Batch 12 continued: Health Symptom Tracker + Inbox De-clutter + Podcast Production Pipeline
This commit is contained in:
38
wiki/concepts/健康追踪.md
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wiki/concepts/健康追踪.md
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---
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title: "健康追踪"
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type: concept
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tags: [health, automation, logging]
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last_updated: 2026-04-16
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---
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## Definition
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通过持续记录食物、症状和行为数据,识别健康模式与潜在触发因素的系统性方法。
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## Core Components
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1. **输入层**:对话式 Telegram 消息 → 自动解析为结构化数据
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2. **存储层**:Markdown 日志文件(带时间戳)
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3. **提醒层**:Cron 驱动的每日固定时间主动提醒
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4. **分析层**:周度模式分析 → 关联性识别
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## Key Characteristics
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- 对话式输入 vs App 式手动记录(摩擦最小化)
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- 时间序列分析识别触发因素
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- 持续优化的个人知识库(已知触发因素记忆)
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## Related Concepts
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- [[模式识别]]:数据分析层面的通用能力
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- [[定时晨报]]:Cron 驱动机制的另一个应用场景
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## Example
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```
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每日 3 次提醒:
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- 8 AM:早餐记录
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- 1 PM:午餐记录
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- 7 PM:晚餐+症状记录
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周日分析:
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- 哪些食物与症状相关?
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- 时间段规律?
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- 明确触发因素?
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```
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35
wiki/concepts/嘉宾研究.md
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wiki/concepts/嘉宾研究.md
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---
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title: "嘉宾研究"
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type: concept
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tags: [podcast, research, content-preparation]
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last_updated: 2026-04-16
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---
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## Definition
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播客录制前对嘉宾背景、近期动态、观点立场的系统性深度调研,是提升访谈质量的核心准备工作。
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## Research Dimensions
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1. **背景研究**:教育、职业、主要成就
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2. **近期动态**:最近的项目、发言、争议
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3. **观点立场**:核心主张、独特视角、争议性话题
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4. **受众预判**:听众已知的 vs 可能惊讶的
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## Value
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- 深度研究使访谈质量产生质的飞跃(无法在后期伪造)
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- 好的研究 → 好的问题 → 好的对话
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- 准备充分才能即兴发挥
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## Related Concepts
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- [[Podcast Production Pipeline]]:嘉宾研究是生产管线第一环节
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- [[内容工厂]]:研究 Agent 可独立并行执行
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## Example Research Output
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```
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嘉宾:[NAME]
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- 背景:...
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- 近期动态:...
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- 潜在争议点:...
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- 3个核心问题:...
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- 备用问题:...
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```
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wiki/entities/Apple-Podcasts.md
