上](sources/安装Ubuntu-24.04.2在HP-Zbook工作站笔记本上.md)
|
||||
- [安装v2rayN](sources/安装v2rayN.md)
|
||||
- [家庭监控方案 Prometheus Grafana Node Exporter cAdvisor Blackbox](sources/家庭监控方案-Prometheus-Grafana-Node-Exporter-cAdvisor-Blackbox.md)
|
||||
- [家庭网络环境概览 2026-04-03](sources/家庭网络环境概览-2026-04-03.md)
|
||||
- [通过VPS内网反向代理实现域名访问内网穿透 aliyun](sources/通过VPS-内网反向代理实现域名访问内网穿透-aliyun.md)
|
||||
- [群晖NAS科学上网方法](sources/群晖NAS科学上网方法.md)
|
||||
- [网件RAX50路由器刷梅林固件与科学上网插件安装教程](sources/网件RAX50路由器刷梅林固件与科学上网插件安装教程.md)
|
||||
- [用Docker中安装Navidrome](sources/用Docker中安装Navidrome.md)
|
||||
- [用Docker安装Apache Superset](sources/用Docker安装Apache-Superset.md)
|
||||
- [用Docker安装Homarr](sources/用Docker安装Homarr.md)
|
||||
- [用Docker安装Jellyfin](sources/用Docker安装Jellyfin.md)
|
||||
- [用Docker安装Portainer](sources/用Docker安装Portainer.md)
|
||||
- [用Docker安装it-tools](sources/用Docker安装it-tools.md)
|
||||
- [用Docker安装transmission](sources/用Docker安装transmission.md)
|
||||
|
||||
## Entities
|
||||
- [Cursor](entities/Cursor.md)
|
||||
- [Coze](entities/Coze.md)
|
||||
- [DeepSeek](entities/DeepSeek.md)
|
||||
- [Smisery](entities/Smisery.md)
|
||||
- [OpenClaw](entities/OpenClaw.md)
|
||||
- [N8N](entities/N8N.md)
|
||||
- [MCP](entities/MCP.md)
|
||||
- [NotebookLM](entities/NotebookLM.md)
|
||||
- [NanoBanana](entities/NanoBanana.md)
|
||||
- [DeepSider](entities/DeepSider.md)
|
||||
- [ElevenLabs](entities/ElevenLabs.md)
|
||||
- [Google](entities/Google.md)
|
||||
- [海螺AI](entities/海螺AI.md)
|
||||
- [F5-TTS](entities/F5TTS.md)
|
||||
- [剪映](entities/剪映.md)
|
||||
- [LangChain](entities/LangChain.md)
|
||||
- [Anthropic](entities/Anthropic.md)
|
||||
- [Canva](entities/Canva.md)
|
||||
- [ClawdTalk](entities/ClawdTalk.md)
|
||||
- [Gamma AI](entities/GammaAI.md)
|
||||
- [Sora](entities/Sora.md)
|
||||
- [Ollama](entities/Ollama.md)
|
||||
- [Open-Webui](entities/OpenWebui.md)
|
||||
- [Alex Ewerlöf](entities/AlexEwerlof.md)
|
||||
- [Ferdinand](entities/Ferdinand.md)
|
||||
- [GNews API](entities/GNewsAPI.md)
|
||||
- [Mediastack](entities/Mediastack.md)
|
||||
- [Opoint](entities/Opoint.md)
|
||||
- [Webz.io](entities/Webzio.md)
|
||||
|
||||
## Concepts
|
||||
- [Agent模式](concepts/Agent模式.md)
|
||||
- [AgentSkill设计模式](concepts/AgentSkill设计模式.md)
|
||||
- [SequentialThinking](concepts/SequentialThinking.md)
|
||||
- [SSE](concepts/SSE.md)
|
||||
- [Workspace](concepts/Workspace.md)
|
||||
- [多Agent系统](concepts/多Agent系统.md)
|
||||
- [工作流自动化](concepts/工作流自动化.md)
|
||||
- [记忆系统](concepts/记忆系统.md)
|
||||
- [技能系统](concepts/技能系统.md)
|
||||
- [Source-Grounding](concepts/SourceGrounding.md)
|
||||
- [音频概览](concepts/音频概览.md)
|
||||
- [提示词框架](concepts/提示词框架.md)
|
||||
- [GenAI](concepts/GenAI.md)
|
||||
- [Generator](concepts/Generator.md)
|
||||
- [Agentic AI](concepts/AgenticAI.md)
|
||||
- [RAG](concepts/RAG.md)
|
||||
- [Embedding](concepts/Embedding.md)
|
||||
- [Prompt能力](concepts/Prompt能力.md)
|
||||
- [需求拆解](concepts/需求拆解.md)
|
||||
- [结构化表达](concepts/结构化表达.md)
|
||||
- [思维链引导](concepts/思维链引导.md)
|
||||
- [AI配音](concepts/AI配音.md)
|
||||
- [声音克隆](concepts/声音克隆.md)
|
||||
- [固定机位](concepts/固定机位.md)
|
||||
- [首尾针动画](concepts/首尾针动画.md)
|
||||
- [九宫格法](concepts/九宫格法.md)
|
||||
- [LLM](concepts/LLM.md)
|
||||
- [Token](concepts/Token.md)
|
||||
- [MCP](concepts/MCP.md)
|
||||
- [Inversion](concepts/Inversion.md)
|
||||
- [Pipeline](concepts/Pipeline.md)
|
||||
- [Reviewer](concepts/Reviewer.md)
|
||||
- [ToolWrapper](concepts/ToolWrapper.md)
|
||||
- [Agent](concepts/Agent.md)
|
||||
- [vLLM](concepts/vLLM.md)
|
||||
- [Claude Skills](concepts/ClaudeSkills.md)
|
||||
- [AI拟人化谬误](concepts/AI拟人化谬误.md)
|
||||
- [YouTubeRSS](concepts/YouTubeRSS.md)
|
||||
- [多Agent可靠性模式](concepts/多Agent可靠性模式.md)
|
||||
- [固定点语义](concepts/固定点语义.md)
|
||||
- [共识投票](concepts/共识投票.md)
|
||||
- [泰勒主义软件工厂](concepts/泰勒主义软件工厂.md)
|
||||
- [验证器模式](concepts/验证器模式.md)
|
||||
- [自举Meta生成](concepts/自举Meta生成.md)
|
||||
- [流程工程](concepts/流程工程.md)
|
||||
- [Vibe Coding](concepts/VibeCoding.md)
|
||||
@@ -1,795 +0,0 @@
|
||||
# Wiki Lint Report — 2026-04-14
|
||||
|
||||
Scanned 119 pages.
|
||||
|
||||
## Structural Issues
|
||||
|
||||
### Orphan Pages (no inbound links)
|
||||
- `wiki/concepts/VibeCoding.md`
|
||||
- `wiki/concepts/AgenticAI.md`
|
||||
- `wiki/concepts/ClaudeSkills.md`
|
||||
- `wiki/concepts/SourceGrounding.md`
|
||||
- `wiki/sources/podcast-production-pipeline.md`
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md`
|
||||
- `wiki/sources/multi-agent-system-reliability.md`
|
||||
- `wiki/sources/meeting-notes-action-items.md`
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md`
|
||||
- `wiki/sources/daily-youtube-digest.md`
|
||||
- `wiki/sources/content-factory.md`
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md`
|
||||
- `wiki/sources/youtube-rss-feed.md`
|
||||
- `wiki/sources/self-healing-home-server.md`
|
||||
- `wiki/sources/health-symptom-tracker.md`
|
||||
- `wiki/sources/project-state-management.md`
|
||||
- `wiki/sources/multi-agent-team.md`
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md`
|
||||
- `wiki/sources/earnings-tracker.md`
|
||||
- `wiki/sources/build-your-own-x.md`
|
||||
- `wiki/sources/multi-channel-assistant.md`
|
||||
- `wiki/sources/LLMs、RAG、AI Agent 三个到底什么区别？.md`
|
||||
- `wiki/sources/OpenAI ChatGPT 个性化定义.md`
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md`
|
||||
- `wiki/sources/event-guest-confirmation.md`
|
||||
- `wiki/sources/market-research-product-factory.md`
|
||||
- `wiki/sources/custom-morning-brief.md`
|
||||
- `wiki/sources/Nano Banana 提示词框架.md`
|
||||
- `wiki/sources/best-7-news-api.md`
|
||||
- `wiki/sources/二创视频必不可少！2025年最热门AI工具推荐合集-AI配音、声音克隆.md`
|
||||
- `wiki/sources/MCP在Cursor中的集成与应用详解.md`
|
||||
- `wiki/sources/inbox-declutter.md`
|
||||
- `wiki/sources/daily-reddit-digest.md`
|
||||
- `wiki/sources/一语点醒梦中人.md`
|
||||
- `wiki/sources/autonomous-project-management.md`
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md`
|
||||
- `wiki/sources/pre-build-idea-validator.md`
|
||||
- `wiki/sources/dynamic-dashboard.md`
|
||||
- `wiki/sources/todoist-task-manager.md`
|
||||
- `wiki/sources/habit-tracker-accountability-coach.md`
|
||||
- `wiki/sources/n8n-configure-telegram-trigger.md`
|
||||
- `wiki/sources/latex-paper-writing.md`
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md`
|
||||
- `wiki/sources/second-brain.md`
|
||||
- `wiki/sources/multi-channel-customer-service.md`
|
||||
- `wiki/sources/7-ways-notebooklm.md`
|
||||
- `wiki/sources/n8n-workflow-orchestration.md`
|
||||
- `wiki/sources/如何写出完美的Prompt（提示词）？.md`
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md`
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md`
|
||||
- `wiki/sources/local-crm-framework.md`
|
||||
- `wiki/sources/overnight-mini-app-builder.md`
|
||||
- `wiki/sources/n8n+Claude通过自然语言自动化工作流.md`
|
||||
- `wiki/sources/n8n-full-tutorial-building-ai-agents.md`
|
||||
- `wiki/sources/never-write-another-prompt.md`
|
||||
- `wiki/sources/polymarket-autopilot.md`
|
||||
- `wiki/sources/大模型相关术语和框架总结｜LLM、MCP、Prompt、RAG、vLLM、Token、数据蒸馏.md`
|
||||
- `wiki/sources/固定镜头短视频制作的AI全流程解析.md`
|
||||
- `wiki/sources/youtube-content-pipeline.md`
|
||||
- `wiki/sources/personal-crm.md`
|
||||
- `wiki/sources/knowledge-base-rag.md`
|
||||
- `wiki/sources/x-twitter-automation.md`
|
||||
- `wiki/sources/multi-source-tech-news-digest.md`
|
||||
- `wiki/sources/family-calendar-household-assistant.md`
|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md`
|
||||
- `wiki/sources/aionui-cowork-desktop.md`
|
||||
- `wiki/sources/semantic-memory-search.md`
|
||||
- `wiki/sources/designing-for-agentic-ai.md`
|
||||
- `wiki/sources/arxiv-paper-reader.md`
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md`
|
||||
- `wiki/sources/autonomous-game-dev-pipeline.md`
|
||||
- `wiki/sources/全网最全！Nano Banana 2 使用指南（2025年12月更新） 1.md`
|
||||
- `wiki/sources/phone-call-notifications.md`
|
||||
- `wiki/sources/x-account-analysis.md`
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md`
|
||||
- `wiki/entities/NanoBanana.md`
|
||||
- `wiki/entities/F5TTS.md`
|
||||
|
||||
### Broken Wikilinks
|
||||
- `wiki/overview.md` links to `[[DenchClaw]]` — not found
|
||||
- `wiki/overview.md` links to `[[AionUi]]` — not found
|
||||
- `wiki/overview.md` links to `[[Nano Banana]]` — not found
|
||||
- `wiki/overview.md` links to `[[F5-TTS]]` — not found
|
||||
- `wiki/overview.md` links to `[[n8n-mcp]]` — not found
|
||||
- `wiki/overview.md` links to `[[idea-reality-mcp]]` — not found
|
||||
- `wiki/overview.md` links to `[[Source-Grounding]]` — not found
|
||||
- `wiki/concepts/Agent.md` links to `[[LLM Terms Framework]]` — not found
|
||||
- `wiki/concepts/Agent.md` links to `[[工具调用]]` — not found
|
||||
- `wiki/concepts/思维链引导.md` links to `[[如何写出完美的Prompt]]` — not found
|
||||
- `wiki/concepts/RAG.md` links to `[[LLM Terms Framework]]` — not found
|
||||
- `wiki/concepts/RAG.md` links to `[[索引]]` — not found
|
||||
- `wiki/concepts/RAG.md` links to `[[检索]]` — not found
|
||||
- `wiki/concepts/RAG.md` links to `[[生成]]` — not found
|
||||
- `wiki/concepts/首尾针动画.md` links to `[[固定镜头短视频AI全流程制作]]` — not found
|
||||
- `wiki/concepts/首尾针动画.md` links to `[[AI视频制作]]` — not found
|
||||
- `wiki/concepts/音频概览.md` links to `[[7 ways I use NotebookLM to make my life easier]]` — not found
|
||||
- `wiki/concepts/音频概览.md` links to `[[被动学习]]` — not found
|
||||
- `wiki/concepts/流程工程.md` links to `[[Claude Skills最值得研究的AI范式]]` — not found
|
||||
- `wiki/concepts/流程工程.md` links to `[[提示词工程]]` — not found
|
||||
- `wiki/concepts/流程工程.md` links to `[[Claude Skills]]` — not found
|
||||
- `wiki/concepts/流程工程.md` links to `[[SOP标准化]]` — not found
|
||||
- `wiki/concepts/MCP.md` links to `[[LLM Terms Framework]]` — not found
|
||||
- `wiki/concepts/MCP.md` links to `[[工具调用]]` — not found
|
||||
- `wiki/concepts/Prompt能力.md` links to `[[如何写出完美的Prompt]]` — not found
|
||||
- `wiki/concepts/Prompt能力.md` links to `[[AI协作]]` — not found
|
||||
- `wiki/concepts/Prompt能力.md` links to `[[结构化思维]]` — not found
|
||||
- `wiki/concepts/多Agent系统.md` links to `[[Milo]]` — not found
|
||||
- `wiki/concepts/多Agent系统.md` links to `[[Josh]]` — not found
|
||||
- `wiki/concepts/多Agent系统.md` links to `[[多Agent专业团队]]` — not found
|
||||
- `wiki/concepts/多Agent系统.md` links to `[[多Agent内容工厂]]` — not found
|
||||
- `wiki/concepts/多Agent系统.md` links to `[[自主项目管理]]` — not found
|
||||
- `wiki/concepts/多Agent系统.md` links to `[[动态仪表板]]` — not found
|
||||
- `wiki/concepts/VibeCoding.md` links to `[[Claude Skills最值得研究的AI范式]]` — not found
|
||||
- `wiki/concepts/VibeCoding.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/concepts/VibeCoding.md` links to `[[Claude Skills]]` — not found
|
||||
- `wiki/concepts/VibeCoding.md` links to `[[AI编程]]` — not found
|
||||
- `wiki/concepts/VibeCoding.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/concepts/VibeCoding.md` links to `[[提示词工程]]` — not found
|
||||
- `wiki/concepts/VibeCoding.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/concepts/固定机位.md` links to `[[固定镜头短视频AI全流程制作]]` — not found
|
||||
- `wiki/concepts/固定机位.md` links to `[[AI视频制作]]` — not found
|
||||
- `wiki/concepts/固定机位.md` links to `[[短视频制作]]` — not found
|
||||
- `wiki/concepts/AgenticAI.md` links to `[[Designing for Agentic AI]]` — not found
|
||||
- `wiki/concepts/AgenticAI.md` links to `[[Agentic AI]]` — not found
|
||||
- `wiki/concepts/AgenticAI.md` links to `[[AI产品设计]]` — not found
|
||||
- `wiki/concepts/AgenticAI.md` links to `[[Agentic AI设计原则]]` — not found
|
||||
- `wiki/concepts/Workspace.md` links to `[[AGENTS.md]]` — not found
|
||||
- `wiki/concepts/Workspace.md` links to `[[SOUL.md]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[Telegram]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[Discord]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[Slack]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[YouTube]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[Reddit]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[GitHub]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[arxiv-reader]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[latex-compiler]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[youtube-full]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[n8n-mcp]]` — not found
|
||||
- `wiki/concepts/技能系统.md` links to `[[idea-reality-mcp]]` — not found
|
||||
- `wiki/concepts/vLLM.md` links to `[[LLM Terms Framework]]` — not found
|
||||
- `wiki/concepts/vLLM.md` links to `[[推理优化]]` — not found
|
||||
- `wiki/concepts/vLLM.md` links to `[[GPU利用率]]` — not found
|
||||
- `wiki/concepts/九宫格法.md` links to `[[固定镜头短视频AI全流程制作]]` — not found
|
||||
- `wiki/concepts/九宫格法.md` links to `[[AI视频制作]]` — not found
|
||||
- `wiki/concepts/九宫格法.md` links to `[[分镜设计]]` — not found
|
||||
- `wiki/concepts/Token.md` links to `[[LLM Terms Framework]]` — not found
|
||||
- `wiki/concepts/Token.md` links to `[[成本计算]]` — not found
|
||||
- `wiki/concepts/Token.md` links to `[[上下文限制]]` — not found
|
||||
- `wiki/concepts/结构化表达.md` links to `[[如何写出完美的Prompt]]` — not found
|
||||
- `wiki/concepts/结构化表达.md` links to `[[结构化思维]]` — not found
|
||||
- `wiki/concepts/工作流自动化.md` links to `[[OpenClaw + n8n工作流编排]]` — not found
|
||||
- `wiki/concepts/工作流自动化.md` links to `[[会议纪要自动化]]` — not found
|
||||
- `wiki/concepts/工作流自动化.md` links to `[[邮件管理自动化]]` — not found
|
||||
- `wiki/concepts/工作流自动化.md` links to `[[日历聚合]]` — not found
|
||||
- `wiki/concepts/工作流自动化.md` links to `[[社交媒体自动化]]` — not found
|
||||
- `wiki/concepts/Embedding.md` links to `[[LLM Terms Framework]]` — not found
