Skill: chunhualiao/openclaw-usecase-catalog (version 1.0.0)

--- name: usecase-catalog description: "Comprehensive catalog of what people are doing with OpenClaw. Covers 15+ categories with real examples, sources, and inspiration. Use when asked about OpenClaw use cases, what others are building, project ideas, or 'what can OpenClaw do'. Triggers on: use cases, ideas, inspiration, what people do, showcase, examples." --- # OpenClaw Use Cases Catalog A curated reference of real-world OpenClaw use cases gathered from Twitter/X, Reddit, blogs, GitHub, and community showcases. Updated 2026-02-04. ## How to Use When My Lord asks about use cases or wants inspiration: 1. Reference the catalog below and `findings/` directory for past discoveries 2. Search the web for fresh examples (Twitter/X, Reddit, Discord, blogs) 3. Save new findings to `findings/YYYY-MM-DD.md` with structured format 4. Git commit and push to `{github_org}/openclaw-skill-usecases` ### Saving Findings (Bilingual) After each invocation that discovers new use cases, append to (or create) `findings/YYYY-MM-DD.md`. **All findings MUST be bilingual** — write both Chinese and English in the same entry. Chinese first, then English. This makes it easier for My Lord to read in his native language while keeping English for reference and searchability. ```markdown # Findings / 发现 - YYYY-MM-DD ## HH:MM PST ### [中文标题] / [English Title] — [Category/类别] - **来源/Source**: [URL or @handle] - **平台/Platform**: [WhatsApp/Telegram/Discord/etc.] - **描述/Description**: - 🇨🇳 中文描述 - 🇺🇸 English description - **亮点/Why interesting**: - 🇨🇳 中文说明为什么有趣 - 🇺🇸 English explanation of why it's notable ``` Then commit and push: ```bash cd /path/to/skills/openclaw-usecases git add findings/ && git commit -m "findings: YYYY-MM-DD" && git push ``` --- ## 1. Messaging & Communication Automation - **Inbox Zero**: Scan emails, archive spam, summarize high-priority items into daily morning briefings. Auto-create Gmail filters. (@andrewjiang: "Helped me clean up hundreds of emails. Inbox 0. Then setup a weekly cron job. All on WhatsApp.") - **iMessage/SMS Monitoring**: Scan text threads every 15 min, detect promises ("I'll review this tomorrow"), auto-create calendar holds. (@brandon.wang) - **Group Chat Summarization**: Daily summaries of high-volume WhatsApp/Signal groups (100+ msgs/day). Pick out interesting topics, skip noise. - **Auto-Reply Drafting**: Draft email/message responses for review before sending. ## 2. Calendar & Scheduling - **Morning Briefings**: 8pm nightly summary of next day's calendar -- meetings, prep notes, commute times. (@benemredoganer: "Daily calendar briefs, creates tasks in Basecamp via voice, preps me for meetings.") - **Smart Conflict Detection**: When texting plans, auto-create "hold" events on calendar to prevent double-booking. - **Dentist/Doctor Booking**: Log into portal, find slots matching calendar availability + location proximity, confirm before booking. (@brandon.wang) - **Cross-Calendar Intersection**: Check both partners' calendars to find mutual free evenings for dinner reservations. ## 3. Remote Coding & Development - **Phone-Based Development**: Build and deploy code projects from WhatsApp/Telegram while on the go. (@christinetyip) - **Site Rebuilds from Bed**: Full website migration (Notion to Astro, 18 posts, DNS to Cloudflare) via Telegram while watching Netflix. (@davekiss) - **Auto-Deployment**: "Deploy the latest commit to staging" -- runs git commands, SSH scripts, handles the pipeline. - **Code Refactoring**: Scan directories, identify messy code, propose refactored versions. - **Server Monitoring**: Periodic htop/disk checks, alert via Telegram when under load. - **GitHub Workflow**: Manage Issues, PRs, CI runs, auto-assign/label/close via webhooks. ## 4. Price Monitoring & Shopping - **Complex Price Alerts**: 30+ simultaneous alerts on hotels, Airbnbs, products. Supports reasoning criteria like "pullout bed OK if not in same room as another bed." Reviews listing photos to verify. (@brandon.wang) - **Hotel/Airbnb Tracking**: Check prices every few hours, notify on changes. Can evaluate subjective criteria (room vibe, renovation quality). - **Package Tracking**: USPS/FedEx tracking numbers, daily progress updates, flags stuck-in-transit items. - **Grocery Price Comparison**: Compare prices on Amazon via browser automation, suggest best options. ## 5. Smart Home & IoT - **Home Assistant Integration**: Full-home smart control via natural language. (@WolframRvnwlf: "OpenClaw truly is next level... my sassy AI assistant Amy is finally running persistently on my Home Assistant box.") - **Air Purifier / Device Control**: Discover and control Winix, Philips Hue, Elgato devices. (@antonplex) - **Scene Automation**: Away/Home/Sleep modes -- lights, AC, security based on WiFi proximity and sleep data. - **Complete Life Integration**: Emails + Home Assistant + homelab SSH + todo lists + shopping list, all via single Telegram chat. (@acevail_) ## 6. Restaurant & Booking - **Resy/OpenTable Automation**: Log in (including 2FA from texts), browse availability page by page, intersect with your + partner's calendar, suggest options. (@brandon.wang) - **Form Filling**: Fill out vendor forms, questionnaires. Workshopes answers