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wiki/entities/Apple-Podcasts.md
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---
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title: "Apple Podcasts"
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type: entity
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tags: [podcast, platform, apple]
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last_updated: 2026-04-16
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---
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## Basic Info
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- **Type**: Podcast Platform
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- **Company**: Apple
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- **Function**: iOS/macOS 原生播客应用与分发平台
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## Description
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Apple Podcasts 是苹果生态下的播客发现与播放平台,拥有庞大的忠实用户群。播客 SEO 描述优化通常以 Apple Podcasts 为标准。
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## Connections
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- [[Apple Podcasts]] ← targets ← [[Podcast Production Pipeline]]
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## Aliases
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- Apple Podcasts
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- Podcasts (iOS)
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- Apple Podcasts Connect
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wiki/entities/Spotify.md
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wiki/entities/Spotify.md
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---
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title: "Spotify"
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type: entity
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tags: [podcast, platform, streaming]
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last_updated: 2026-04-16
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---
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## Basic Info
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- **Type**: Podcast / Music Streaming Platform
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- **Company**: Spotify AB
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- **Function**: 播客分发与托管平台
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## Description
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Spotify for Podcasters 提供播客节目管理、数据分析、听众统计等功能。播客创作者重要的分发渠道之一。
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## Connections
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- [[Spotify]] ← hosts ← [[Podcast Production Pipeline]]
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## Aliases
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- Spotify
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- Spotify for Podcasters
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- Spotify Podcasting
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wiki/entities/Whisper.md
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wiki/entities/Whisper.md
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---
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title: "Whisper"
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type: entity
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tags: [ai, speech-to-text, openai, transcription]
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last_updated: 2026-04-16
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---
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## Basic Info
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- **Type**: AI Model / Open Source
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- **Provider**: OpenAI
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- **Function**: 语音转文字(Speech-to-Text) transcription
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## Description
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Whisper 是 OpenAI 开源的语音识别模型,支持多语言转录。本地运行,无需 API 调用费用。
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## Use Cases
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- 播客录音转文字脚本
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- 会议记录自动生成
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- YouTube 视频字幕提取
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## Connections
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- [[Whisper]] ← used_in ← [[Podcast Production Pipeline]]
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- [[Whisper]] ← alternative_to ← [[OpenAI Whisper API]]