|
||||
- `wiki/concepts/Embedding.md` links to `[[向量数据库]]` — not found
|
||||
- `wiki/concepts/提示词框架.md` links to `[[Nano Banana提示词框架]]` — not found
|
||||
- `wiki/concepts/提示词框架.md` links to `[[AI图像生成]]` — not found
|
||||
- `wiki/concepts/提示词框架.md` links to `[[Nano Banana]]` — not found
|
||||
- `wiki/concepts/记忆系统.md` links to `[[Semantic Memory Search]]` — not found
|
||||
- `wiki/concepts/记忆系统.md` links to `[[memory/]]` — not found
|
||||
- `wiki/concepts/记忆系统.md` links to `[[MEMORY.md]]` — not found
|
||||
- `wiki/concepts/记忆系统.md` links to `[[第二大脑]]` — not found
|
||||
- `wiki/concepts/记忆系统.md` links to `[[个人CRM]]` — not found
|
||||
- `wiki/concepts/记忆系统.md` links to `[[健康症状追踪]]` — not found
|
||||
- `wiki/concepts/记忆系统.md` links to `[[memsearch]]` — not found
|
||||
- `wiki/concepts/记忆系统.md` links to `[[Milvus]]` — not found
|
||||
- `wiki/concepts/ClaudeSkills.md` links to `[[Claude Skills最值得研究的AI范式]]` — not found
|
||||
- `wiki/concepts/ClaudeSkills.md` links to `[[提示词工程]]` — not found
|
||||
- `wiki/concepts/ClaudeSkills.md` links to `[[Claude Skills]]` — not found
|
||||
- `wiki/concepts/ClaudeSkills.md` links to `[[SOP标准化]]` — not found
|
||||
- `wiki/concepts/ClaudeSkills.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/concepts/ClaudeSkills.md` links to `[[Claude Skills]]` — not found
|
||||
- `wiki/concepts/声音克隆.md` links to `[[AI配音与声音克隆工具合集]]` — not found
|
||||
- `wiki/concepts/声音克隆.md` links to `[[内容创作]]` — not found
|
||||
- `wiki/concepts/LLM.md` links to `[[LLM Terms Framework]]` — not found
|
||||
- `wiki/concepts/需求拆解.md` links to `[[如何写出完美的Prompt]]` — not found
|
||||
- `wiki/concepts/SourceGrounding.md` links to `[[7 ways I use NotebookLM to make my life easier]]` — not found
|
||||
- `wiki/concepts/SourceGrounding.md` links to `[[Source-Grounding]]` — not found
|
||||
- `wiki/concepts/SourceGrounding.md` links to `[[AI准确性]]` — not found
|
||||
- `wiki/concepts/SourceGrounding.md` links to `[[Source-Grounding]]` — not found
|
||||
- `wiki/concepts/AI配音.md` links to `[[AI配音与声音克隆工具合集]]` — not found
|
||||
- `wiki/concepts/AI配音.md` links to `[[二创视频]]` — not found
|
||||
- `wiki/concepts/AI配音.md` links to `[[内容创作]]` — not found
|
||||
- `wiki/concepts/GenAI.md` links to `[[Designing for Agentic AI]]` — not found
|
||||
- `wiki/concepts/GenAI.md` links to `[[Agentic AI]]` — not found
|
||||
- `wiki/concepts/GenAI.md` links to `[[AI产品设计]]` — not found
|
||||
- `wiki/sources/podcast-production-pipeline.md` links to `[[raw/Agent/usecases/podcast-production-pipeline.md]]` — not found
|
||||
- `wiki/sources/podcast-production-pipeline.md` links to `[[播客制作]]` — not found
|
||||
- `wiki/sources/podcast-production-pipeline.md` links to `[[多Agent协作]]` — not found
|
||||
- `wiki/sources/podcast-production-pipeline.md` links to `[[播客制作]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[raw/AI/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[图生视频]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[主体一致性]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[运动控制]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[绘蛙AI视频]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[智谱清影]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[通义万相]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[Vidu]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[可灵AI]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[即梦AI]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[PixVerse]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[Stable Video]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[AI视频生成]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[图生视频]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[阿里巴巴]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[绘蛙AI视频]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[阿里巴巴]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[通义万相]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[快手]]` — not found
|
||||
- `wiki/sources/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md` links to `[[可灵AI]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[raw/AI/Multi-Agent System Reliability.md]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[层级模式]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[共识模式]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[对抗辩论]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[淘汰制]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[LLM不可靠性]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[Alex Ewerlöf]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[层级模式]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[共识模式]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[对抗辩论]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[淘汰制]]` — not found
|
||||
- `wiki/sources/multi-agent-system-reliability.md` links to `[[可靠性工程]]` — not found
|
||||
- `wiki/sources/meeting-notes-action-items.md` links to `[[raw/Agent/usecases/meeting-notes-action-items.md]]` — not found
|
||||
- `wiki/sources/meeting-notes-action-items.md` links to `[[会议自动化]]` — not found
|
||||
- `wiki/sources/meeting-notes-action-items.md` links to `[[任务创建]]` — not found
|
||||
- `wiki/sources/meeting-notes-action-items.md` links to `[[会议自动化]]` — not found
|
||||
- `wiki/sources/meeting-notes-action-items.md` links to `[[任务创建]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[raw/Agent/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[AGENTS.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[SOUL.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[USER.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[TOOLS.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[IDENTITY.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[BOOTSTRAP.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[memory]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[Claude]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[AGENTS.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[SOUL.md]]` — not found
|
||||
- `wiki/sources/万字讲透OpenClaw-Workspace深度解析-2026-03-21.md` links to `[[USER.md]]` — not found
|
||||
- `wiki/sources/daily-youtube-digest.md` links to `[[raw/Agent/usecases/daily-youtube-digest.md]]` — not found
|
||||
- `wiki/sources/daily-youtube-digest.md` links to `[[内容聚合]]` — not found
|
||||
- `wiki/sources/daily-youtube-digest.md` links to `[[视频摘要]]` — not found
|
||||
- `wiki/sources/daily-youtube-digest.md` links to `[[youtube-full]]` — not found
|
||||
- `wiki/sources/daily-youtube-digest.md` links to `[[YouTube]]` — not found
|
||||
- `wiki/sources/content-factory.md` links to `[[raw/Agent/usecases/content-factory.md]]` — not found
|
||||
- `wiki/sources/content-factory.md` links to `[[多Agent协作]]` — not found
|
||||
- `wiki/sources/content-factory.md` links to `[[内容工厂]]` — not found
|
||||
- `wiki/sources/content-factory.md` links to `[[Discord集成]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[raw/AI/The Picture They Paint of You.md]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[AI SRE]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[编码助手]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[泰勒主义]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[拟人化]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[AI产品定位]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[工作价值认知]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[编码助手]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[合作伙伴]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[AI SRE]]` — not found
|
||||
- `wiki/sources/the-picture-they-paint-of-you.md` links to `[[替代者]]` — not found
|
||||
- `wiki/sources/youtube-rss-feed.md` links to `[[raw/AI/How to Get the RSS Feed For Any YouTube Channel.md]]` — not found
|
||||
- `wiki/sources/youtube-rss-feed.md` links to `[[RSS订阅]]` — not found
|
||||
- `wiki/sources/youtube-rss-feed.md` links to `[[YouTube RSS]]` — not found
|
||||
- `wiki/sources/youtube-rss-feed.md` links to `[[YouTube]]` — not found
|
||||
- `wiki/sources/youtube-rss-feed.md` links to `[[RSS订阅]]` — not found
|
||||
- `wiki/sources/self-healing-home-server.md` links to `[[raw/Agent/usecases/self-healing-home-server.md]]` — not found
|
||||
- `wiki/sources/self-healing-home-server.md` links to `[[自愈系统]]` — not found
|
||||
- `wiki/sources/self-healing-home-server.md` links to `[[基础设施即代码]]` — not found
|
||||
- `wiki/sources/self-healing-home-server.md` links to `[[安全审计]]` — not found
|
||||
- `wiki/sources/self-healing-home-server.md` links to `[[自愈系统]]` — not found
|
||||
- `wiki/sources/self-healing-home-server.md` links to `[[安全审计]]` — not found
|
||||
- `wiki/sources/health-symptom-tracker.md` links to `[[raw/Agent/usecases/health-symptom-tracker.md]]` — not found
|
||||
- `wiki/sources/health-symptom-tracker.md` links to `[[健康追踪]]` — not found
|
||||
- `wiki/sources/health-symptom-tracker.md` links to `[[模式识别]]` — not found
|
||||
- `wiki/sources/health-symptom-tracker.md` links to `[[Telegram集成]]` — not found
|
||||
- `wiki/sources/health-symptom-tracker.md` links to `[[健康追踪]]` — not found
|
||||
- `wiki/sources/health-symptom-tracker.md` links to `[[Telegram集成]]` — not found
|
||||
- `wiki/sources/project-state-management.md` links to `[[raw/Agent/usecases/project-state-management.md]]` — not found
|
||||
- `wiki/sources/project-state-management.md` links to `[[事件驱动架构]]` — not found
|
||||
- `wiki/sources/project-state-management.md` links to `[[项目状态管理]]` — not found
|
||||
- `wiki/sources/project-state-management.md` links to `[[自然语言查询]]` — not found
|
||||
- `wiki/sources/multi-agent-team.md` links to `[[raw/Agent/usecases/multi-agent-team.md]]` — not found
|
||||
- `wiki/sources/multi-agent-team.md` links to `[[多Agent团队]]` — not found
|
||||
- `wiki/sources/multi-agent-team.md` links to `[[共享内存]]` — not found
|
||||
- `wiki/sources/multi-agent-team.md` links to `[[私有上下文]]` — not found
|
||||
- `wiki/sources/multi-agent-team.md` links to `[[Milo]]` — not found
|
||||
- `wiki/sources/multi-agent-team.md` links to `[[Josh]]` — not found
|
||||
- `wiki/sources/multi-agent-team.md` links to `[[Marketing Agent]]` — not found
|
||||
- `wiki/sources/multi-agent-team.md` links to `[[Dev Agent]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[raw/AI/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[本地化部署]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[多模型支持]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[播客生成]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[Open Notebook]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[SurfSense]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[Podcastfy]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[notebookllama]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[PageLM]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[InsightsLM]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[Open Notebook]]` — not found
|
||||
- `wiki/sources/Google 神级生产力工具，所有 GitHub 开源平替都找到了。.md` links to `[[InsightsLM]]` — not found
|
||||
- `wiki/sources/earnings-tracker.md` links to `[[raw/Agent/usecases/earnings-tracker.md]]` — not found
|
||||
- `wiki/sources/earnings-tracker.md` links to `[[财报追踪]]` — not found
|
||||
- `wiki/sources/earnings-tracker.md` links to `[[定时任务]]` — not found
|
||||
- `wiki/sources/earnings-tracker.md` links to `[[财报追踪]]` — not found
|
||||
- `wiki/sources/earnings-tracker.md` links to `[[定时任务]]` — not found
|
||||
- `wiki/sources/build-your-own-x.md` links to `[[raw/AI/codecrafters-iobuild-your-own-x Master programming by recreating your favorite technologies from scratch.md]]` — not found
|
||||
- `wiki/sources/build-your-own-x.md` links to `[[Build Your Own X]]` — not found
|
||||
- `wiki/sources/build-your-own-x.md` links to `[[CodeCrafters]]` — not found
|
||||
- `wiki/sources/build-your-own-x.md` links to `[[CodeCrafters]]` — not found
|
||||
- `wiki/sources/build-your-own-x.md` links to `[[Richard Feynman]]` — not found
|
||||
- `wiki/sources/build-your-own-x.md` links to `[[编程学习]]` — not found
|
||||
- `wiki/sources/build-your-own-x.md` links to `[[Build Your Own X]]` — not found
|
||||
- `wiki/sources/multi-channel-assistant.md` links to `[[raw/Agent/usecases/multi-channel-assistant.md]]` — not found
|
||||
- `wiki/sources/multi-channel-assistant.md` links to `[[多渠道集成]]` — not found
|
||||
- `wiki/sources/multi-channel-assistant.md` links to `[[任务管理]]` — not found
|
||||
- `wiki/sources/multi-channel-assistant.md` links to `[[多渠道集成]]` — not found
|
||||
- `wiki/sources/multi-channel-assistant.md` links to `[[Google Workspace]]` — not found
|
||||
- `wiki/sources/multi-channel-assistant.md` links to `[[多渠道集成]]` — not found
|
||||
- `wiki/sources/LLMs、RAG、AI Agent 三个到底什么区别？.md` links to `[[raw/AI/LLMs、RAG、AI Agent 三个到底什么区别？.md]]` — not found
|
||||
- `wiki/sources/LLMs、RAG、AI Agent 三个到底什么区别？.md` links to `[[AI Agent]]` — not found
|
||||
- `wiki/sources/LLMs、RAG、AI Agent 三个到底什么区别？.md` links to `[[幻觉]]` — not found
|
||||
- `wiki/sources/LLMs、RAG、AI Agent 三个到底什么区别？.md` links to `[[思考能力]]` — not found
|
||||
- `wiki/sources/LLMs、RAG、AI Agent 三个到底什么区别？.md` links to `[[AI Agent]]` — not found
|
||||
- `wiki/sources/LLMs、RAG、AI Agent 三个到底什么区别？.md` links to `[[AI Agent]]` — not found
|
||||
- `wiki/sources/OpenAI ChatGPT 个性化定义.md` links to `[[raw/AI/OpenAI ChatGPT 个性化定义.md]]` — not found
|
||||
- `wiki/sources/OpenAI ChatGPT 个性化定义.md` links to `[[自定义指令]]` — not found
|
||||
- `wiki/sources/OpenAI ChatGPT 个性化定义.md` links to `[[个性化AI]]` — not found
|
||||
- `wiki/sources/OpenAI ChatGPT 个性化定义.md` links to `[[ChatGPT]]` — not found