back and forth, unchecks marketing emails automatically. - **Flight Check-in**: Auto check-in for flights, generate packing lists based on destination weather. ## 7. Health & Fitness Tracking - **Fitness Coach**: Analyze Garmin/Apple Health data. "You only slept 5 hours last night; maybe skip heavy cardio today." - **Medical Lab Analysis**: Feed blood test PDFs for plain-English explanations. - **Wearable Data Dashboard**: Steps, sleep quality, heart rate summaries on demand. ## 8. Household & Life Management - **Freezer Inventory**: Take photos of freezer contents, AI parses items/quantities, updates Notion list, removes stocked items from grocery list. (@brandon.wang) - **Grocery List from Recipes**: Screenshot a recipe, ingredients auto-organized into Apple Reminders. Dedupes and combines ("2 carrots becomes 3"). - **Todo Creation with Context**: Photo of running shoes at REI -> todo with brand, model, size, product URL auto-found. - **Travel Planning**: Search flights, generate packing lists based on weather, book accommodations. ## 9. Digital Agency / Business - **One-Person Agency**: AI "Chief of Staff" coordinating all ops -- SEO client monitoring, email triage, content creation, Shopify management, overnight PRs for morning review. (@openclaw.com.au) - **Project Management**: Connect code, Linear, WhatsApp history, and Obsidian for seamless PM workflow. (@crossiBuilds) - **Content Creation Pipeline**: Blog posts, meta descriptions, reports, social media content. - **24/7 Accountability Partner**: Daily reminders, GitHub tracking, weekly accountability nudges for goals. (@tobi_bsf) ## 10. AI Phone & Voice - **Phone Call Assistant**: Make and receive phone calls on your behalf. (@steipete) - **Voice-to-Text Processing**: Transcribe voice messages, act on content. - **Voice-Controlled Tasks**: Create tasks in Basecamp via voice commands. ## 11. Full-Stack Productivity Hub - **Single Chat Command Center**: Control Gmail, Calendar, WordPress, Hetzner servers from Telegram. (@Abhay08: "controlling Gmail, Calendar, WordPress, Hetzner from Telegram like a boss.") - **Perfect Memory Assistant**: Remembers everything across all conversations, learns preferences over time. (@darrwalk) - **Workflow Self-Documentation**: Auto-writes human-readable workflow descriptions to Notion with version control diffs. (@brandon.wang) ## 12. Self-Creating Skills & Integrations - **On-Demand Skill Creation**: "I wanted to automate Todoist and OpenClaw created a skill for it on its own, all within Telegram." (@iamsubhrajyoti) - **ClawHub Ecosystem**: 3,000+ community skills on clawhub.ai. 1,715+ curated in awesome-openclaw-skills repo. - **Category Breakdown**: Web/Frontend (46), Coding Agents (55), Git/GitHub (34), DevOps/Cloud (144), Browser Automation (69), Image/Video (41), Apple Apps (32), Search/Research (148), CLI Utilities (88), Marketing/Sales (94), Productivity (93), AI/LLMs (159), Notes/PKM (61), Smart Home (50), Communication (58), Speech (44), Health/Fitness (35), Shopping (33), Calendar (28), PDF/Documents (35), Security (21), Gaming (7). ## 13. Content & Media - **WeChat公众号 Article Illustration**: Auto-generate scrapbook-style infographics for articles using GPT-4o or GLM-Image. (Our own suwin-illustrator skill) - **YouTube Transcription**: yt-dlp + Whisper API for video transcription and note-taking. - **News Aggregation**: Aggregate 8+ sources (Hacker News, GitHub Trending, Product Hunt). Daily tech briefings. - **Podcast Summarization**: Extract transcripts and key points from audio content. - **Remotion Video**: Programmatic video creation with React + Remotion framework. ## 14. AI-Powered Research - **Deep Research**: Multi-source web research, synthesized reports. - **Academic Paper Analysis**: Parse PDFs, explain findings, compare methodologies. - **Competitive Intelligence**: Monitor competitor websites, pricing changes, product updates. ## 15. Security & Privacy - **Local-First Architecture**: All data stored locally, keys never sent to third parties. - **Docker Isolation**: Sandboxed execution prevents system damage. - **Human-in-the-Loop**: Sensitive commands require explicit approval. - **Dedicated Account Strategy**: Use burner accounts for integrations to limit blast radius. --- ## Sources | Source | URL | |--------|-----| | Official Showcase | getclawdbot.com/showcase | | OpenClaw Wiki | openclawwiki.org/blog/openclaw_clawdbot-usage-use-cases | | Medium (10 Use Cases) | medium.com/@balazskocsis/10-clawdbot-use-cases | | Brandon Wang Deep Dive | brandon.wang/2026/clawdbot | | Awesome Skills (1715+) | github.com/VoltAgent/awesome-openclaw-skills | | Extension Ecosystem | help.apiyi.com/en/openclaw-extensions-ecosystem-guide-en | | Digital Agency Case | openclaw.com.au/use-cases | | r/openclaw | reddit.com/r/openclaw | | r/OpenClawCentral | reddit.com/r/OpenClawCentral | | ClawHub Registry | clawhub.ai/skills | ## Stats (Feb 2026) - GitHub Stars: 135K+ - ClawHub Skills: 3,000+ published, 1,715+ curated - Messaging Platforms: 12 (WhatsApp, Telegram, Discord, Slack, iMessage, Signal, Google Chat, Teams, Matrix, BlueBubbles, Zalo, WebChat) - Discord Community: 8,900+ members - Subreddits: 5+ (r/openclaw, r/OpenClawCentral, r/openclawpirates, r/myclaw, r/OpenClawDevs)