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## Aliases
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- Whisper
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- OpenAI Whisper
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- whisper.cpp
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@@ -3,6 +3,16 @@
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## Overview
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- [Overview](overview.md) — living synthesis
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## Sources (2026-04-16 Batch 12 continued)
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- [Health & Symptom Tracker](sources/Health-Symptom-Tracker.md) — OpenClaw Telegram 对话式健康追踪:每日3次 Cron 提醒 + Markdown 日志 + 周度模式分析识别食物触发因素
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- [Inbox De-clutter](sources/Inbox-De-clutter.md) — OpenClaw Gmail 新闻简报自动化:OAuth 读取 + LLM 摘要生成 + 偏好记忆持续优化
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- [Podcast Production Pipeline](sources/Podcast-Production-Pipeline.md) — 多 Agent 链式协作播客生产管线:预录制研究→大纲生成→录制后 Show Notes→社媒工具包
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## Sources (2026-04-16 Batch 12)
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- [n8n Telegram Trigger HTTPS 配置修复](sources/n8n-Telegram-Trigger-HTTPS配置修复.md) — n8n Telegram Trigger 必须使用 HTTPS Webhook URL;设置 `WEBHOOK_URL` 环境变量解决 "Bad Request: bad webhook" 报错
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- [n8n Docker 安装与 SOCKS5 代理配置](sources/n8n-Docker安装与SOCKS5代理配置.md) — n8n Docker 部署配置:自定义 Dockerfile 安装 curl/wget;`ALL_PROXY=socks5://172.21.0.1:10808` 路由容器流量经宿主机代理访问 AI API
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- [N8N AI Agent 2025 入门教程](sources/n8n-AI-Agent-2025入门教程.md) — N8N AI Agent 零基础入门:Workflow(预定义)vs Agent(LLM动态决策);5类节点;Memory 机制;Airtable 工具接入
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## Sources (2026-04-16 Batch 11)
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- [arXiv Paper Reader](sources/arXiv-Paper-Reader.md) — OpenClaw Agent 论文阅读助手:Prismer arxiv-reader skill(3 工具:fetch/sections/abstract)+ LaTeX 源码自动展平 + 多篇对比表格 + 本地缓存
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- [Custom Morning Brief](sources/Custom-Morning-Brief.md) — OpenClaw 定时晨报工作流:新闻+待办+AI主动推荐任务,夜间待机时间转化为制作时间,起床即可看到完整脚本
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@@ -151,6 +161,14 @@
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- [养虾日记1:用 OpenClaw 管了 28 万张照片](sources/养虾日记1-OpenClaw照片整理实战.md) — OpenClaw AI Agent 照片整理实战:MD5 精确去重、小文件清理、分 8 批次凌晨执行、Telegram 报告
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- [不谈技术:普通人该怎么在AI时代赚钱](sources/普通人如何在AI时代赚钱.md) — AI 时代赚钱三原则:品味是护城河、端到端优于零件、死亡过滤器筛选真正热爱
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## Entities (2026-04-16 Batch 12 continued)
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- [Spotify](entities/Spotify.md) — 播客分发与托管平台,Spotify for Podcasters 后台管理
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- [Apple Podcasts](entities/Apple-Podcasts.md) — 苹果生态播客平台,SEO 播客描述优化标准
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- [Whisper](entities/Whisper.md) — OpenAI 开源语音转文字模型,本地转录无 API 费用
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## Entities (2026-04-16 Batch 12)
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- [Telegram](entities/Telegram.md) — 即时通讯平台,Bot API 支持 Webhook 回调;n8n Telegram Trigger 节点集成
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## Entities (2026-04-16 Batch 7)
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- [Kira2red](entities/Kira2red.md) — AI产品管理实践者,Gemini工作流方法论作者
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- [ElevenLabs](entities/ElevenLabs.md) — 国际顶流AI配音工具,30+语言,情感语音生成,声音克隆
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@@ -574,6 +592,14 @@
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- [SOCKS5 代理](concepts/SOCKS5代理.md) — socks5 vs socks5h vs HTTP 代理对比;代理服务器 DNS 解析防止污染
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- [Docker Daemon 代理](concepts/Docker-Daemon代理.md) — systemd 环境变量注入;docker info 验证;vs 容器内应用代理
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## Concepts (2026-04-16 Batch 12 continued)
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- [健康追踪](concepts/健康追踪.md) — Telegram 对话式持续记录食物与症状,Cron 每日 3 次提醒,周度模式分析识别触发因素
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- [嘉宾研究](concepts/嘉宾研究.md) — 播客录制前深度调研嘉宾背景/近期动态/观点立场,是提升访谈质量的核心准备
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## Concepts (2026-04-16 Batch 12)
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- [Telegram Webhook](concepts/Telegram-Webhook.md) — Telegram Bot 回调机制,HTTP POST 推送用户消息;强制 HTTPS 要求;5秒响应时间限制