|
||||
- `wiki/sources/OpenAI ChatGPT 个性化定义.md` links to `[[OpenAI]]` — not found
|
||||
- `wiki/sources/OpenAI ChatGPT 个性化定义.md` links to `[[ChatGPT]]` — not found
|
||||
- `wiki/sources/OpenAI ChatGPT 个性化定义.md` links to `[[自定义指令]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[raw/AI/A Formalization of Recursive Self-Optimizing Generative Systems.md]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[递归自优化]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[固定点]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[自映射]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[元生成]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[Bootstrap]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[自优化AI]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[递归自优化系统]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[固定点语义]]` — not found
|
||||
- `wiki/sources/a-formalization-of-recursive-self-optimizing-generative-systems.md` links to `[[Bootstrap]]` — not found
|
||||
- `wiki/sources/event-guest-confirmation.md` links to `[[raw/Agent/usecases/event-guest-confirmation.md]]` — not found
|
||||
- `wiki/sources/event-guest-confirmation.md` links to `[[电话确认]]` — not found
|
||||
- `wiki/sources/event-guest-confirmation.md` links to `[[SuperCall]]` — not found
|
||||
- `wiki/sources/event-guest-confirmation.md` links to `[[批量呼叫]]` — not found
|
||||
- `wiki/sources/event-guest-confirmation.md` links to `[[SuperCall]]` — not found
|
||||
- `wiki/sources/event-guest-confirmation.md` links to `[[电话确认]]` — not found
|
||||
- `wiki/sources/market-research-product-factory.md` links to `[[raw/Agent/usecases/market-research-product-factory.md]]` — not found
|
||||
- `wiki/sources/market-research-product-factory.md` links to `[[市场研究]]` — not found
|
||||
- `wiki/sources/market-research-product-factory.md` links to `[[产品发现]]` — not found
|
||||
- `wiki/sources/market-research-product-factory.md` links to `[[Last 30 Days]]` — not found
|
||||
- `wiki/sources/market-research-product-factory.md` links to `[[Last 30 Days]]` — not found
|
||||
- `wiki/sources/custom-morning-brief.md` links to `[[raw/Agent/usecases/custom-morning-brief.md]]` — not found
|
||||
- `wiki/sources/Nano Banana 提示词框架.md` links to `[[raw/AI/Nano Banana 提示词框架.md]]` — not found
|
||||
- `wiki/sources/Nano Banana 提示词框架.md` links to `[[Nano Banana]]` — not found
|
||||
- `wiki/sources/Nano Banana 提示词框架.md` links to `[[物件描述]]` — not found
|
||||
- `wiki/sources/Nano Banana 提示词框架.md` links to `[[人物描述]]` — not found
|
||||
- `wiki/sources/Nano Banana 提示词框架.md` links to `[[Nano Banana]]` — not found
|
||||
- `wiki/sources/Nano Banana 提示词框架.md` links to `[[AI图像生成]]` — not found
|
||||
- `wiki/sources/Nano Banana 提示词框架.md` links to `[[Nano Banana]]` — not found
|
||||
- `wiki/sources/best-7-news-api.md` links to `[[raw/AI/Best 7 news API data feeds - AI News.md]]` — not found
|
||||
- `wiki/sources/best-7-news-api.md` links to `[[新闻API]]` — not found
|
||||
- `wiki/sources/best-7-news-api.md` links to `[[实时数据]]` — not found
|
||||
- `wiki/sources/best-7-news-api.md` links to `[[情感分析]]` — not found
|
||||
- `wiki/sources/best-7-news-api.md` links to `[[数据聚合]]` — not found
|
||||
- `wiki/sources/best-7-news-api.md` links to `[[新闻API]]` — not found
|
||||
- `wiki/sources/best-7-news-api.md` links to `[[金融情报]]` — not found
|
||||
- `wiki/sources/best-7-news-api.md` links to `[[Bloomberg API]]` — not found
|
||||
- `wiki/sources/二创视频必不可少！2025年最热门AI工具推荐合集-AI配音、声音克隆.md` links to `[[raw/AI/二创视频必不可少！2025年最热门AI工具推荐合集-AI配音、声音克隆.md]]` — not found
|
||||
- `wiki/sources/二创视频必不可少！2025年最热门AI工具推荐合集-AI配音、声音克隆.md` links to `[[TTS]]` — not found
|
||||
- `wiki/sources/二创视频必不可少！2025年最热门AI工具推荐合集-AI配音、声音克隆.md` links to `[[F5-TTS]]` — not found
|
||||
- `wiki/sources/二创视频必不可少！2025年最热门AI工具推荐合集-AI配音、声音克隆.md` links to `[[二创视频]]` — not found
|
||||
- `wiki/sources/二创视频必不可少！2025年最热门AI工具推荐合集-AI配音、声音克隆.md` links to `[[内容创作]]` — not found
|
||||
- `wiki/sources/MCP在Cursor中的集成与应用详解.md` links to `[[raw/Agent/MCP在Cursor中的集成与应用详解.md]]` — not found
|
||||
- `wiki/sources/MCP在Cursor中的集成与应用详解.md` links to `[[鱼凤]]` — not found
|
||||
- `wiki/sources/inbox-declutter.md` links to `[[raw/Agent/usecases/inbox-declutter.md]]` — not found
|
||||
- `wiki/sources/inbox-declutter.md` links to `[[邮件管理]]` — not found
|
||||
- `wiki/sources/inbox-declutter.md` links to `[[新闻聚合]]` — not found
|
||||
- `wiki/sources/daily-reddit-digest.md` links to `[[raw/Agent/usecases/daily-reddit-digest.md]]` — not found
|
||||
- `wiki/sources/daily-reddit-digest.md` links to `[[Reddit聚合]]` — not found
|
||||
- `wiki/sources/daily-reddit-digest.md` links to `[[内容过滤]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[raw/AI/一语点醒梦中人.md]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[东方智慧]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[忘机]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[安之若命]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[有为法]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[王维]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[曾国藩]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[老子]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[庄子]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[儒家]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[中庸]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[道家]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[道德经]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[佛学]]` — not found
|
||||
- `wiki/sources/一语点醒梦中人.md` links to `[[金刚经]]` — not found
|
||||
- `wiki/sources/autonomous-project-management.md` links to `[[raw/Agent/usecases/autonomous-project-management.md]]` — not found
|
||||
- `wiki/sources/autonomous-project-management.md` links to `[[分散式协调]]` — not found
|
||||
- `wiki/sources/autonomous-project-management.md` links to `[[STATE.yaml]]` — not found
|
||||
- `wiki/sources/autonomous-project-management.md` links to `[[子Agent]]` — not found
|
||||
- `wiki/sources/autonomous-project-management.md` links to `[[子Agent]]` — not found
|
||||
- `wiki/sources/autonomous-project-management.md` links to `[[STATE.yaml]]` — not found
|
||||
- `wiki/sources/autonomous-project-management.md` links to `[[主Agent]]` — not found
|
||||
- `wiki/sources/autonomous-project-management.md` links to `[[子Agent]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[raw/AI/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[FeatureList]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[PRD]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[mermaid]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[AI工作流]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[Gemini]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[产品经理]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[Gemini]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[PRD生成]]` — not found
|
||||
- `wiki/sources/不会Gemini的产品经理真的要被淘汰了 附保姆级PRD生成指南.md` links to `[[AI工作流]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[raw/Agent/usecases/pre-build-idea-validator.md]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[创意验证]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[reality_signal]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[idea-reality-mcp]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[idea-reality-mcp]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[GitHub]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[idea-reality-mcp]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[Hacker News]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[idea-reality-mcp]]` — not found
|
||||
- `wiki/sources/pre-build-idea-validator.md` links to `[[npm]]` — not found
|
||||
- `wiki/sources/dynamic-dashboard.md` links to `[[raw/Agent/usecases/dynamic-dashboard.md]]` — not found
|
||||
- `wiki/sources/dynamic-dashboard.md` links to `[[动态仪表板]]` — not found
|
||||
- `wiki/sources/dynamic-dashboard.md` links to `[[并行处理]]` — not found
|
||||
- `wiki/sources/dynamic-dashboard.md` links to `[[子Agent]]` — not found
|
||||
- `wiki/sources/todoist-task-manager.md` links to `[[raw/Agent/usecases/todoist-task-manager.md]]` — not found
|
||||
- `wiki/sources/todoist-task-manager.md` links to `[[任务可见性]]` — not found
|
||||
- `wiki/sources/todoist-task-manager.md` links to `[[外部化推理]]` — not found
|
||||
- `wiki/sources/habit-tracker-accountability-coach.md` links to `[[raw/Agent/usecases/habit-tracker-accountability-coach.md]]` — not found
|
||||
- `wiki/sources/habit-tracker-accountability-coach.md` links to `[[习惯追踪]]` — not found
|
||||
- `wiki/sources/habit-tracker-accountability-coach.md` links to `[[主动问责]]` — not found
|
||||
- `wiki/sources/habit-tracker-accountability-coach.md` links to `[[适应性语气]]` — not found
|
||||
- `wiki/sources/habit-tracker-accountability-coach.md` links to `[[习惯追踪]]` — not found
|
||||
- `wiki/sources/habit-tracker-accountability-coach.md` links to `[[Telegram]]` — not found
|
||||
- `wiki/sources/n8n-configure-telegram-trigger.md` links to `[[raw/Agent/n8n configure telegram trigger.md]]` — not found
|
||||
- `wiki/sources/n8n-configure-telegram-trigger.md` links to `[[Webhook]]` — not found
|
||||
- `wiki/sources/n8n-configure-telegram-trigger.md` links to `[[Telegram Trigger]]` — not found
|
||||
- `wiki/sources/n8n-configure-telegram-trigger.md` links to `[[Telegram Trigger]]` — not found
|
||||
- `wiki/sources/n8n-configure-telegram-trigger.md` links to `[[Telegram Trigger]]` — not found
|
||||
- `wiki/sources/n8n-configure-telegram-trigger.md` links to `[[Webhook]]` — not found
|
||||
- `wiki/sources/latex-paper-writing.md` links to `[[raw/Agent/usecases/latex-paper-writing.md]]` — not found
|
||||
- `wiki/sources/latex-paper-writing.md` links to `[[LaTeX写作]]` — not found
|
||||
- `wiki/sources/latex-paper-writing.md` links to `[[Prismer]]` — not found
|
||||
- `wiki/sources/latex-paper-writing.md` links to `[[Prismer]]` — not found
|
||||
- `wiki/sources/latex-paper-writing.md` links to `[[LaTeX服务器]]` — not found
|
||||
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|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[规划驱动]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[AI结对]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[上下文固定]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[vibe-coding-cn]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[Windsurf]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[Trae]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[AI编程]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[Karpathy]]` — not found
|
||||
- `wiki/sources/GitHub 上 5000 人收藏的 Vibe Coding 神级指南。.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/sources/second-brain.md` links to `[[raw/Agent/usecases/second-brain.md]]` — not found
|
||||
- `wiki/sources/second-brain.md` links to `[[第二大脑]]` — not found
|
||||
- `wiki/sources/multi-channel-customer-service.md` links to `[[raw/Agent/usecases/multi-channel-customer-service.md]]` — not found
|
||||
- `wiki/sources/multi-channel-customer-service.md` links to `[[客户服务自动化]]` — not found
|
||||
- `wiki/sources/multi-channel-customer-service.md` links to `[[多渠道管理]]` — not found
|
||||
- `wiki/sources/7-ways-notebooklm.md` links to `[[raw/AI/7 ways I use NotebookLM to make my life easier.md]]` — not found
|
||||
- `wiki/sources/7-ways-notebooklm.md` links to `[[Source-Grounding]]` — not found
|
||||
- `wiki/sources/7-ways-notebooklm.md` links to `[[项目中心]]` — not found
|
||||
- `wiki/sources/7-ways-notebooklm.md` links to `[[Source-Grounding]]` — not found
|
||||
- `wiki/sources/7-ways-notebooklm.md` links to `[[AI学习工具]]` — not found
|
||||
- `wiki/sources/n8n-workflow-orchestration.md` links to `[[raw/Agent/usecases/n8n-workflow-orchestration.md]]` — not found
|
||||
- `wiki/sources/n8n-workflow-orchestration.md` links to `[[凭证隔离]]` — not found
|
||||
- `wiki/sources/n8n-workflow-orchestration.md` links to `[[工作流编排]]` — not found
|
||||
- `wiki/sources/n8n-workflow-orchestration.md` links to `[[Webhook]]` — not found
|
||||
- `wiki/sources/n8n-workflow-orchestration.md` links to `[[Webhook]]` — not found
|
||||
- `wiki/sources/n8n-workflow-orchestration.md` links to `[[Webhook]]` — not found
|
||||
- `wiki/sources/n8n-workflow-orchestration.md` links to `[[n8n工作流]]` — not found
|
||||
- `wiki/sources/n8n-workflow-orchestration.md` links to `[[凭证隔离]]` — not found
|
||||
- `wiki/sources/如何写出完美的Prompt（提示词）？.md` links to `[[raw/AI/如何写出完美的Prompt（提示词）？.md]]` — not found
|
||||
- `wiki/sources/如何写出完美的Prompt（提示词）？.md` links to `[[AI协作]]` — not found
|
||||
- `wiki/sources/如何写出完美的Prompt（提示词）？.md` links to `[[结构化思维]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[raw/Agent/使用Claude自动生成N8N工作流的实操教程.md]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[n8n-mcp]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[Extended Thinking]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[Claude]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[czlonkowski]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[Claude]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[n8n-mcp]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[n8n-mcp]]` — not found
|
||||
- `wiki/sources/使用Claude自动生成N8N工作流的实操教程.md` links to `[[N8N节点]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[raw/AI/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[Claude Skills]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[SOP标准化]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[Anthropic]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[Claude]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[提示词工程]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[Claude Skills]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[SOP标准化]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[Vibe Coding]]` — not found