path: findings/2026-02-04.md
content: # Findings / 发现 - 2026-02-04

## 06:32 PST — 搜索新用例 / Fresh search for new/missed use cases

### 健康与养生 / Health & Wellness

#### WHOOP/Oura数据 + AI冥想引导 / WHOOP/Oura Data + AI Meditations
- **来源/Source**: aicybr.com/blog/moltbot-guide
- **平台/Platform**: Multi
- **描述/Description**:
  - 🇨🇳 获取可穿戴设备健康数据（WHOOP、Oura Ring），分析趋势，并使用TTS生成个性化冥想引导。基于真实生物数据的健康教练
  - 🇺🇸 Fetches wearable health data (WHOOP, Oura Ring), analyzes trends, and generates guided meditations using TTS. Personalized wellness coaching based on real biometric data
- **亮点/Why interesting**:
  - 🇨🇳 将健康API + AI推理 + 语音合成组合成主动式健康工作流
  - 🇺🇸 Combines health API + AI reasoning + text-to-speech into a proactive wellness workflow

### DevOps与基础设施 / DevOps & Infrastructure

#### Hetzner服务器运维 + Sentry错误告警 / Hetzner Server Ops + Sentry Error Alerts
- **来源/Source**: aicybr.com/blog/moltbot-guide
- **平台/Platform**: Multi
- **描述/Description**:
  - 🇨🇳 管理Hetzner云服务器，监控CI/CD流水线，集成Sentry实时错误告警。可自主分诊和响应生产环境问题
  - 🇺🇸 Manages Hetzner cloud servers, monitors CI/CD pipelines, integrates with Sentry for real-time error alerting. Can autonomously triage and respond to production issues
- **亮点/Why interesting**:
  - 🇨🇳 完整DevOps闭环——从监控到告警到修复，全程通过聊天完成
  - 🇺🇸 Full DevOps loop -- from monitoring to alerting to remediation, all via chat

#### Cloudflare Workers部署 / Cloudflare Workers Deployment
- **来源/Source**: github.com/cloudflare/moltworker
- **平台/Platform**: Cloudflare
- **描述/Description**:
  - 🇨🇳 官方概念验证：在Cloudflare沙箱容器中运行OpenClaw。始终在线部署，R2持久化存储，无需自建服务器。Cloudflare Workers套餐每月$5
  - 🇺🇸 Official proof-of-concept running OpenClaw inside Cloudflare Sandbox containers. Always-on deployment with R2 persistence, no self-hosting needed. $5/mo Cloudflare Workers plan
- **亮点/Why interesting**:
  - 🇨🇳 无服务器版OpenClaw——消除了最大的使用门槛（需要始终在线的硬件）。Cloudflare官方亲自构建
  - 🇺🇸 Serverless OpenClaw -- removes the biggest barrier (always-on hardware). Cloudflare themselves built this

### 自主编程 / Autonomous Coding

#### Claude Code自动循环 / Claude Code Loops
- **来源/Source**: aicybr.com/blog/moltbot-guide
- **平台/Platform**: Terminal + Messaging
- **描述/Description**:
  - 🇨🇳 运行自主编程循环：编写功能、运行测试、修复bug、开PR——全程无需人工干预。通过消息平台报告结果
  - 🇺🇸 Runs autonomous coding loops: write features, run tests, fix bugs, open PRs -- all without human intervention. Reports results via messaging platform
- **亮点/Why interesting**:
  - 🇨🇳 将编程代理与24/7守护进程结合。手机上发起任务，醒来就看到PR
  - 🇺🇸 Combines coding agent with 24/7 daemon. Start a task from your phone, wake up to a PR

### AI社交网络 / AI Social Network

#### 连接的Clawdbot们密谋在一起 / Connected Clawdbots Plotting Together
- **来源/Source**: brandon.wang/2026/clawdbot + nxcode.io
- **平台/Platform**: Multi-instance
- **描述/Description**:
  - 🇨🇳 人们将各自的OpenClaw实例互相连接到社交网络上，创建纯AI社区。AI之间互动、共享信息、协作
  - 🇺🇸 People connecting their OpenClaw instances to each other on a social network, creating an AI-only community. The AIs interact, share information, and collaborate
- **亮点/Why interesting**:
  - 🇨🇳 涌现行为——"AI Reddit"现象。疯狂且有争议，但展示了代理式未来
  - 🇺🇸 Emergent behavior -- the "AI Reddit" phenomenon. Wild and controversial, but showcases the agentic future

### 背景数据 / Background Context

#### OpenClaw增长数据（nxcode.io）/ OpenClaw Growth Stats (nxcode.io)
- 🇨🇳 约7天内GitHub星标超10万（有史以来最快的AI项目）；首周200万访客；经历3次更名：Clawdbot -> Moltbot -> OpenClaw；已有维基百科页面；Cloudflare和Hetzner集成标志着企业级基础设施野心；月度API费用：$0（本地模型）到$150（重度自动化）
- 🇺🇸 100K+ GitHub stars in ~7 days (fastest AI project ever); 2M visitors in first week; 3 name changes: Clawdbot -> Moltbot -> OpenClaw; Wikipedia page already exists; Cloudflare, Hetzner integration signals enterprise-grade infrastructure ambitions; Monthly API costs: $0 (local models) to $150 (heavy automation)

---

## 06:25 PST — 初始目录构建 / Initial catalog built from 10+ sources

---

### 家居与生活 / Household & Life

#### 冰柜库存拍照识别 / Freezer Inventory via Photos
- **来源/Source**: brandon.wang/2026/clawdbot
- **平台/Platform**: Slack
- **描述/Description**:
  - 🇨🇳 拍摄冰柜里所有物品的照片，OpenClaw解析物品和数量，更新Notion库存，并从购物清单中移除已有物品
  - 🇺🇸 Take photos of everything in chest freezer, OpenClaw parses items and quantities, updates Notion inventory, removes stocked items from grocery list
- **亮点/Why interesting**:
  - 🇨🇳 多模态（视觉 + 推理 + Notion API），取代了两个人的手动流程
  - 🇺🇸 Multi-modal (vision + reasoning + Notion API), replaces a two-person manual process