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- [WEBHOOK_URL](concepts/WEBHOOK_URL.md) — n8n 环境变量,指定公网 HTTPS Webhook 地址;解决 Telegram Webhook HTTPS 报错
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## Concepts (2026-04-16 Batch 10)
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- [任务-笔记一体化](concepts/任务-笔记一体化.md) — 任务与笔记不是分离系统,任务是有截止日期和优先级的笔记段落;Obsidian Tasks 插件实现工具层融合
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- [系统提示词](concepts/系统提示词.md) — 定义 AI Agent 核心身份和行为准则的顶层 prompt;5 层架构(身份/沟通/执行/技术规范/安全防护);行为可预期性设计原则
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12
wiki/log.md
12
wiki/log.md
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## [2026-04-16 Batch 12 continued] ingest | 3 sources — Health Tracker + Inbox De-clutter + Podcast Production Pipeline
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- Health & Symptom Tracker:Telegram 对话式健康追踪,每日 3 次 Cron 提醒 + Markdown 日志 + 周度模式分析识别食物触发因素
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- Inbox De-clutter:Gmail 新闻简报自动化,OAuth 读取 + LLM 摘要生成 + 偏好记忆持续优化
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- Podcast Production Pipeline:多 Agent 链式协作播客生产管线,预录制研究→大纲生成→录制后 Show Notes→社媒工具包
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- Created: 3 entities (Spotify, Apple Podcasts, Whisper), 2 concepts (健康追踪, 嘉宾研究)
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## [2026-04-16 Batch 8] ingest | 3 sources — Agentic AI 设计 + LLM/RAG/Agent 架构 + DevOps 成熟度
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- Designing for Agentic AI:Agentic AI 五大 UX 设计原则(透明度/控制权/个性化/对话/预判);与 GenAI 的本质区别——主动行动 vs 被动响应内容创作
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- LLMs、RAG、AI Agent 三个到底什么区别?:LLM(天才大脑/思考)→ RAG(随身图书馆助理/信息)→ AI Agent(行动者/执行)三层架构;真正生产系统叠加三者——LLM推理、RAG确保准确性、Agent框架实现自主性
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@@ -396,3 +402,9 @@ Created: 3 source pages, 3 entity pages (LaunchDarkly, HP, Christian Dior), 5 co
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||||
- Event Guest Confirmation:SuperCall AI 外呼确认活动出席;GPT-4o Realtime + Twilio 批量拨号;沙箱化 Persona 隔离每通电话防止数据泄露;无跨对话记忆
|
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- Daily Reddit Digest:reddit-readonly skill + 内容偏好记忆 + 每日下午 5 点定时推送;Read-only 模式只读不互动;AI 随时间优化 digest 质量
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||||
- Created: 3 new entities (SuperCall, Twilio, reddit-readonly), 7 new concepts (LaTeX Flattening, 定时主动任务, 晨报自动化, AI推荐任务, AI外呼确认, 沙箱化 Persona, Reddit内容聚合, 内容偏好记忆, Read-only API)
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## Batch 12 (2026-04-16 08:00 CST) - 3 docs
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- n8n Telegram Trigger HTTPS 配置修复:Telegram Webhook 强制 HTTPS 要求;WEBHOOK_URL 环境变量解决 "Bad Request: bad webhook" 报错
|
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- n8n Docker 安装与 SOCKS5 代理配置:ALL_PROXY=socks5://172.21.0.1:10808 将容器流量路由到宿主机 V2Ray 代理访问 AI API
|
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- N8N AI Agent 2025 入门教程:Workflow(预定义固定路径)vs Agent(LLM 动态决策);Memory 机制;Airtable 工具接入
|
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- Created: 1 new entity (Telegram), 2 new concepts (Telegram Webhook, WEBHOOK_URL)
|
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|
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36
wiki/sources/Health-Symptom-Tracker.md
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36
wiki/sources/Health-Symptom-Tracker.md
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---
|
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title: "Health & Symptom Tracker"
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type: source
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tags: [health, automation, telegram, cron]
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date: 2026-04-16
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---
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## Source File
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- [[raw/Agent/usecases/health-symptom-tracker.md]]
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## Summary
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- 核心主题:基于 Telegram 的个人健康与症状追踪自动化工作流
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- 问题域:食物敏感性识别需要长期持续记录,用户难以坚持手动日志
|
||||
- 方法/机制:Telegram 话题 + OpenClaw Cron 提醒 + Markdown 日志 + 周分析
|
||||
- 结论/价值:用最低摩擦的对话式输入替代 App,OpenClaw 自动解析+模式分析
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|
||||
## Key Claims
|
||||
- Telegram 话题消息可作为结构化健康日志输入源
|
||||
- 每日 3 次定时提醒(早/中/晚)可培养用户记录习惯
|
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- 周度模式分析能识别食物与症状的关联性
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||||
|
||||
## Key Concepts
|
||||
- [[健康追踪]]:通过对话式界面持续记录食物与症状,替代专用 App
|
||||