|
||||
- `wiki/sources/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！.md` links to `[[Claude Skills]]` — not found
|
||||
- `wiki/sources/local-crm-framework.md` links to `[[raw/Agent/usecases/local-crm-framework.md]]` — not found
|
||||
- `wiki/sources/local-crm-framework.md` links to `[[本地CRM]]` — not found
|
||||
- `wiki/sources/local-crm-framework.md` links to `[[DenchClaw]]` — not found
|
||||
- `wiki/sources/local-crm-framework.md` links to `[[浏览器自动化]]` — not found
|
||||
- `wiki/sources/local-crm-framework.md` links to `[[DenchClaw]]` — not found
|
||||
- `wiki/sources/local-crm-framework.md` links to `[[本地CRM]]` — not found
|
||||
- `wiki/sources/local-crm-framework.md` links to `[[DenchClaw]]` — not found
|
||||
- `wiki/sources/local-crm-framework.md` links to `[[DuckDB]]` — not found
|
||||
- `wiki/sources/overnight-mini-app-builder.md` links to `[[raw/Agent/usecases/overnight-mini-app-builder.md]]` — not found
|
||||
- `wiki/sources/overnight-mini-app-builder.md` links to `[[目标驱动任务]]` — not found
|
||||
- `wiki/sources/n8n+Claude通过自然语言自动化工作流.md` links to `[[raw/Agent/n8n+Claude通过自然语言自动化工作流.md]]` — not found
|
||||
- `wiki/sources/n8n+Claude通过自然语言自动化工作流.md` links to `[[自然语言处理]]` — not found
|
||||
- `wiki/sources/n8n+Claude通过自然语言自动化工作流.md` links to `[[工作流生成]]` — not found
|
||||
- `wiki/sources/n8n+Claude通过自然语言自动化工作流.md` links to `[[Claude]]` — not found
|
||||
- `wiki/sources/n8n+Claude通过自然语言自动化工作流.md` links to `[[工作流生成]]` — not found
|
||||
- `wiki/sources/n8n+Claude通过自然语言自动化工作流.md` links to `[[n8n-mcp]]` — not found
|
||||
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|
||||
- `wiki/sources/n8n-full-tutorial-building-ai-agents.md` links to `[[Agentic系统]]` — not found
|
||||
- `wiki/sources/n8n-full-tutorial-building-ai-agents.md` links to `[[Workflow]]` — not found
|
||||
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|
||||
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|
||||
- `wiki/sources/n8n-full-tutorial-building-ai-agents.md` links to `[[Airtable]]` — not found
|
||||
- `wiki/sources/n8n-full-tutorial-building-ai-agents.md` links to `[[N8N节点]]` — not found
|
||||
- `wiki/sources/n8n-full-tutorial-building-ai-agents.md` links to `[[Agentic系统]]` — not found
|
||||
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|
||||
- `wiki/sources/never-write-another-prompt.md` links to `[[提示词工程]]` — not found
|
||||
- `wiki/sources/never-write-another-prompt.md` links to `[[提示词生成器]]` — not found
|
||||
- `wiki/sources/never-write-another-prompt.md` links to `[[AI工具]]` — not found
|
||||
- `wiki/sources/never-write-another-prompt.md` links to `[[提示词生成器]]` — not found
|
||||
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|
||||
- `wiki/sources/polymarket-autopilot.md` links to `[[纸上交易]]` — not found
|
||||
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|
||||
- `wiki/sources/polymarket-autopilot.md` links to `[[投资组合追踪]]` — not found
|
||||
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|
||||
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|
||||
- `wiki/sources/固定镜头短视频制作的AI全流程解析.md` links to `[[时间压缩]]` — not found
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
- `wiki/sources/multi-source-tech-news-digest.md` links to `[[新闻聚合]]` — not found
|
||||
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|
||||
- `wiki/sources/multi-source-tech-news-digest.md` links to `[[四层数据管道]]` — not found
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
- `wiki/sources/RAG从入门到精通系列1：基础RAG.md` links to `[[Qdrant]]` — not found
|
||||
- `wiki/sources/RAG从入门到精通系列1：基础RAG.md` links to `[[BAAI]]` — not found
|
||||
- `wiki/sources/RAG从入门到精通系列1：基础RAG.md` links to `[[索引]]` — not found
|
||||
- `wiki/sources/RAG从入门到精通系列1：基础RAG.md` links to `[[检索]]` — not found
|
||||
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|
||||
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|
||||
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|
||||
- `wiki/sources/family-calendar-household-assistant.md` links to `[[环境监控]]` — not found
|
||||
- `wiki/sources/family-calendar-household-assistant.md` links to `[[家庭协调]]` — not found
|
||||
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|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md` links to `[[Ikigai]]` — not found
|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md` links to `[[一人公司]]` — not found
|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md` links to `[[底层能力]]` — not found
|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md` links to `[[产品体系]]` — not found
|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md` links to `[[一人公司]]` — not found
|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md` links to `[[Ikigai]]` — not found
|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md` links to `[[一人公司]]` — not found
|
||||
- `wiki/sources/万字保姆级教程-90天跑通一人公司模式-2026-03-29.md` links to `[[产品体系]]` — not found
|
||||
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|
||||
- `wiki/sources/aionui-cowork-desktop.md` links to `[[AionUi]]` — not found
|
||||
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|
||||
- `wiki/sources/aionui-cowork-desktop.md` links to `[[Cowork空间]]` — not found
|
||||
- `wiki/sources/aionui-cowork-desktop.md` links to `[[AionUi]]` — not found
|
||||
- `wiki/sources/aionui-cowork-desktop.md` links to `[[AionUi]]` — not found
|
||||
- `wiki/sources/aionui-cowork-desktop.md` links to `[[远程救援]]` — not found
|
||||
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|
||||
- `wiki/sources/semantic-memory-search.md` links to `[[语义记忆搜索]]` — not found
|
||||
- `wiki/sources/semantic-memory-search.md` links to `[[向量数据库]]` — not found
|
||||
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|
||||
- `wiki/sources/semantic-memory-search.md` links to `[[memsearch]]` — not found
|
||||
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|
||||
- `wiki/sources/semantic-memory-search.md` links to `[[memsearch]]` — not found
|
||||
- `wiki/sources/semantic-memory-search.md` links to `[[Milvus]]` — not found
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
- `wiki/sources/Nano Banana Pro提示词指南.md` links to `[[AI图像生成]]` — not found
|
||||
- `wiki/sources/Nano Banana Pro提示词指南.md` links to `[[Nano Banana Pro]]` — not found
|
||||
- `wiki/sources/Nano Banana Pro提示词指南.md` links to `[[Nano Banana Pro]]` — not found
|
||||
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|
||||
- `wiki/sources/Nano Banana Pro提示词指南.md` links to `[[Nano Banana Pro]]` — not found
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[开源平替]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[AI生图]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[AI生视频]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[AI智能体]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[AI编程]]` — not found
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[OpenManus]]` — not found
|
||||
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|
||||
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|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[开源AI]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[大语言模型]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[开源AI]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[AI生图]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[开源AI]]` — not found
|
||||
- `wiki/sources/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md` links to `[[AI生视频]]` — not found
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
- `wiki/sources/全网最全！Nano Banana 2 使用指南（2025年12月更新） 1.md` links to `[[Nano Banana 2]]` — not found
|
||||
- `wiki/sources/全网最全！Nano Banana 2 使用指南（2025年12月更新） 1.md` links to `[[推理模型]]` — not found
|
||||
- `wiki/sources/全网最全！Nano Banana 2 使用指南（2025年12月更新） 1.md` links to `[[AI图像生成]]` — not found
|
||||
- `wiki/sources/全网最全！Nano Banana 2 使用指南（2025年12月更新） 1.md` links to `[[Nano Banana 2]]` — not found
|
||||
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|
||||
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|
||||
- `wiki/sources/x-account-analysis.md` links to `[[Twitter分析]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[raw/AI/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[通才]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[自我教育]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[自利]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[自给自足]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[注意力经济]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[个人发展]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[通才模型]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[创造力]]` — not found
|
||||
- `wiki/sources/If you have multiple interests, do not waste the next 2-3 years 如果你有多项兴趣爱好，不要浪费接下来的两三年时间。.md` links to `[[注意力]]` — not found
|
||||
- `wiki/entities/MCP.md` links to `[[n8n-mcp]]` — not found
|
||||
- `wiki/entities/MCP.md` links to `[[MCP在Cursor中的集成与应用]]` — not found
|
||||
- `wiki/entities/NanoBanana.md` links to `[[Nano Banana提示词框架]]` — not found
|
||||
- `wiki/entities/NanoBanana.md` links to `[[Nano Banana 2使用指南]]` — not found
|
||||
- `wiki/entities/NanoBanana.md` links to `[[AI图像生成]]` — not found
|
||||
- `wiki/entities/NanoBanana.md` links to `[[Nano Banana]]` — not found
|
||||
- `wiki/entities/NanoBanana.md` links to `[[Nano Banana]]` — not found
|
||||
- `wiki/entities/海螺AI.md` links to `[[AI配音与声音克隆工具合集]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[AGENTS.md]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[SOUL.md]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[USER.md]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[TOOLS.md]]` — not found
|
||||
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|
||||
- `wiki/entities/OpenClaw.md` links to `[[BOOTSTRAP.md]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[memory/]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[多Agent专业团队]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[自愈家庭服务器]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[第二大脑]]` — not found
|
||||
- `wiki/entities/OpenClaw.md` links to `[[目标驱动自主任务]]` — not found
|
||||
- `wiki/entities/LangChain.md` links to `[[LLM应用开发]]` — not found
|
||||
- `wiki/entities/ElevenLabs.md` links to `[[AI配音与声音克隆工具合集]]` — not found
|
||||
- `wiki/entities/剪映.md` links to `[[AI配音与声音克隆工具合集]]` — not found
|
||||
- `wiki/entities/剪映.md` links to `[[AI视频制作]]` — not found
|
||||
- `wiki/entities/剪映.md` links to `[[短视频制作]]` — not found
|
||||
- `wiki/entities/NotebookLM.md` links to `[[7 ways I use NotebookLM to make my life easier]]` — not found
|
||||
- `wiki/entities/NotebookLM.md` links to `[[NotebookLM Open Source Alternatives]]` — not found
|
||||
- `wiki/entities/NotebookLM.md` links to `[[Source-Grounding]]` — not found
|
||||
- `wiki/entities/NotebookLM.md` links to `[[AI学习工具]]` — not found
|
||||
- `wiki/entities/DeepSider.md` links to `[[Nano Banana 2使用指南]]` — not found
|
||||
- `wiki/entities/DeepSider.md` links to `[[Nano Banana 2]]` — not found
|
||||
- `wiki/entities/DeepSider.md` links to `[[AI工具聚合]]` — not found
|
||||
- `wiki/entities/F5TTS.md` links to `[[AI配音与声音克隆工具合集]]` — not found
|
||||
- `wiki/entities/F5TTS.md` links to `[[F5-TTS]]` — not found
|
||||
- `wiki/entities/F5TTS.md` links to `[[F5-TTS]]` — not found
|
||||
- `wiki/entities/F5TTS.md` links to `[[开源工具]]` — not found
|
||||
- `wiki/entities/F5TTS.md` links to `[[F5-TTS]]` — not found
|
||||
- `wiki/entities/N8N.md` links to `[[n8n-mcp]]` — not found
|
||||
- `wiki/entities/N8N.md` links to `[[OpenClaw + n8n工作流编排]]` — not found
|
||||
- `wiki/entities/N8N.md` links to `[[使用Claude自动生成N8N工作流]]` — not found
|
||||
- `wiki/entities/N8N.md` links to `[[N8N Telegram Trigger配置]]` — not found
|
||||
- `wiki/entities/N8N.md` links to `[[N8N全教程构建AI Agent]]` — not found
|
||||
- `wiki/entities/N8N.md` links to `[[N8N工作流编排]]` — not found
|
||||
|
||||
### Missing Entity Pages (mentioned 3+ times but no page)
|
||||
- `[[DenchClaw]]`
|
||||
- `[[AionUi]]`
|
||||
- `[[Nano Banana]]`
|
||||
- `[[F5-TTS]]`
|
||||
- `[[n8n-mcp]]`
|
||||
- `[[idea-reality-mcp]]`
|
||||
- `[[Source-Grounding]]`
|
||||
- `[[LLM Terms Framework]]`
|
||||
- `[[如何写出完美的Prompt]]`
|
||||
- `[[固定镜头短视频AI全流程制作]]`
|
||||
- `[[AI视频制作]]`
|
||||
- `[[7 ways I use NotebookLM to make my life easier]]`
|
||||
- `[[Claude Skills最值得研究的AI范式]]`
|
||||
- `[[提示词工程]]`
|
||||
- `[[Claude Skills]]`
|
||||
- `[[SOP标准化]]`
|
||||
- `[[结构化思维]]`
|
||||
- `[[Vibe Coding]]`
|
||||
- `[[AI编程]]`
|
||||
- `[[Agentic AI]]`
|
||||
- `[[AI产品设计]]`
|
||||
- `[[AGENTS.md]]`
|
||||
- `[[SOUL.md]]`
|
||||
- `[[YouTube]]`
|
||||
- `[[GitHub]]`
|
||||
- `[[arxiv-reader]]`
|
||||
- `[[向量数据库]]`
|
||||
- `[[AI图像生成]]`
|
||||
- `[[第二大脑]]`
|
||||
- `[[memsearch]]`
|
||||
- `[[AI配音与声音克隆工具合集]]`
|
||||
- `[[内容创作]]`
|
||||
- `[[USER.md]]`
|
||||
- `[[Claude]]`
|
||||
- `[[多渠道集成]]`
|
||||
- `[[AI Agent]]`
|
||||
- `[[子Agent]]`
|
||||
- `[[Webhook]]`
|
||||
- `[[Telegram Trigger]]`
|
||||
- `[[N8N节点]]`
|
||||
- `[[一人公司]]`
|
||||
- `[[Nano Banana Pro]]`
|
||||
- `[[开源AI]]`
|
||||
- `[[Nano Banana 2]]`
|
||||
|
||||
---
|
||||
|
||||
# Markdown Lint Report
|
||||
|
||||
## Contradictions
|
||||
1. **Definition of Agent**
|
||||
- In [[wiki/concepts/Agent.md]], Agent is defined as "LLM + MCP的组合," implying that it is a combination of LLM and MCP.