#### 食谱转购物清单 / Recipe to Grocery List
- **来源/Source**: brandon.wang/2026/clawdbot
- **平台/Platform**: Slack
- **描述/Description**:
  - 🇨🇳 截图一个食谱，OpenClaw将食材提取到Apple Reminders购物清单中。自动去重合并数量（"2根胡萝卜变成3根"）
  - 🇺🇸 Screenshot a recipe, OpenClaw extracts ingredients into Apple Reminders grocery list. Dedupes and combines quantities ("2 carrots becomes 3")
- **亮点/Why interesting**:
  - 🇨🇳 视觉 + 推理 + 去重逻辑，零手动数据录入
  - 🇺🇸 Vision + reasoning + deduplication logic, zero manual data entry

---

### 预订与表单 / Booking & Forms

#### Resy/OpenTable + 日历交叉查询 / Resy/OpenTable with Calendar Intersection
- **来源/Source**: brandon.wang/2026/clawdbot
- **平台/Platform**: Slack + Browser
- **描述/Description**:
  - 🇨🇳 登录Resy（包括从短信读取2FA验证码），逐页浏览可用时段，与双方日历交叉比对，推荐选项。学习取消政策并在日历事件中添加截止日期
  - 🇺🇸 Log into Resy (including reading 2FA from texts), browse availability page-by-page, intersect with both partners' calendars, suggest options. Learns cancellation policies and adds deadlines to calendar events
- **亮点/Why interesting**:
  - 🇨🇳 端到端流程：2FA处理 + 浏览器自动化 + 日历API + 迭代学习。接近一次性偏好校准，"换成真人助理需要数月"
  - 🇺🇸 End-to-end: 2FA handling + browser automation + calendar API + iterative learning. Near single-shot preference calibration that "takes months with a human PA"

#### 牙医预约自动化 / Dentist Appointment Booking
- **来源/Source**: brandon.wang/2026/clawdbot
- **平台/Platform**: Browser + Calendar
- **描述/Description**:
  - 🇨🇳 知道何时该洗牙，登录牙医门户，找到匹配日历和位置距离的时段，确认后预约
  - 🇺🇸 Knows when cleaning is due, logs into dentist portal, finds slot matching calendar + location proximity, confirms before booking
- **亮点/Why interesting**:
  - 🇨🇳 主动式健康管理，而非被动式任务执行
  - 🇺🇸 Proactive health management, not just reactive task execution

---

### 价格监控 / Price Monitoring

#### 复杂酒店价格提醒 + 照片审查 / Complex Hotel Price Alerts with Photo Review
- **来源/Source**: brandon.wang/2026/clawdbot
- **平台/Platform**: Multi
- **描述/Description**:
  - 🇨🇳 同时30+价格提醒。酒店/Airbnb支持推理标准，如"折叠沙发床可以，但不能和另一张床在同一房间"。实际查看房源照片验证房间布局
  - 🇺🇸 30+ simultaneous price alerts. Hotels/Airbnbs with reasoning criteria like "pullout bed OK if not in same room as another bed." Actually reviews listing photos to verify room layout
- **亮点/Why interesting**:
  - 🇨🇳 超越简单价格追踪——对房源照片进行视觉推理，评估主观标准。计划尝试"房间氛围"和"翻新vs破旧"标准
  - 🇺🇸 Goes beyond simple price tracking -- visual reasoning on listing photos, subjective criteria evaluation. Plans to try "room vibe" and "renovated vs dingy" criteria

---

### 远程开发 / Remote Development

#### 躺在床上完成整站重建 / Full Site Rebuild from Bed
- **来源/Source**: @davekiss on X
- **平台/Platform**: Telegram
- **描述/Description**:
  - 🇨🇳 通过Telegram将整个个人网站从Notion迁移到Astro，18篇文章，DNS迁移到Cloudflare。边看Netflix边操作，从未打开笔记本电脑
  - 🇺🇸 Migrated entire personal site from Notion to Astro, 18 posts, DNS moved to Cloudflare. All via Telegram while watching Netflix, never opened laptop
- **亮点/Why interesting**:
  - 🇨🇳 展示"手机即开发终端"的范式转变。非简单的迁移（CMS更换 + DNS），却轻松完成
  - 🇺🇸 Shows the "phone as development terminal" paradigm shift. Non-trivial migration (CMS change + DNS) done casually

---

### 商业应用 / Business

#### 一人数字营销公司 / One-Person Digital Agency
- **来源/Source**: openclaw.com.au/use-cases
- **平台/Platform**: Multi
- **描述/Description**:
  - 🇨🇳 独立营销人员用OpenClaw作为"参谋长"——每日SEO客户检查（5个站点）、邮件分诊+草拟回复、博客/元数据内容创作、Shopify管理、通宵PR
  - 🇺🇸 Solo marketer uses OpenClaw as "Chief of Staff" -- daily SEO client checks (5 sites), email triage + draft responses, blog/meta content creation, Shopify management, overnight PRs
- **亮点/Why interesting**:
  - 🇨🇳 取代一个小团队。"我醒来看到的是完成的工作，而不是待办清单"
  - 🇺🇸 Replaces a small team. "I wake up to completed work instead of a to-do list"

---

### 自进化工作流 / Self-Evolving Workflows

#### 工作流自文档化到Notion / Workflow Self-Documentation to Notion
- **来源/Source**: brandon.wang/2026/clawdbot
- **平台/Platform**: Notion
- **描述/Description**:
  - 🇨🇳 OpenClaw自动将每个创建/修改的工作流以人类可读的方式写入Notion数据库，带版本控制diff。展示每个工作流的演变过程
  - 🇺🇸 OpenClaw auto-writes human-readable descriptions of every workflow it creates/modifies into a Notion database with version control. Shows diffs of how each workflow evolved
- **亮点/Why interesting**:
  - 🇨🇳 元能力——AI记录自己的学习过程。提供可见性和可审计性。"这些小事跟真人助理需要数月甚至数年才能调好。用clawdbot，几乎一次搞定"
  - 🇺🇸 Meta-capability -- the AI documents its own learning. Provides visibility and auditability. "These are little things that take months or years to dial in with a human PA. With clawdbot, nearly single shot."