- [[模式识别]]:基于时间序列分析识别触发因素
|
||||
- [[定时晨报]]:OpenClaw Cron 驱动的固定时间主动提醒机制
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||||
## Key Entities
|
||||
- [[Telegram]]:消息接收通道,支持话题(Topic)隔离不同类型对话
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||||
## Connections
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- [[Health Symptom Tracker]] ← extends ← [[定时晨报]]
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- [[Health Symptom Tracker]] ← uses ← [[Telegram]]
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- [[健康追踪]] ← relates_to ← [[模式识别]]
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||||
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||||
## Contradictions
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||||
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36
wiki/sources/Inbox-De-clutter.md
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36
wiki/sources/Inbox-De-clutter.md
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---
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title: "Inbox De-clutter"
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type: source
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tags: [email, gmail, automation, newsletter, cron]
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||||
date: 2026-04-16
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||||
---
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||||
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||||
## Source File
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- [[raw/Agent/usecases/inbox-declutter.md]]
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||||
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||||
## Summary
|
||||
- 核心主题:使用 OpenClaw AI Agent 自动整理 Gmail 新闻简报收件箱
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||||
- 问题域:新闻简报堆积导致重要邮件被淹没,人工筛选耗时
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||||
- 方法/机制:Gmail OAuth 读取 + LLM 摘要生成 + 偏好记忆 + Cron 定时执行
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||||
- 结论/价值:将 0 价值的邮箱浏览转化为 5 分钟高效摘要,建立在个人偏好基础上持续优化的闭环
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||||
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||||
## Key Claims
|
||||
- 新闻简报聚合阅读比逐封浏览信息密度更高、效率更高
|
||||
- AI 摘要 + 反馈闭环可建立个性化内容筛选模型
|
||||
- 专用邮箱隔离策略可简化管理并提升摘要质量
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||||
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||||
## Key Concepts
|
||||
- [[邮箱分类]]:Gmail 自动标签标注、归档噪音、待处理项识别
|
||||
- [[多平台热点聚合]]:结构化趋势研究方法论的变体(邮件领域)
|
||||
- [[偏好记忆]]:基于用户反馈持续优化下一次输出质量
|
||||
|
||||
## Key Entities
|
||||
- [[Gmail]]:Google 邮件服务平台,支持 OAuth API 访问
|
||||
|
||||
## Connections
|
||||
- [[Inbox De-clutter]] ← extends ← [[定时晨报]]
|
||||
- [[Inbox De-clutter]] ← uses ← [[Gmail]]
|
||||
- [[邮箱分类]] ← relates_to ← [[偏好记忆]]
|
||||
|
||||
## Contradictions
|
||||
|
||||
46
wiki/sources/Podcast-Production-Pipeline.md
Normal file
46
wiki/sources/Podcast-Production-Pipeline.md
Normal file
@@ -0,0 +1,46 @@
|
||||
---
|
||||
title: "Podcast Production Pipeline"
|
||||
type: source
|
||||
tags: [podcast, content-automation, multi-agent, ai-workflow]
|
||||
date: 2026-04-16
|
||||
---
|
||||
|
||||
## Source File
|
||||
- [[raw/Agent/usecases/podcast-production-pipeline.md]]
|
||||
|
||||
## Summary
|
||||
- 核心主题:多 Agent 链式协作的播客全流程生产管线
|
||||
- 问题域:播客制作中非录制环节(研究/大纲/笔记/推广)占 70% 工作量,单人难以坚持
|
||||
- 方法/机制:预录制研究 Agent → 大纲生成 → 录制后摘要/Show Notes → 社媒工具包
|
||||
- 结论/价值:将播客生产从手工业转化为流水线,大幅降低运营负担,保留创作核心价值
|
||||
|
||||
## Key Claims
|
||||
- 预录制深度研究是最大价值点,嘉宾访谈质量直接由准备深度决定
|
||||
- 时间戳 Show Notes 是高用户留存工具,大多数播客制作者因繁琐而跳过
|
||||
- 社交媒体工具包是最可自动化的重复性工作,每期结构一致
|
||||
|
||||
## Key Quotes
|
||||
> "Research takes hours, show notes are an afterthought, and social media promotion is the first thing that gets skipped. The creative part — the conversation — is maybe 30% of the total effort." — 内容分析
|
||||
|
||||
## Key Concepts
|
||||
- [[内容工厂]]:多 Agent 链式协作内容创作管线的变体(播客垂直领域)
|
||||
- [[多代理并行]]:研究与写作 Agent 可并行执行提升效率
|
||||
- [[RSS Feed]]:竞品播客监控的标准化订阅协议
|
||||
- [[内容矩阵]]:一次长内容(播客)切多格式(推文/领英/Ins)分发
|
||||
- [[嘉宾研究]]:嘉宾背景/近期动态/争议观点的深度挖掘
|
||||
|
||||
## Key Entities
|
||||
- [[Spotify]]:播客分发平台,Podcasters 后台管理
|
||||
- [[Apple Podcasts]]:播客分发平台,SEO 描述优化目标
|
||||
- [[YouTube]]:播客视频化分发平台
|
||||
- [[Whisper]]:OpenAI 开源语音转文字模型,本地化转录
|
||||
|
||||
## Connections
|
||||
- [[Podcast Production Pipeline]] ← extends ← [[内容工厂]]
|
||||
- [[Podcast Production Pipeline]] ← uses ← [[多代理并行]]
|
||||
- [[Podcast Production Pipeline]] ← uses ← [[RSS Feed]]
|
||||
- [[Podcast Production Pipeline]] ← produces ← [[内容矩阵]]
|
||||
- [[Show Notes 生成]] ← relates_to ← [[嘉宾研究]]
|
||||
|
||||
## Contradictions
|
||||
|
||||
Reference in New Issue
Block a user