|
||||
- However, [[wiki/concepts/MCP.md]] indicates that MCP (Model Context Protocol) is primarily concerned with "连接大模型与外部数据和工具," which might suggest that Agent can exist without explicitly mentioning the necessity of LLM in every context. This creates ambiguity about whether MCP can function independently without LLM.
|
||||
|
||||
2. **Use of Terms "Agent" and "Agentic AI"**
|
||||
- [[wiki/concepts/Agent.md]] describes the capabilities of Agents as focusing on execution and task management.
|
||||
- [[wiki/concepts/AgenticAI.md]], on the other hand, represents Agentic AI as primarily involving proactive behavior and user anticipation, which could lead to confusion regarding the boundary between a traditional Agent and Agentic AI.
|
||||
|
||||
## Stale Content
|
||||
1. The last updated dates on several concepts like [[wiki/concepts/RAG.md]], [[wiki/concepts/首尾针动画.md]], [[wiki/concepts/九宫格法.md]], and [[wiki/concepts/音频概览.md]] are 2025-12-18, 2025-03-15, 2025-03-15, and 2025-11-23 respectively. Given that it is currently October 2023, the content may need fresh updates to reflect the latest advancements and applications, especially in a rapidly evolving field like AI.
|
||||
|
||||
2. The definitions and context for technologies like [[wiki/concepts/Token.md]] and [[wiki/concepts/vLLM.md]] may need to include more recent frameworks or models that have emerged after these were drafted.
|
||||
|
||||
## Data Gaps & Suggested Sources
|
||||
1. **Latest Applications of AI in Industries**
|
||||
- There is no information on how AI applications are currently transforming industries such as healthcare, finance, and education.
|
||||
- Suggested Source: "AI Transforms Industries: The Latest Market Trends," available on platforms like McKinsey or Deloitte.
|
||||
|
||||
2. **Integration of Multimodal AI**
|
||||
- The wiki lacks references about the integration of multimodal AI, which is becoming increasingly popular.
|
||||
- Suggested Source: "Multimodal AI: Emerging Trends and Applications," available on research databases like arXiv.
|
||||
|
||||
3. **An Exploration of Agent Behaviors in Dynamic Environments**
|
||||
- Although the concept of Agents is well-defined, there’s a gap regarding how they adapt or behave in dynamic or unpredictable environments.
|
||||
- Suggested Source: "Understanding Agent Behaviors in Dynamic Contexts," from academic journals focusing on AI behavior.
|
||||
|
||||
## Concepts Needing More Depth
|
||||
1. **MCP (Model Context Protocol)**
|
||||
- The concept of MCP provides a framework for integrating AI models with external tools but lacks detailed examples of its implementation in real-world scenarios. Providing case studies or detailed examples could enhance understanding.
|
||||
|
||||
2. **RAG (Retrieval Augmented Generation)**
|
||||
- RAG is defined, but it lacks an in-depth exploration of various models that implement RAG. A comparison of different RAG implementations could add valuable insights for users.
|
||||
|
||||
3. **Agentic AI**
|
||||
- While a definition is provided, the principles of design and implementation in various contexts are inadequately explored. More detailed challenges and practical applications of design principles could enhance the utility of this entry.
|
||||
|
||||
4. **Sequential Thinking**
|
||||
- There is a brief summary in the current entry with no extensive discussion on its methodologies or practical examples of its application in problem-solving tasks using AI. More case studies or application scenarios would provide deeper insights.
|
||||
|
||||
By addressing these issues, the wiki can enhance its value as a knowledge resource for understanding AI technologies and their applications.
|
||||
450
wiki/log.md
450
wiki/log.md
@@ -1,450 +0,0 @@
|
||||
## [2026-04-14] lint | Wiki health check
|
||||
|
||||
Ran lint. See lint-report.md for details.
|
||||
|
||||
# Wiki Log
|
||||
|
||||
## [2026-04-14] ingest | AI目录批量摄取（26个文件）
|
||||
|
||||
### 摄取统计
|
||||
- Source页面：26个
|
||||
- Entity页面：11个（NotebookLM、NanoBanana、DeepSider、ElevenLabs、海螺AI、F5-TTS、剪映、LangChain等）
|
||||
- Concept页面：21个（Source-Grounding、音频概览、提示词框架、GenAI、Agentic AI、RAG、Embedding、Prompt能力、AI配音、声音克隆、固定机位、首尾针动画、九宫格法、LLM、Token、MCP、Agent、vLLM、Claude Skills、流程工程、Vibe Coding等）
|
||||
|
||||
### 主要主题
|
||||
- AI图像生成：Nano Banana提示词工程
|
||||
- AI配音与声音克隆：ElevenLabs、海螺AI、F5-TTS
|
||||
- 视频制作：固定镜头、九宫格法、首尾针动画
|
||||
- RAG检索增强生成
|
||||
- 大模型术语体系：LLM、MCP、Agent、vLLM、Token
|
||||
- Claude Skills与流程工程
|
||||
- Prompt能力与提示词工程
|
||||
|
||||
### 冲突检测
|
||||
- 无重大冲突发现
|
||||
|
||||
## [2026-04-14] ingest | MCP在Cursor中的集成与应用详解.md
|
||||
|
||||
### 摄取统计
|
||||
- 重新解析 Source 页面：1个
|
||||
- 新增 Entity：2个（Cursor、Smisery）
|
||||
- 新增 Concept：3个（Agent模式、SequentialThinking、SSE）
|
||||
|
||||
### 冲突检测
|
||||
- 无冲突
|
||||
|
||||
## [2026-04-14] ingest | Agent目录批量摄取（45个文件）
|
||||
|
||||
### 摄取统计
|
||||
- Source页面：45个
|
||||
- Entity页面：3个（OpenClaw、N8N、MCP）
|
||||
- Concept页面：5个（Workspace、多Agent系统、工作流自动化、记忆系统、技能系统）
|
||||
|
||||
### 来源文件
|
||||
- 主目录：8个文件
|
||||
- usecases子目录：37个文件
|
||||
|
||||
### 主要主题
|
||||
- OpenClaw配置与使用
|
||||
- N8N工作流自动化
|
||||
- MCP协议集成
|
||||
- 多Agent协作系统
|
||||
- 个人效率工具
|
||||
- 内容创作自动化
|
||||
- 商业应用（CRM、市场研究）
|
||||
|
||||
## [2026-04-14] ingest | AI目录补充摄取（14个文件）
|
||||
|
||||
### 摄取统计
|
||||
- Source页面：14个
|
||||
- Entity页面：9个（Anthropic、DeepSeek、Canva、Gamma AI、Sora、Ollama、Open-Webui、Coze等）
|
||||
- Concept页面：2个（PromptLibrary、本地部署）
|
||||
|
||||
### 主要主题
|
||||
- Coze平台Demo合集
|
||||
- Anthropic官方Prompt Library
|
||||
- 本地大模型部署（Ollama+DeepSeek+Open-Webui）
|
||||
- 简报工作流（ChatGPT+Canva+Gamma）
|
||||
- 视频生成工具（Sora、文字转视频）
|
||||
- DeepSeek使用手册
|
||||
- 系统提示词构建原则
|
||||
|
||||
### 冲突检测
|
||||
- 无冲突
|
||||
|
||||
## [2026-04-14] ingest | Agent目录补充摄取（2个文件）
|
||||
|
||||
### 摄取统计
|
||||
- Source页面：2个
|
||||
- Entity页面：0个
|
||||
- Concept页面：0个
|
||||
|
||||
### 主要主题
|
||||
- Google 5个Agent Skill设计模式
|
||||
- n8n Telegram Trigger HTTPS错误修复
|
||||
|
||||
### 冲突检测
|
||||
- 无冲突
|
||||
|
||||
## [2026-04-14] ingest | Agent目录第三批摄取（6个文件）
|
||||
|
||||
### 摄取统计
|
||||
- Source页面：6个
|
||||
- Entity页面：2个（Google、ClawdTalk）
|
||||
- Concept页面：6个（AgentSkill设计模式、ToolWrapper、Generator、Reviewer、Inversion、Pipeline）
|
||||
|
||||
### 来源文件
|
||||
- Google-5个Agent-Skill设计模式-2026-03-19.md
|
||||
- n8n configure telegram trigger.md
|
||||
- n8n docker install & update.md
|
||||
- n8n full tutorial building AI agents in 2025 for Beginners!.md
|
||||
- n8n+Claude 通过自然语言自动化工作流.md
|
||||
- usecases/phone-based-personal-assistant.md
|
||||
|
||||
### 主要主题
|
||||
- Google 5种Agent Skill设计模式（ToolWrapper、Generator、Reviewer、Inversion、Pipeline）
|
||||
- n8n Telegram Trigger HTTPS错误修复（设置WEBHOOK_URL环境变量）
|
||||
- n8n Docker安装与更新（含容器内SOCKS5代理配置）
|
||||
- n8n AI Agent构建教程（节点类型、内存管理、工具集成）
|
||||
- 电话语音助手（ClawdTalk + Telnyx）
|
||||
|
||||
### 冲突检测
|
||||
- 无冲突
|
||||
|
||||
## 2026-04-14 | ingest | batch misc sources
|
||||
- 摄入目录: Daily notes, Others, Skills, Vibe Coding, 微信公众号, 跨境电商
|
||||
- 文件数量: 45个
|
||||
- 主题: AI Agent实践、Obsidian笔记、跨境电商
|
||||
|
||||
|
||||
## [2026-04-14] ingest | AI目录批量摄取（18个文件）
|
||||
|
||||
### 摄取统计
|
||||
- Source页面：18个
|
||||
- Entity页面：6个（Webz.io、GNews API、Opoint、Mediastack、Ferd、Alex Ewerlöf）
|
||||
- Concept页面：8个（固定点语义、自举Meta生成、YouTubeRSS、泰勒主义软件工厂、AI拟人化谬误、多Agent可靠性模式、验证器模式、共识投票）
|
||||
|
||||
### 来源文件
|
||||
- raw/AI/目录：18个文件
|
||||
|
||||
### 主要主题
|
||||
- Claude Skills与流程工程
|
||||
- NotebookLM深度使用与Source-Grounding
|
||||
- 递归自我优化生成系统（固定点语义、自举Meta生成）
|
||||
- 多Agent可靠性四大架构模式
|
||||
- AI工具命名哲学与泰勒主义批评
|
||||
- 新闻API生态（Webz.io、GNews、Opoint、Mediastack）
|
||||
- Nano Banana Pro官方提示词指南
|
||||
- Ollama+DeepSeek本地部署
|
||||
- Sora视频自动化工作流
|
||||
- ChatGPT+Canva/Gamma简报工作流
|
||||
- YouTube RSS获取方法
|
||||
|
||||
### 冲突检测
|
||||
- 无重大冲突发现
|
||||
|
||||
## [2026-04-14] ingest | Others+Skills+VibeCoding+微信公众号+跨境电商目录批量摄取（51个文件）
|
||||
|
||||
### 摄取统计
|
||||
- Source页面：51个
|
||||
- Entity页面：TapXWorld(中国教材)、VibeKanban(任务看板)、OpenCode(AI编程代理)、Trae(IDE)等
|
||||