---

### 消息管理 / Messaging

#### 永不遗忘短信中的承诺 / Never Forgetting Text Promises
- **来源/Source**: brandon.wang/2026/clawdbot
- **平台/Platform**: iMessage + Calendar
- **描述/Description**:
  - 🇨🇳 每15分钟扫描短信。检测具体承诺（"我明天会看"），创建日历事件。检测聚餐要素（时间+地点+确认），起草日历邀请，创建占位防止重复预约
  - 🇺🇸 Scans texts every 15 min. Detects concrete promises ("I'll review this tomorrow"), creates calendar events. Detects meeting plan ingredients (time + place + confirmation), drafts calendar invites, creates holds to prevent double-booking
- **亮点/Why interesting**:
  - 🇨🇳 弥合了邮件（Superhuman级功能）和短信（混乱无序）之间的工具鸿沟。主动式承诺追踪
  - 🇺🇸 Bridges the tooling gap between email (Superhuman-level features) and texting (wild west). Proactive commitment tracking

---

### 生态规模 / Ecosystem Scale

#### ClawHub注册表数据 / ClawHub Registry Stats
- **来源/Source**: github.com/VoltAgent/awesome-openclaw-skills + clawhub.ai
- **描述/Description**:
  - 🇨🇳 已发布3000+技能。筛选加密货币/垃圾/重复后精选1715+个。31个类别。排名靠前：AI/LLM（159）、搜索/研究（148）、DevOps/云（144）
  - 🇺🇸 3,000+ skills published. Curated list of 1,715+ after filtering crypto/spam/dupes. 31 categories. Top: AI/LLMs (159), Search/Research (148), DevOps/Cloud (144)
- **亮点/Why interesting**:
  - 🇨🇳 截至2026年2月，增长最快的AI代理技能生态系统
  - 🇺🇸 Fastest-growing AI agent skill ecosystem as of Feb 2026


path: findings/2026-02-05-leo-personalized.md
content: # OpenClaw Use Cases for Leo Liao / Leo Liao的OpenClaw应用场景

**Generated:** 2026-02-05 07:08 PST  
**Profile:** Senior Computer Scientist @ {research_lab} | SVCAF Founding President | WeChat公众号 AI Tech/Policy

---

## 🎯 Priority Rankings / 优先级排序

### High Priority (立即可用 - Immediate Value)
1. **Bilingual Content Pipeline** — 公众号 article → translation → illustration (30 min setup)
2. **{internal_grant} Proposal Assistant** — Leverage existing skill for whitepaper generation (15 min)
3. **GitHub + Multi-Channel Workflow** — Issue triage across Discord/Telegram/email (45 min)

### Medium Priority (中期价值 - Medium-term Value)
4. **WeChat Community Management** — SVCAF member engagement tracking (1-2 hours)
5. **Research Collaboration Coordinator** — {research_lab} team coordination + literature tracking (1 hour)
6. **HPC Job Monitoring** — Cluster job status + alerting (2-3 hours, requires cluster access)

### Long-term Priority (长期战略 - Strategic/Experimental)
7. **{compiler_project} Compiler Integration** — AI-assisted refactoring workflows (4-8 hours, experimental)
8. **AI4Legislation Analysis** — Policy document analysis + bilingual summaries (3-5 hours)

---

## 📚 CATEGORY 1: Bilingual Content Creation / 双语内容创作

### 1.1 WeChat公众号 Article Pipeline / 公众号文章流水线

**Use Case / 场景:**
- 🇨🇳 从草稿到发布的完整自动化：AI写作 → 中英翻译 → 美工配图 → 跨平台分发（公众号/Twitter/LinkedIn）
- 🇺🇸 End-to-end automation: AI drafting → EN/ZH translation → Illustration → Multi-platform distribution (WeChat/Twitter/LinkedIn)

**Implementation / 实施步骤:**

```bash
# Step 1: Draft article (English or Chinese)
# Via Telegram/WhatsApp: "Draft article on AI4Legislation compliance frameworks"

# Step 2: Translate
# OpenClaw calls DeepL/GPT-4 for high-quality translation
# Output: dual-language versions in memory/drafts/

# Step 3: Generate illustrations
cd skills/article-illustrator
node scripts/generate.mjs \
  --input ~/drafts/2026-02-05-ai4legislation.md \
  --style scrapbook \
  --lang zh \
  --max 5 \
  --watermark "SVCAF | 书同文"

# Step 4: Cross-platform distribution
# Manual for WeChat公众号 (API limitations)
# Auto-post to Twitter/LinkedIn via OpenClaw message tool
```

**Skills Needed / 所需技能:**
- ✅ **EXISTING:** `article-illustrator` (GPT-4o image generation)
- ⚙️ **TO CREATE:** `bilingual-translator` (DeepL/GPT-4 wrapper)
- ⚙️ **TO CREATE:** `social-distributor` (Twitter/LinkedIn API posting)

**Time Estimate / 时间估算:**
- Setup: 30-45 minutes
- Per article: 5-10 minutes (vs. 2-3 hours manual)

**Example Workflow / 示例流程:**
```
You (Telegram): "Write article: 'How AI Tools Are Transforming Legislative Compliance in California', 800 words, technical but accessible"

OpenClaw:
  → Drafts article in English using Claude
  → Translates to Chinese using DeepL API
  → Generates 4 scrapbook-style illustrations
  → Saves to ~/public-accounts/drafts/2026-02-05/
  → Offers to post to Twitter/LinkedIn

You: "Post English version to Twitter thread, Chinese to WeChat draft"

OpenClaw:
  → Creates 8-tweet thread with images
  → Exports WeChat draft as markdown for manual upload
  → Logs to memory/2026-02-05.md
```

---

### 1.2 AI Policy Analysis with Bilingual Output / AI政策分析双语输出

**Use Case / 场景:**
- 🇨🇳 监控AI相关立法动态（美国/中国），生成双语分析报告，定期推送到公众号素材库
- 🇺🇸 Monitor AI legislation (US/China), generate bilingual analysis reports, periodic push to WeChat drafts

**Implementation / 实施步骤:**

```bash
# Cron job: Daily at 8am
# Scan sources: congress.gov, CAC.gov.cn, arXiv policy papers
# Generate summary if significant updates

# Example heartbeat workflow:
# ~/.openclaw/skills/ai-policy-tracker/heartbeat.mjs
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `policy-tracker` (web scraping + RSS feeds)
- ⚙️ **TO CREATE:** `bilingual-policy-summarizer` (Claude + structured prompts)

**Time Estimate / 时间估算:**
- Setup: 2-3 hours (source configuration + prompt engineering)
- Maintenance: 10 min/week

**ROI / 投资回报:**
- Saves 3-5 hours/week of manual research
- Content cadence: 2-3 articles/month → 8-10 articles/month

---

## 🔬 CATEGORY 2: Scientific Computing & Compiler Development / 科学计算与编译器开发

### 2.1 HPC Job Monitoring & Alerting / 高性能计算任务监控与告警

**Use Case / 场景:**
- 🇨🇳 监控{research_lab}集群上的长时间运行任务（{compiler_project}编译测试、性能基准），任务完成/失败时通过Telegram告警
- 🇺🇸 Monitor long-running jobs on {research_lab} clusters ({compiler_project} compiler tests, benchmarks), alert via Telegram on completion/failure

**Implementation / 实施步骤:**

```bash
# On {research_lab} cluster (via SSH from OpenClaw):
# 1. Setup SSH key auth to cluster (ssh ubuntu-rog or {research_lab} login node)
# 2. Create monitoring script

# Example: skills/hpc-job-monitor/monitor.sh
#!/bin/bash
# Check SLURM queue for your jobs
squeue -u liao --format="%.18i %.9P %.50j %.8u %.2t %.10M %.6D %R" > /tmp/jobs.txt

# OpenClaw periodically runs this via SSH, parses output
# Alerts on state changes: PENDING → RUNNING → COMPLETED/FAILED
```

**OpenClaw Heartbeat / 心跳配置:**
```javascript
// ~/.openclaw/heartbeats/hpc-monitor.mjs
export default {
  schedule: "*/15 * * * *", // Every 15 minutes
  async run({ exec, message }) {
    const result = await exec({
      command: "ssh login-node 'squeue -u liao'",
      timeout: 10000
    });
    
    // Parse job states, compare with last known state
    // Alert if status changed to COMPLETED or FAILED
    if (jobCompleted) {
      await message({
        action: "send",
        target: "Leo",
        message: `✅ Job ${jobId} completed: ${jobName}\nRuntime: ${runtime}\nOutput: /path/to/output`
      });
    }
  }
};
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `hpc-job-monitor` (SLURM/PBS parser + state tracking)
- ✅ **EXISTING:** OpenClaw `exec` + `message` tools

**Time Estimate / 时间估算:**
- Setup: 1-2 hours (SSH keys + script + heartbeat)
- Per-job value: Saves checking cluster every 30 min

**Security Note / 安全注意:**
- Use dedicated SSH key with read-only access
- No sensitive code/data in alerts (job IDs only)

---

### 2.2 Automated Code Review for C++/Fortran Compliance / C++/Fortran代码审查自动化

**Use Case / 场景:**
- 🇨🇳 为{compiler_project}项目PR自动运行静态分析（clang-tidy, cppcheck），将结果汇总并评论到GitHub PR
- 🇺🇸 Auto-run static analysis (clang-tidy, cppcheck) on {compiler_project} PRs, summarize findings, comment on GitHub

**Implementation / 实施步骤:**

```bash
# GitHub webhook → OpenClaw skill → Run analysis → Comment on PR

# 1. Setup GitHub webhook for {github_user}/rose
# 2. OpenClaw receives PR event
# 3. Clone PR branch, run analysis tools
# 4. Parse output, generate human-readable summary
# 5. Post as PR comment

# Example: skills/code-review-assistant/analyze.sh
#!/bin/bash
PR_BRANCH=$1
git clone --depth 1 --branch $PR_BRANCH https://github.com/{github_user}/rose.git /tmp/rose-pr
cd /tmp/rose-pr
clang-tidy src/**/*.cpp > /tmp/analysis.txt
cppcheck --enable=all src/ 2> /tmp/cppcheck.txt

# OpenClaw parses /tmp/*.txt and generates summary
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `code-review-assistant` (GitHub webhook handler + static analysis parser)
- 🔧 **TOOLS:** clang-tidy, cppcheck, sonar-scanner

**Time Estimate / 时间估算:**
- Setup: 2-3 hours
- Per PR: 5-10 minutes automated (vs. 30-60 min manual)

**Advanced / 高级功能:**
- GPT-4 code review: "Explain why this function has high cyclomatic complexity"
- Suggest refactorings: "This loop can be parallelized with OpenMP"

---

### 2.3 {compiler_project} Compiler Integration: AI-Assisted Refactoring / {compiler_project}编译器AI辅助重构

**Use Case / 场景:**
- 🇨🇳 利用{compiler_project} AST分析能力，结合GPT-4建议重构模式（例如：检测可并行化循环，生成OpenMP指令）
- 🇺🇸 Leverage {compiler_project} AST analysis + GPT-4 to suggest refactoring patterns (e.g., detect parallelizable loops, generate OpenMP directives)

**Implementation / 实施步骤:**