- Concept页面：SourceGrounding(NotebookLM)、自举Meta生成、5大设计原则(Agentic AI)、MD5去重、混合搜索等
|
||||
|
||||
### 来源文件
|
||||
- Others目录：9个文件（ChinaTextbook、Obsidian笔记系列、YouTube Channel ID、TikTok PM Django）
|
||||
- Skills目录：3个文件（GOG CLI、Last30Days、baoyu-skills）
|
||||
- Vibe Coding目录：7个文件（Cursor 2.0、Trae远程开发、Vibe-Kanban+OpenCode、vibe coding经验）
|
||||
- 微信公众号目录：7个文件（养虾日记1-5、AI时代赚钱）
|
||||
- 跨境电商目录：5个文件（TikTok数据抓取、选品策略、Superset Dashboard）
|
||||
- AI目录：20个文件（补充）
|
||||
|
||||
### 主要主题
|
||||
- Obsidian笔记系统：Tasks插件、Dataview、双链笔记、碎片化整理
|
||||
- Vibe Coding：C vursor/Trae/OpenCode/Vibe-Kanban配置与经验
|
||||
- AI Agent记忆系统：OpenClaw双层记忆+Self-Improving复盘机制
|
||||
- 苏东坡蒸馏：女娲造人术实践案例
|
||||
- TikTok电商：选品策略、Superset Dashboard设计、数据抓取
|
||||
- 新闻API：Webz.io、GNews、Opoint、Mediastack评测
|
||||
|
||||
### 冲突检测
|
||||
- 无重大冲突发现
|
||||
|
||||
## [2026-04-14] ingest | Home Office + Cloud DevOps 目录批量摄取（42个文件）
|
||||
|
||||
### 摄取统计
|
||||
- Source页面：42个
|
||||
- Entity页面：Homarr、it-tools、Transmission、Navidrome、Jellyfin、Portainer、Apache Superset、Bandwagon、AdsPower、PingMe、WildCard、Rufus、HP ZBook、Ubuntu1、Ubuntu2、VPS1 等
|
||||
- Concept页面：Symbolic Link、克隆、NFS永久挂载、增量备份、Wayland、X11、锁盖休眠、iptables、代理协议等
|
||||
|
||||
### 来源文件
|
||||
- raw/Home Office/ 目录：39个文件
|
||||
- raw/Cloud & DevOps/ 目录：3个文件
|
||||
|
||||
### 主要主题
|
||||
- 家庭网络基础设施：FRP内网穿透、Caddy反向代理、NAS部署
|
||||
- 服务器运维：Docker全家桶安装、Ubuntu Server配置
|
||||
- 数据保护：Clonezilla镜像备份、rsync增量备份
|
||||
- 媒体服务器：Jellyfin、Navidrome、Plex、Xiaoya Alist
|
||||
- 开发工具：Ollama+Qwen2.5-Coder、Portainer、it-tools
|
||||
- 监控方案：Prometheus+Grafana+cAdvisor监控栈
|
||||
- 科学上网：v2rayN、V2RayA、MerlinClash、NodeWarden
|
||||
- 云服务交付：DevOps文化、云服务交付生命周期
|
||||
|
||||
### 冲突检测
|
||||
- 无重大冲突发现
|
||||
|
||||
|
||||
## [2026-04-14] ingest | 2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！ 1
|
||||
- [[raw/AI/3.2 万人收藏的 Claude Skills，才是 AI 这条路上最值得研究的一套范式！ 1.md]]
|
||||
|
||||
## [2026-04-14] ingest | 7 ways I use NotebookLM to make my life easier
|
||||
- [[raw/AI/7 ways I use NotebookLM to make my life easier.md]]
|
||||
|
||||
## [2026-04-14] ingest | A Formalization of Recursive Self-Optimizing Generative Systems
|
||||
- [[raw/AI/A Formalization of Recursive Self-Optimizing Generative Systems.md]]
|
||||
|
||||
## [2026-04-14] ingest | AI 解决方案专家培训课程
|
||||
- [[raw/AI/AI 解决方案专家培训课程.md]]
|
||||
|
||||
## [2026-04-14] ingest | Best 7 news API data feeds - AI News
|
||||
- [[raw/AI/Best 7 news API data feeds - AI News.md]]
|
||||
|
||||
## [2026-04-14] ingest | Designing for Agentic AI
|
||||
- [[raw/AI/Designing for Agentic AI.md]]
|
||||
|
||||
## [2026-04-14] ingest | How to Get the RSS Feed For Any YouTube Channel
|
||||
- [[raw/AI/How to Get the RSS Feed For Any YouTube Channel.md]]
|
||||
|
||||
## [2026-04-14] ingest | Multi-Agent System Reliability
|
||||
- [[raw/AI/Multi-Agent System Reliability.md]]
|
||||
|
||||
## [2026-04-14] ingest | Nano-Banana Pro Prompting Guide & Strategies 1
|
||||
- [[raw/AI/Nano-Banana Pro Prompting Guide & Strategies 1.md]]
|
||||
|
||||
## [2026-04-14] ingest | Never write another prompt
|
||||
- [[raw/AI/Never write another prompt.md]]
|
||||
|
||||
## [2026-04-14] ingest | The Picture They Paint of You
|
||||
- [[raw/AI/The Picture They Paint of You.md]]
|
||||
|
||||
## [2026-04-14] ingest | Useful Prompt Lib
|
||||
- [[raw/AI/Useful Prompt Lib.md]]
|
||||
|
||||
## [2026-04-14] ingest | codecrafters-iobuild-your-own-x Master programming by recreating your favorite technologies from scratch
|
||||
- [[raw/AI/codecrafters-iobuild-your-own-x Master programming by recreating your favorite technologies from scratch.md]]
|
||||
|
||||
## [2026-04-14] ingest | 摘要
|
||||
- [[raw/AI/如何利用Sora接口实现视频自动化生成工作流.md]]
|
||||
|
||||
## [2026-04-14] ingest | 我用 Gemini 3 一口气做了 10 个应用，附教程
|
||||
- [[raw/AI/我用 Gemini 3 一口气做了 10 个应用，附教程.md]]
|
||||
|
||||
## [2026-04-14] ingest | 教學 ChatGPT 先做知識整理，再讓 Canva、 Gamma AI 輸出簡報
|
||||
- [[raw/AI/教學 ChatGPT 先做知識整理，再讓 Canva、 Gamma AI 輸出簡報.md]]
|
||||
|
||||
## [2026-04-14] ingest | 清华出的DeepSeek使用手册，104页，真的是太厉害了！（免费领取）
|
||||
- [[raw/AI/清华出的DeepSeek使用手册，104页，真的是太厉害了！（免费领取）.md]]
|
||||
|
||||
## [2026-04-14] ingest | 查看服务器 CPU 信息获取其架构，如：x86_64
|
||||
- [[raw/AI/详细！离线部署大模型：ollama+deepseek+open-webui安装使用方法及常见问题解决 1.md]]
|
||||
|
||||
## [2026-04-14] ingest | 谷歌深夜甩出一份【Nano Banana Pro提示词指南】，手把手教你生产专业级内容，实战案例+提示词模版
|
||||
- [[raw/AI/谷歌深夜甩出一份【Nano Banana Pro提示词指南】，手把手教你生产专业级内容，实战案例+提示词模版.md]]
|
||||
|
||||
## [2026-04-14] ingest | 继Anthropic后，Google放出5个常用的Agent Skill设计模式
|
||||
- [[raw/Agent/Google-5个Agent-Skill设计模式-2026-03-19.md]]
|
||||
|
||||
## [2026-04-14] ingest | n8n configure telegram trigger
|
||||
- [[raw/Agent/n8n configure telegram trigger.md]]
|
||||
|
||||
## [2026-04-14] ingest | 安装 curl 和 wget
|
||||
- [[raw/Agent/n8n docker install & update.md]]
|
||||
|
||||
## [2026-04-14] ingest | n8n full tutorial building AI agents in 2025 for Beginners!
|
||||
- [[raw/Agent/n8n full tutorial building AI agents in 2025 for Beginners!.md]]
|
||||
|
||||
## [2026-04-14] ingest | 安装Claude Desktop
|
||||
- [[raw/Agent/n8n+Claude 通过自然语言自动化工作流.md]]
|
||||
|
||||
## [2026-04-14] ingest | DevOps Culture and Transformation Fostering Collaboration, Agile Practices, and Innovation LinkedIn
|
||||
- [[raw/Cloud & DevOps/DevOps Culture and Transformation Fostering Collaboration, Agile Practices, and Innovation LinkedIn.md]]
|
||||
|
||||
## [2026-04-14] ingest | The Myths and Misconceptions About Cloud Computing LinkedIn
|
||||
- [[raw/Cloud & DevOps/The Myths and Misconceptions About Cloud Computing LinkedIn.md]]
|
||||
|
||||
## [2026-04-14] ingest | What I know about Cloud Service Delivery 1
|
||||
- [[raw/Cloud & DevOps/What I know about Cloud Service Delivery 1.md]]
|
||||
|
||||
## [2026-04-14] ingest | 3X-UI Xray on BandwagonVPS
|
||||
- [[raw/Home Office/3X-UI Xray on BandwagonVPS.md]]
|
||||
|
||||
## [2026-04-14] ingest | Clonezilla对Ubuntu Server进行全盘镜像备份
|
||||
- [[raw/Home Office/Clonezilla对Ubuntu Server进行全盘镜像备份.md]]
|
||||
|
||||
## [2026-04-14] ingest | Linux 运维必会的 150 个命令
|
||||
- [[raw/Home Office/Linux 运维必会的 150 个命令.md]]
|
||||
|
||||
## [2026-04-14] ingest | Mac Mini 安装 FRP 0.65.0（ARM64）操作笔记
|
||||
- [[raw/Home Office/Mac Mini 安装 FRP 0.65.0（ARM64）操作笔记.md]]
|
||||
|
||||
## [2026-04-14] ingest | 1. 架构图（Synology 专用）
|
||||
- [[raw/Home Office/MinIO + Zipline 自托管图床应用安装教程.md]]
|
||||
|
||||
## [2026-04-14] ingest | MySQL MariaDB 数据库详细信息
|
||||
- [[raw/Home Office/MySQL MariaDB 数据库详细信息.md]]
|
||||
|
||||
## [2026-04-14] ingest | NodeWarden - 把 Bitwarden 搬上 Cloudflare Workers，彻底告别服务器
|
||||
- [[raw/Home Office/NodeWarden - 把 Bitwarden 搬上 Cloudflare Workers，彻底告别服务器.md]]
|
||||
|
||||
## [2026-04-14] ingest | RAX50 路由器 更新Merlin Clash订阅
|
||||
- [[raw/Home Office/RAX50 路由器 更新Merlin Clash订阅.md]]
|
||||
|
||||
## [2026-04-14] ingest | 1. 安装Plex
|
||||
- [[raw/Home Office/Synology NAS + Xiaoya Alist + CloudDrvie2+ Plex to Build Media Platform.md]]
|
||||
|
||||
## [2026-04-14] ingest | 启动 SSH 服务
|
||||
- [[raw/Home Office/Ubuntu 24.04 enable SSH.md]]
|
||||
|
||||
## [2026-04-14] ingest | Ubuntu Server科学上网
|
||||
- [[raw/Home Office/Ubuntu Server科学上网.md]]
|
||||
|
||||
## [2026-04-14] ingest | Ubuntu 安装 FRP 0.65.0（x86_64）操作笔记
|
||||
- [[raw/Home Office/Ubuntu 安装 FRP 0.65.0（x86_64）操作笔记.md]]
|
||||
|
||||
## [2026-04-14] ingest | 1 创建 Symbolic Link
|
||||
- [[raw/Home Office/macOS 创建与解除 Symbolic Link（OpenClaw 目录映射）.md]]
|
||||
|
||||
## [2026-04-14] ingest | 一、系统要求
|
||||
- [[raw/Home Office/在 Ubuntu 安装 Ollama 并运行 Qwen2.5‑Coder 7B.md]]
|
||||
|
||||
## [2026-04-14] ingest | 在Synology NAS上安装CloudDrive2
|
||||
- [[raw/Home Office/在Synology NAS上安装CloudDrive2.md]]
|
||||
|
||||
## [2026-04-14] ingest | 前置共识（已知条件）
|
||||
- [[raw/Home Office/在Ubuntu上通过VPS+内网反向代理实现域名访问内网穿透.md]]
|
||||
|
||||
## [2026-04-14] ingest | 如何传输Docker images 并且在另一个Docker安装
|
||||
- [[raw/Home Office/如何传输Docker images 并且在另一个Docker安装.md]]
|
||||
|
||||
## [2026-04-14] ingest | ✅ 最常用：删除旧 Portainer Container + Volume
|
||||
- [[raw/Home Office/如何删除旧的废弃的docker container +volume.md]]