```bash
# Experimental workflow (4-8 hours R&D)

# 1. {compiler_project} AST dump → JSON
rose-compiler --dump-ast input.cpp > ast.json

# 2. OpenClaw analyzes AST
# Detects patterns:
# - Loops with no data dependencies → OpenMP candidate
# - Array accesses with predictable patterns → Vectorization candidate

# 3. GPT-4 generates refactored code
# Prompt: "Here is the AST of a loop. Suggest OpenMP parallelization."

# 4. Output: Diff + explanation
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `rose-ast-analyzer` (AST parser + pattern detector)
- 🧠 **AI:** GPT-4 with code generation prompts
- 🔬 **EXPERT:** {compiler_project} API knowledge (Leo already has this!)

**Time Estimate / 时间估算:**
- Proof of concept: 4-6 hours
- Production-ready: 20-40 hours (iterative refinement)

**Risk / 风险:**
- High complexity, low immediate ROI
- Recommend: Start with simpler code review automation (2.2) first

---

## 🏛️ CATEGORY 3: Community & Non-profit Management / 社区与非营利管理

### 3.1 SVCAF Member Engagement Tracking / 书同文会员互动追踪

**Use Case / 场景:**
- 🇨🇳 聚合跨平台会员活动（WeChat群、email列表、Signal），生成每周参与度报告，识别需要跟进的成员
- 🇺🇸 Aggregate cross-platform member activity (WeChat groups, email lists, Signal), generate weekly engagement reports, identify members needing follow-up

**Implementation / 实施步骤:**

```bash
# Challenge: WeChat API is restricted (no official bot API for group messages)
# Workaround: Use WeChat message export + manual upload

# 1. Weekly: Export WeChat group chat history (manual or using 3rd party tools)
# 2. Upload to OpenClaw: "Analyze this week's WeChat group activity"
# 3. OpenClaw parses:
#    - Message counts per member
#    - Key topics discussed
#    - Unanswered questions
#    - Members who haven't posted in 30+ days

# 4. Generate report:
#    - Top 10 active members
#    - Members to re-engage (suggested personal messages)
#    - Action items from discussions

# Email/Signal: Use OpenClaw message tool to scan directly
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `community-engagement-analyzer` (chat log parser + engagement metrics)
- ⚙️ **TO CREATE:** `wechat-export-parser` (handle WeChat export formats)

**Time Estimate / 时间估算:**
- Setup: 1-2 hours
- Weekly maintenance: 10 minutes (upload + review report)

**Output Example / 输出示例:**
```
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📊 SVCAF Weekly Engagement Report
Week of 2026-02-03 to 2026-02-09
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

✅ Total Messages: 287 (↑ 12% vs last week)
👥 Active Members: 45/120 (37.5%)
🔥 Hot Topics: AI translation tools (18 mentions), 
               Fundraising event (12 mentions)

⚠️ Re-engage (silent >30 days):
   • Zhang Wei (last: 2025-12-15)
   • Li Hua (last: 2026-01-05)
   Suggested: "Hi Zhang Wei, we missed you at..."

📋 Action Items:
   • Follow up on fundraising venue booking
   • Schedule AI translation workshop (8 members interested)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
```

---

### 3.2 Event Coordination & Calendar Management / 活动协调与日历管理

**Use Case / 场景:**
- 🇨🇳 SVCAF活动策划：自动检查成员可用性（从邮件线程/日历），建议时间，发送日历邀请，活动前提醒
- 🇺🇸 SVCAF event planning: Auto-check member availability (from email threads/calendars), suggest times, send invites, pre-event reminders

**Implementation / 实施步骤:**

```bash
# Similar to Resy/OpenTable use case from catalog
# Adapted for non-profit context

# Workflow:
# You: "Schedule SVCAF board meeting, 2 hours, all 5 board members, next 2 weeks"

# OpenClaw:
# 1. Checks your calendar + board members' shared calendars (Google Calendar API)
# 2. Finds 3-5 time slots that work for everyone
# 3. Presents options with conflict summary
# 4. You select
# 5. OpenClaw sends calendar invites (Google Calendar API)
# 6. Sets reminder: 2 days before (prep agenda), 1 hour before (link)
```

**Skills Needed / 所需技能:**
- ✅ **EXISTING:** Calendar intersection logic (from catalog examples)
- ⚙️ **TO CREATE:** `multi-calendar-scheduler` (Google Calendar API wrapper)

**Time Estimate / 时间估算:**
- Setup: 30-45 minutes (OAuth setup for Google Calendar)
- Per event: Saves 20-30 minutes of email back-and-forth

---

### 3.3 Grant & Proposal Tracking / 资助与提案跟踪

**Use Case / 场景:**
- 🇨🇳 追踪SVCAF申请的各类资助：截止日期提醒、状态更新、文档归档
- 🇺🇸 Track SVCAF grant applications: deadline reminders, status updates, document archiving

**Implementation / 实施步骤:**