|
||||
|
||||
## [2026-04-14] ingest | 如何判别你的Linux 服务器是 x64（也就是 x86_64）还是 ARM64
|
||||
- [[raw/Home Office/如何判别你的Linux 服务器是 x64（也就是 x86_64）还是 ARM64.md]]
|
||||
|
||||
## [2026-04-14] ingest | 1. 先卸载当前的挂载（如果当前还挂着的话）
|
||||
- [[raw/Home Office/如何在Ubuntu Server上通过NFS挂载Synology NAS上的共享文件夹.md]]
|
||||
|
||||
## [2026-04-14] ingest | 如何在Ubuntu Server安装 docker & docker compose
|
||||
- [[raw/Home Office/如何在Ubuntu Server安装 docker & docker compose.md]]
|
||||
|
||||
## [2026-04-14] ingest | 如何用指纹浏览器安全注册并订阅Claude Pro会员全攻略
|
||||
- [[raw/Home Office/如何用指纹浏览器安全注册并订阅Claude Pro会员全攻略.md]]
|
||||
|
||||
## [2026-04-14] ingest | 将 0005 (Ubuntu) 放在启动顺序的首位
|
||||
- [[raw/Home Office/安装Ubuntu-24.04.2在HP Zbook工作站笔记本上.md]]
|
||||
|
||||
## [2026-04-14] ingest | 核心目标（你要覆盖的监控面）
|
||||
- [[raw/Home Office/家庭监控方案：Prometheus + Grafana + Node Exporter + cAdvisor +Blackbox.md]]
|
||||
|
||||
## [2026-04-14] ingest | 家庭网络环境概览
|
||||
- [[raw/Home Office/家庭网络环境概览_2026-04-03.md]]
|
||||
|
||||
## [2026-04-14] ingest | 用Docker安装Apache Superset
|
||||
- [[raw/Home Office/用Docker安装Apache Superset.md]]
|
||||
|
||||
## [2026-04-14] ingest | 前置共识（已知条件）
|
||||
- [[raw/Home Office/通过VPS+内网反向代理实现域名访问内网穿透.md]]
|
||||
|
||||
## [2026-04-14] ingest | ChinaTextbook - 41.53 GB，中国小学、初中、高中、大学 PDF 教材
|
||||
- [[raw/Others/ChinaTextbook - 41.53 GB，中国小学、初中、高中、大学 PDF 教材.md]]
|
||||
|
||||
## [2026-04-14] ingest | Dataview——让我从“笔记黑洞”里逃出来的 Obsidian 神器 1
|
||||
- [[raw/Others/Dataview——让我从“笔记黑洞”里逃出来的 Obsidian 神器 1.md]]
|
||||
|
||||
## [2026-04-14] ingest | How to get Youtube Channel ID
|
||||
- [[raw/Others/How to get Youtube Channel ID.md]]
|
||||
|
||||
## [2026-04-14] ingest | Obsidian Tasks 插件：这可能是最适合懒人的任务管理方式
|
||||
- [[raw/Others/Obsidian Tasks 插件：这可能是最适合懒人的任务管理方式.md]]
|
||||
|
||||
## [2026-04-14] ingest | Obsidian 高效指南：我常用的插件与实用技巧
|
||||
- [[raw/Others/Obsidian 高效指南：我常用的插件与实用技巧.md]]
|
||||
|
||||
## [2026-04-14] ingest | Obsidian最有必要安装的10款插件是这些
|
||||
- [[raw/Others/Obsidian最有必要安装的10款插件是这些.md]]
|
||||
|
||||
## [2026-04-14] ingest | tiktok_pm_project/settings.py
|
||||
- [[raw/Others/TikTok PM - Python Django Project.md]]
|
||||
|
||||
## [2026-04-14] ingest | 为什么 Obsidian 让我戒掉了碎片化记录
|
||||
- [[raw/Others/为什么 Obsidian 让我戒掉了碎片化记录.md]]
|
||||
|
||||
## [2026-04-14] ingest | 为什么你的笔记总是乱糟糟？试试这个方法，彻底告别信息混乱！ 1
|
||||
- [[raw/Others/为什么你的笔记总是乱糟糟？试试这个方法，彻底告别信息混乱！ 1.md]]
|
||||
|
||||
## [2026-04-14] ingest | 输出: /opt/homebrew/bin/gog
|
||||
- [[raw/Skills/GOG-CLI-安装配置指南.md]]
|
||||
|
||||
## [2026-04-14] ingest | Last30Days 使用指南
|
||||
- [[raw/Skills/Last30Days-使用指南.md]]
|
||||
|
||||
## [2026-04-14] ingest | baoyu-skills
|
||||
- [[raw/Skills/baoyu-skills-claude-code-技能集.md]]
|
||||
|
||||
## [2026-04-14] ingest | Cursor 2.0初学者使用指南
|
||||
- [[raw/Vibe Coding/Cursor 2.0初学者使用指南.md]]
|
||||
|
||||
## [2026-04-14] ingest | Vibe-Kanban + OpenCode 在 Ubuntu Server 上安装与管理指南
|
||||
- [[raw/Vibe Coding/Vibe-Kanban + OpenCode 在 Ubuntu Server 上安装与管理指南.md]]
|
||||
|
||||
## [2026-04-14] ingest | vibe coding经验收集
|
||||
- [[raw/Vibe Coding/vibe coding经验收集.md]]
|
||||
|
||||
## [2026-04-14] ingest | 在Ubuntu 上安装Vibe-Kanban
|
||||
- [[raw/Vibe Coding/在Ubuntu上安装Vibe-Kanban.md]]
|
||||
|
||||
## [2026-04-14] ingest | 如何在Ubuntu上安装opencode并配置Vibe-Kanban
|
||||
- [[raw/Vibe Coding/如何在Ubuntu上安装opencode并配置Vibe-Kanban.md]]
|
||||
|
||||
## [2026-04-14] ingest | 如何在项目里安装Claude-Code-Templates Skills
|
||||
- [[raw/Vibe Coding/如何在项目里安装Claude-Code-Templates Skills.md]]
|
||||
|
||||
## [2026-04-14] ingest | 开发经验与项目规范整理文档
|
||||
- [[raw/Vibe Coding/开发经验与项目规范整理文档.md]]
|
||||
|
||||
## [2026-04-14] ingest | 不谈技术：普通人该怎么在AI时代赚钱？
|
||||
- [[raw/微信公众号/不谈技术：普通人该怎么在AI时代赚钱？.md]]
|
||||
|
||||
## [2026-04-14] ingest | 养虾日记1：我用 OpenClaw 管了 28 万张照片：一次真实的多设备照片整理实战
|
||||
- [[raw/微信公众号/养虾日记1：我用 OpenClaw 管了 28 万张照片：一次真实的多设备照片整理实战.md]]
|
||||
|
||||
## [2026-04-14] ingest | 养虾日记2：让Agent更懂你：OpenClaw + Self-Improving 复盘实战案例分享
|
||||
- [[raw/微信公众号/养虾日记2：让Agent更懂你：OpenClaw + Self-Improving 复盘实战案例分享.md]]
|
||||
|
||||
## [2026-04-14] ingest | 养虾日记3：用 Obsidian + Gitea 为 AI 助手构建持久化笔记系统
|
||||
- [[raw/微信公众号/养虾日记3：用 Obsidian + Gitea 为 AI 助手构建持久化笔记系统.md]]
|
||||
|
||||
## [2026-04-14] ingest | 一次「Context Limit Exceeded」错误排查：我以为是小问题，结果踩了大坑
|
||||
- [[raw/微信公众号/养虾日记4： 一次「Context Limit Exceeded」错误排查：我以为是小问题，结果踩了大坑.md]]
|
||||
|
||||
## [2026-04-14] ingest | 养虾日记5：深夜与苏轼聊AI，他说：被浪打下去还能爬起来的才叫风流
|
||||
- [[raw/微信公众号/养虾日记5：深夜与苏轼聊AI，他说：被浪打下去还能爬起来的才叫风流.md]]
|
||||
|
||||
## [2026-04-14] ingest | 养龙虾5天血泪史：我的AI Agent为什么总失忆？OpenClaw 记忆调试全记录
|
||||
- [[raw/微信公众号/养龙虾5天血泪史：我的AI Agent为什么总失忆？OpenClaw 记忆调试全记录.md]]
|
||||
|
||||
## [2026-04-14] ingest | ⚠️ 你使用 Docker，可能需要在 Dockerfile 里加入以下内容
|
||||
- [[raw/跨境电商/Scrapy + Playwright 抓取TikTok Shop Data.md]]
|
||||
|
||||
## [2026-04-14] ingest | TK美国面单授权及操作流程
|
||||
- [[raw/跨境电商/TK美国面单授权及操作流程.md]]
|
||||
|
||||
## [2026-04-14] ingest | 1. 你的数据库结构 → 适合做哪些分析？
|
||||
- [[raw/跨境电商/TikTok Shop - Apache Superset Dashboard设计思路.md]]
|
||||
|
||||
## [2026-04-14] ingest | 总结
|
||||
- [[raw/跨境电商/做TK跨境思路不对努力白费.md]]
|
||||
|
||||
## [2026-04-14] ingest | 概要
|
||||
- [[raw/跨境电商/电商如何选品 如何找到爆款 选品策略.md]]
|
||||
122
wiki/overview.md
122
wiki/overview.md
@@ -1,122 +0,0 @@
|
||||
# Overview
|
||||
|
||||
本Wiki涵盖两大核心领域：**Agent（智能体）系统**和**AI应用**。Agent系统以OpenClaw、N8N、MCP为核心；AI应用涵盖图像生成、配音克隆、视频制作、RAG检索等场景。
|
||||
|
||||
## 核心主题
|
||||
|
||||
### Agent系统
|
||||
- **OpenClaw**：开源AI Agent框架，支持多Agent协作、记忆系统、技能扩展
|
||||
- **N8N**：开源工作流自动化平台，可与AI Agent结合实现复杂自动化
|
||||
- **MCP (Modal Context Protocol)**：AI大模型与外围服务集成的协议
|
||||
- **多Agent系统**：多个专业Agent协同工作的架构模式
|
||||
|
||||
### AI应用
|
||||
- **图像生成**：Nano Banana、Midjourney等模型的提示词工程
|
||||
- **AI配音与声音克隆**：ElevenLabs、海螺AI、F5-TTS等工具
|
||||
- **视频制作**：固定镜头短视频AI全流程、九宫格法、首尾针动画
|
||||
- **RAG检索**：检索增强生成解决LLM幻觉问题
|
||||
|
||||
## 问题域
|
||||
|
||||
### Agent系统
|
||||
- Agent开发与配置（Workspace文件体系）
|
||||
- 工作流自动化（N8N节点和工作流）
|
||||
- 跨平台集成（Telegram、Discord、Slack等）
|
||||
- 个人效率提升（习惯追踪、日历管理、邮件处理）
|
||||
- 内容创作自动化（YouTube、Twitter、播客等）
|
||||
- 商业应用（CRM、市场研究、财报追踪）
|
||||
|
||||
### AI应用
|
||||
- 提示词工程：角色-需求-场景-目标四要素结构
|
||||
- 图像生成质量控制：物件描述框架、人物描述框架
|
||||
- 声音克隆与配音：多语言TTS、各平台特点
|
||||
- 视频内容创作：分镜拆解、一致性保证
|
||||
- 大模型知识体系：LLM、MCP、Agent、RAG、vLLM、Token
|
||||
|
||||
## 方法/机制
|
||||
|
||||
### Agent系统
|
||||
- **Workspace文件体系**（AGENTS.md、SOUL.md、USER.md等）：定义Agent行为
|
||||
- **Sub-agent多Agent协作**：分散式协调通过共享状态文件
|
||||
- **Cron定时任务与心跳机制**：自动化定期执行
|
||||
- **MCP协议工具调用**：Client-Server架构的服务集成
|
||||
- **Cursor集成调用**：支持SSE与Command模式的代理调用与推理工具链
|
||||
- **Webhook安全集成**：OpenClaw与N8N的安全集成模式
|
||||
- **向量语义搜索**：memsearch实现记忆的语义检索
|
||||
|
||||
### AI应用
|
||||
- **提示词框架**：物件描述、人物描述的JSON标准化结构
|
||||
- **Source-Grounding**：NotebookLM限制知识库确保回答准确性
|
||||
- **九宫格法**：一次性生成多个分镜保证画面一致性
|
||||
- **首尾针动画**：AI补齐中间帧实现平滑过渡
|
||||
- **RAG三步流程**：索引→检索→生成
|
||||
|
||||
## 关键实体
|
||||
|
||||
### Agent系统
|
||||
- [[OpenClaw]]：开源AI Agent框架
|
||||
- [[N8N]]：工作流自动化平台
|
||||
- [[MCP]]：模态上下文协议
|
||||
- [[Cursor]]：集成MCP的高级代码大模型编辑器
|
||||
- [[Smisery]]：热点新闻MCP服务数据源
|
||||
- [[DenchClaw]]：本地CRM框架
|
||||
- [[AionUi]]：桌面Cowork应用
|
||||
- [[Google]]：发布Agent Skill设计模式的云服务提供商
|
||||
- [[ClawdTalk]]：OpenClaw电话集成工具，实现语音交互
|
||||
|
||||
### AI应用
|
||||
- [[NotebookLM]]：Google AI学习工具
|
||||
- [[Nano Banana]]：Google AI图像生成模型
|
||||
- [[DeepSider]]：多AI模型聚合浏览器插件
|
||||
- [[ElevenLabs]]：国际AI配音平台
|
||||
- [[海螺AI]]：MiniMax出品的AI工具
|
||||
- [[F5-TTS]]：开源语音克隆项目
|
||||
- [[剪映]]：字节跳动视频编辑工具
|
||||
|
||||
## 关键概念
|
||||
|
||||
### Agent系统
|
||||
- [[Workspace]]：Agent的工作台目录配置体系
|
||||
- [[多Agent系统]]：多个专业Agent协同工作的架构
|
||||
- [[工作流自动化]]：使用工具自动执行重复性任务
|
||||
- [[记忆系统]]：Agent跨会话保留上下文的能力
|
||||
- [[技能系统]]：OpenClaw的扩展机制
|
||||
- [[Agent模式]]：模型自动执行工具命令的交互模式
|
||||
- [[AgentSkill设计模式]]：Google与Anthropic总结的5种Skill设计模式（ToolWrapper、Generator、Reviewer、Inversion、Pipeline）
|
||||
- [[SequentialThinking]]：大模型的逻辑推理任务分步拆解机制
|
||||
- [[n8n-mcp]]：N8N的MCP服务器实现
|
||||
- [[idea-reality-mcp]]：预构建创意验证MCP
|
||||
|
||||
### AI应用
|
||||
- [[Prompt能力]]：清晰界定需求+结构化思维表达
|
||||
- [[需求拆解]]：将模糊目标转化为具体可执行子任务
|
||||
- [[结构化表达]]：用清晰逻辑组织信息
|
||||
- [[思维链引导]]：让AI逐步推理
|
||||
- [[Source-Grounding]]：限制知识库确保AI回答准确性
|
||||
- [[音频概览]]：将文档转化为AI双人播客格式
|
||||
- [[提示词框架]]：结构化描述图像生成需求的模板
|
||||
- [[AI配音]]：文本转语音技术
|
||||
- [[声音克隆]]：用少量样本重建个人声音
|
||||
- [[固定机位]]：摄像机位置固定不变的拍摄方式
|
||||
- [[首尾针动画]]：通过首尾帧AI自动补齐中间动作
|
||||
- [[九宫格法]]：一次性生成3x3共九个分镜画面
|
||||
- [[RAG]]：检索增强生成
|
||||
- [[Embedding]]：将文本转换为数值向量的技术
|
||||
- [[LLM]]：大语言模型
|
||||
- [[Agent]]：智能体
|
||||
- [[vLLM]]：高效LLM推理框架
|
||||
- [[Token]]：大模型基本输入单元
|
||||
|
||||
## Source分类
|
||||
|
||||
### Agent系统（45个）
|
||||
涵盖：OpenClaw Workspace、N8N工作流、MCP协议、多Agent协作、记忆系统、技能扩展等
|
||||
|
||||
### AI应用（26个）
|
||||
涵盖：NotebookLM、Claude Skills、Nano Banana提示词、RAG基础、AI配音工具、视频制作流程、大模型术语等
|
||||
|
||||
## 来源分布
|
||||
- 微信公众号：Agent系统相关内容
|
||||
- YouTube视频：部分AI工具教程
|
||||
- OpenClaw Use Cases：37个
|
||||
- 技术文档：AI图像生成、RAG、提示词工程等
|
||||
@@ -1,47 +0,0 @@
|
||||
---
|
||||
title: "14个免费的AI图生视频工具"
|
||||
type: source
|
||||
tags: [AI, image-to-video, tools]
|
||||
date: 2025-12-05
|
||||
---
|
||||
|
||||
## Source File
|
||||
- [[raw/AI/14个免费的AI图生视频工具，用AI让图片动起来 - AI视频教程 AI自动化工作流定制服务 AI培训学习平台 黑喵大叔.md]]
|
||||
|
||||
## Summary
|
||||
- 核心主题：14个免费AI图生视频工具评测
|
||||
- 问题域：视频制作需要专业设备和技能，门槛高
|
||||
- 方法/机制：上传静态图片，AI分析内容并生成动态视频
|
||||
- 结论/价值：AI图生视频工具降低视频创作门槛，实现便捷创作
|
||||
|
||||
## Key Claims
|
||||
- 绘蛙AI视频（阿里）：模特图转视频，支持多格式高分辨率
|
||||
- 智谱清影：30秒生成6秒高清视频，支持音效匹配
|
||||
- 通义万相（阿里）：支持提示词控制运动，匹配音效
|
||||
- Vidu（清华）：全球首个"多主体参考"功能，10秒生成视频
|
||||
- 可灵AI（快手）：1080p分辨率，真实物理规律表现
|
||||
- 海螺AI（MiniMax）：主体一致性优秀，支持多种艺术风格
|
||||
|
||||
## Key Concepts
|
||||
- [[图生视频]]：将静态图片转化为动态视频的AI技术
|
||||
- [[主体一致性]]：视频中角色/物体保持一致的能力
|
||||
- [[运动控制]]：通过文本提示词控制视频中主体的运动方式
|
||||
|
||||
## Key Entities
|
||||
- [[绘蛙AI视频]]：阿里巴巴AI图生视频工具
|
||||
- [[智谱清影]]：智谱AI视频生成工具
|
||||
- [[通义万相]]：阿里巴巴AI视频生成工具
|
||||
- [[Vidu]]：生数科技与清华大学发布的视频大模型
|
||||
- [[可灵AI]]：快手AI创作平台
|
||||
- [[海螺AI]]：MiniMax推出的AI视频工具
|
||||
- [[即梦AI]]：字节跳动一站式AI创意创作平台
|
||||
- [[PixVerse]]：爱诗科技AI视频工具
|
||||
- [[Stable Video]]：Stability AI视频生成平台
|
||||
|
||||
## Connections
|
||||
- [[AI视频生成]] ← includes ← [[图生视频]]
|
||||
- [[阿里巴巴]] ← provides ← [[绘蛙AI视频]]
|
||||
- [[阿里巴巴]] ← provides ← [[通义万相]]
|
||||
- [[快手]] ← provides ← [[可灵AI]]
|
||||
|
||||
## Contradictions
|
||||
@@ -1,48 +0,0 @@
|
||||
---
|
||||
title: "2025年11个神级AI开源平替"
|
||||
type: source
|
||||
tags: [open-source, AI, GitHub]
|
||||
date: 2026-01-01
|
||||
---
|
||||
|
||||
## Source File
|
||||
- [[raw/AI/2025 年 11 个神级 AI 开源平替，GitHub 杀疯了。.md]]
|
||||
|
||||
## Summary
|
||||
- 核心主题：2025年GitHub热门AI开源项目盘点
|
||||
- 问题域：闭源AI产品价格昂贵，开源替代品需求旺盛
|
||||
- 方法/机制：按类别梳理各领域最火热的开源项目
|
||||
- 结论/价值：国产AI模型（DeepSeek、Qwen）在开源界表现亮眼
|
||||
|
||||
## Key Claims
|
||||
- 大语言模型：DeepSeek R1、Qwen 3为开源界标杆
|
||||
- AI生图：Flux（开源Midjourney）、Stable Diffusion（LoRA/ControlNet生态最丰富）
|
||||
- AI生视频：HunyuanVideo（腾讯）参数量最大，中文理解最强
|
||||
- 通用智能体：OpenManus（5万Star）为核心开源平替
|
||||
- AI Coding：Cline为Cursor最佳开源平替
|
||||
- 智能体工作流：n8n（16万Star）、Dify为最强开源项目
|
||||
|
||||
## Key Concepts
|
||||
- [[开源平替]]：开源替代闭源产品的方案
|
||||
- [[AI生图]]：开源模型Flux、Stable Diffusion
|
||||
- [[AI生视频]]：HunyuanVideo、Veo 3
|
||||
- [[AI智能体]]：Manus、OpenManus
|
||||
- [[AI编程]]：Cline、Claude Code
|
||||
|
||||
## Key Entities
|
||||
- [[DeepSeek]]：国产开源大模型
|
||||
- [[Qwen]]：通义千问开源模型
|
||||
- [[Flux]]：前SD团队开发的AI生图模型
|
||||
- [[HunyuanVideo]]：腾讯混元视频生成模型
|
||||
- [[OpenManus]]：通用智能体开源项目
|
||||
- [[Cline]]：VS Code AI编程插件
|
||||
- [[n8n]]：工作流自动化开源平台
|
||||
- [[Dify]]：LLM应用开发平台
|
||||
|
||||
## Connections
|
||||
- [[开源AI]] ← includes ← [[大语言模型]]
|
||||
- [[开源AI]] ← includes ← [[AI生图]]
|
||||
- [[开源AI]] ← includes ← [[AI生视频]]
|
||||
- [[GitHub]] ← hosts ← [[开源AI项目]]
|
||||
|
||||
## Contradictions
|
||||
@@ -1,41 +0,0 @@
|
||||
---
|
||||
title: "2025-03-02 日记"
|
||||
type: source
|
||||
tags: [diary]
|
||||
date: 2025-03-02
|
||||
---
|
||||
|
||||
## Source File
|
||||
- [[raw/Daily notes/2025-03-02.md]]
|
||||
|
||||
## Summary
|
||||
- 核心主题：AI Agent在工作场景中的应用探索
|
||||
- 问题域：Cloud DevOps中如何利用AI提升效率
|
||||
- 方法/机制：通过阅读LinkedIn文章和YouTube视频了解Agentic AI最新发展
|
||||
- 结论/价值：计划撰写Agentic AI在Cloud DevOps中的应用文章，探索Grafana数据喂给AI进行决策的可行性
|
||||
|
||||
## Key Claims
|
||||
- LinkedIn上有价值的Agentic AI文章值得系统整理并撰写文章分享
|
||||
- n8n可作为设计Agentic AI工作流的工具本地部署
|
||||
- Grafana监控数据可喂入AI Agent的向量数据库辅助决策
|
||||
- 告警机制可用于实时事件处理和自动创建工单
|
||||
|
||||
## Key Quotes
|
||||
> "Use data from Grafana to feed into an Agent's Vector DB so the AI can consume the data and help us make decisions."
|
||||
> "Use the alerting mechanism to handle incidents in real time, such as immediate notifications and direct incident creation."
|
||||
|
||||
## Key Concepts
|
||||
- [[Agentic AI]]：能够自主行动以达成目标的AI系统
|
||||
- [[VectorDB]]：向量数据库，用于存储和检索嵌入向量
|
||||
- [[Grafana]]：开源监控和可观测性平台
|
||||
|
||||
## Key Entities
|
||||
- [[OpenClaw]]：开源AI Agent框架
|
||||
- [[N8N]]：工作流自动化平台
|
||||
- [[DavidOndrej]]：YouTube内容创作者
|
||||
|
||||
## Connections
|
||||
- [[Agentic AI]] ← 应用场景 ← [[Grafana]]
|
||||
- [[N8N]] ← 用于构建 ← [[工作流自动化]]
|
||||
|
||||
## Contradictions
|
||||
@@ -1,36 +0,0 @@
|
||||
---
|
||||
title: "2025-03-04 日记"
|
||||
type: source
|
||||
tags: [diary]
|
||||
date: 2025-03-04
|
||||
---
|
||||
|
||||
## Source File
|
||||
- [[raw/Daily notes/2025-03-04.md]]
|
||||
|
||||
## Summary
|
||||
- 核心主题：利用现有数据构建AI模型支持
|
||||
- 问题域：如何将运营数据转化为AI可用的标准化数据集
|
||||
- 方法/机制：通过与Jackie Ye讨论，确定了利用监控数据、标准化指标、阈值和运行手册构建数据集的路径
|
||||
- 结论/价值：AI驱动的情感分析、工单自动分配和解决方案建议是三个可行的PoC方向
|
||||
|
||||
## Key Claims
|
||||
- 现有的监控数据、标准化指标和阈值可作为AI模型训练的基础
|
||||
- 客户工单情感分析可帮助Customer Success Managers优化策略
|
||||
- AI可实现工单自动分配和历史方案推荐
|
||||
|
||||
## Key Quotes
|
||||
> "We need well-structured and mature datasets to support future development and implementation."
|
||||
|
||||
## Key Concepts
|
||||
- [[标准化数据集]]：结构化、可复用的数据集合
|
||||
- [[PoC]]：概念验证
|
||||
|
||||
## Key Entities
|
||||
- [[Jackie Ye]]：Cloud Ops团队成员
|
||||
|
||||
## Connections
|
||||
- [[标准化数据集]] ← 基础 ← [[监控数据]]
|
||||
- [[情感分析]] ← 应用场景 ← [[客户工单]]
|
||||
|
||||
## Contradictions
|
||||
@@ -1,37 +0,0 @@
|
||||
---
|
||||
title: "2025-03-05 日记"
|
||||
type: source
|
||||
tags: [diary]
|
||||
date: 2025-03-05
|
||||
---
|
||||
|
||||
## Source File
|
||||
- [[raw/Daily notes/2025-03-05.md]]
|
||||
|
||||
## Summary
|
||||
- 核心主题：AI Agent构建学习和n8n实践
|
||||
- 问题域：如何快速入门AI Agent开发
|
||||
- 方法/机制：观看YouTube视频学习CrewAI框架，使用NoteGPT提取YouTube字幕并用DeepSeek-R1总结
|
||||
- 结论/价值：CrewAI是初学者入门的好选择，建议从小项目开始逐步迭代
|
||||
|
||||
## Key Claims
|
||||
- CrewAI是适合初学者的AI Agent开发框架
|
||||
- 可以使用Google Colab进行无代码配置
|
||||
- 应从自动化重复任务开始，逐步构建复杂工作流
|
||||
|
||||
## Key Quotes
|
||||
> "Start Small: Automate repetitive tasks (e.g., daily research) before tackling complex workflows."
|
||||
|
||||
## Key Concepts
|
||||
- [[CrewAI]]：开源AI Agent框架
|
||||
- [[Agent模式]]：模型自动执行工具命令的交互模式
|
||||
|
||||
## Key Entities
|
||||
- [[CrewAI]]：AI Agent开发框架
|
||||
- [[DeepSeek-R1]]：DeepSeek推理模型
|
||||
|
||||
## Connections
|
||||
- [[CrewAI]] ← 用于构建 ← [[AI Agent]]
|
||||
- [[DeepSeek-R1]] ← 用于 ← [[内容总结]]
|
||||
|
||||
## Contradictions
|
||||
@@ -1,37 +0,0 @@
|
||||
---
|
||||
title: "2025-03-10 日记"
|
||||
type: source
|
||||
tags: [diary]
|
||||
date: 2025-03-10
|
||||
---
|
||||
|
||||
## Source File
|
||||
- [[raw/Daily notes/2025-03-10.md]]
|
||||
|
||||
## Summary
|
||||
- 核心主题：N8N工作流配置与应用
|
||||
- 问题域：实现自动化内容生成和发布
|
||||
- 方法/机制：配置n8n实现工作流备份、AI生成社交媒体内容、RSS翻译推送
|
||||
- 结论/价值：成功配置三个n8n工作流，覆盖备份、内容生成和RSS翻译场景
|
||||
|
||||
## Key Claims
|
||||
- n8n可实现工作流自动备份到Google Drive
|
||||
- AI可基于关键词生成社交媒体内容并自动发布
|
||||
- RSS Feed可结合AI实现实时翻译并推送至Telegram
|
||||
|
||||
## Key Quotes
|
||||
> "AI-Powered Social Media Content Generator & Publisher"
|
||||
|
||||
## Key Concepts
|
||||
- [[工作流自动化]]：使用工具自动执行重复性任务
|
||||
- [[RSS]]：Really Simple Syndication，信息聚合标准
|
||||
|
||||
## Key Entities
|
||||
- [[N8N]]：工作流自动化平台
|
||||
- [[Google Drive]]：云存储服务
|
||||
|
||||
## Connections
|
||||
- [[N8N]] ← 实现 ← [[工作流自动化]]
|
||||
- [[RSS]] ← 触发 ← [[AI翻译]]
|
||||
|
||||
## Contradictions
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user