```bash
# Simple workflow using OpenClaw memory + reminders

# 1. Create grants tracking file: memory/grants-2026.md
# 2. Log each application:
#    - Grant name
#    - Deadline
#    - Amount
#    - Status (Draft/Submitted/Under Review/Approved/Rejected)
#    - Contact person

# 3. OpenClaw heartbeat checks daily:
#    - Alerts 2 weeks before deadline
#    - Alerts 1 week before
#    - Alerts 3 days before
#    - Prompts for status update if no update in 30 days

# 4. Generate monthly report of all active grants
```

**Skills Needed / 所需技能:**
- ✅ **EXISTING:** OpenClaw heartbeat system
- ⚙️ **TO CREATE:** `grant-tracker-heartbeat` (markdown parser + date logic)

**Time Estimate / 时间估算:**
- Setup: 30 minutes
- Ongoing: Saves 1-2 hours/month of manual tracking

---

## 📝 CATEGORY 4: Research Workflow / 研究工作流

### 4.1 {internal_grant} Proposal Generation / {internal_grant}提案生成

**Use Case / 场景:**
- 🇨🇳 使用现有`ldrd-proposal-writer`技能，结合{research_lab}战略重点，快速生成高质量白皮书草稿
- 🇺🇸 Use existing `ldrd-proposal-writer` skill, aligned with {research_lab} strategic priorities, to rapidly generate high-quality whitepaper drafts

**Implementation / 实施步骤:**

```bash
# ✅ SKILL ALREADY EXISTS in workspace!

cd skills/ldrd-proposal-writer

# Via Telegram/WhatsApp:
You: "Write {internal_grant} proposal: 'AI-Accelerated Compiler Optimization for Exascale Heterogeneous Systems', 
     Category: HPC + AI, 
     Duration: 3 years, 
     My expertise: {compiler_project} compiler, LLVM, source-to-source transformation"

OpenClaw:
  → Researches state-of-art in AI4Compilers
  → Drafts 5-page whitepaper with structure:
     • Executive Summary
     • Technical Motivation (cites recent papers)
     • Proposed Approach (specific milestones)
     • Expected Outcomes (follow-on funding paths)
     • Team & Resources
  → Saves to ~/ldrd-proposals/2026-02-05-ai-compiler-opt.md
  → Generates LaTeX version using {research_lab} template
```

**Skills Needed / 所需技能:**
- ✅ **EXISTING:** `ldrd-proposal-writer` (see SKILL.md above)

**Time Estimate / 时间估算:**
- Setup: ZERO (already installed!)
- Per proposal: 30-45 minutes draft (vs. 4-8 hours manual)

**ROI / 投资回报:**
- 🏆 **HIGHEST IMMEDIATE VALUE** for Leo's profile
- {internal_grant} proposals are high-stakes, time-intensive
- AI draft → human refinement = 5-10x productivity boost

---

### 4.2 Literature Review Automation / 文献综述自动化

**Use Case / 场景:**
- 🇨🇳 自动监控arXiv/LLVM Weekly/PLDI等渠道，筛选编译器优化、HPC相关论文，生成周报
- 🇺🇸 Auto-monitor arXiv/LLVM Weekly/PLDI, filter compiler optimization & HPC papers, generate weekly digest

**Implementation / 实施步骤:**

```bash
# Heartbeat: Weekly on Monday 8am

# Sources:
# - arXiv: cs.PL (Programming Languages), cs.DC (Distributed/Parallel)
# - LLVM Weekly: http://llvmweekly.org/
# - ACM PLDI/POPL proceedings

# OpenClaw workflow:
# 1. Scrape/fetch RSS feeds
# 2. Filter by keywords: "compiler", "optimization", "HPC", "{compiler_project}", "LLVM"
# 3. GPT-4 summarizes each paper (2-3 sentences)
# 4. Ranks by relevance to Leo's work
# 5. Sends digest via Telegram

# Example output:
📚 Weekly Compiler & HPC Digest - 2026-02-10

🔥 Top 3 Highly Relevant:
1. "Neural Program Synthesis for Compiler Optimization" (arXiv:2602.12345)
   Summary: Uses transformers to predict profitable optimization passes...
   Relevance: 95% - Directly applicable to {compiler_project} ML integration
   
2. "Scalable Source-to-Source Transformation on Exascale Clusters" (SC26)
   Summary: Distributed AST manipulation framework...
   Relevance: 88% - Parallel {compiler_project} processing

📖 Also Worth Reading (5 more papers)
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `research-digest-generator` (RSS + arXiv API + GPT-4 summarization)

**Time Estimate / 时间估算:**
- Setup: 2-3 hours (source configuration + prompt tuning)
- Saves: 2-3 hours/week of manual paper hunting

---

### 4.3 Collaboration Coordination for {research_lab} Teams / {research_lab}团队协作协调

**Use Case / 场景:**
- 🇨🇳 协调跨团队协作（编译器组、HPC算法组、应用科学家）：同步会议笔记、追踪行动项、提醒截止日期
- 🇺🇸 Coordinate cross-team collaboration (compiler team, HPC algorithms, app scientists): sync meeting notes, track action items, deadline reminders

**Implementation / 实施步骤:**

```bash
# Integration with existing {research_lab} tools (Confluence, JIRA, email)

# Workflow:
# 1. After each team meeting, send notes to OpenClaw (or auto-transcribe if recorded)
# 2. OpenClaw extracts:
#    - Action items (who/what/when)
#    - Decisions made
#    - Open questions
# 3. Creates/updates tracking document: memory/org-collab/2026-Q1.md
# 4. Sets reminders for action item deadlines
# 5. Generates weekly "What's Blocking Us" summary

# Example:
You: "Meeting notes attached: {compiler_project}-HPC integration discussion"

OpenClaw:
  → Parses notes
  → Extracts:
     • ACTION: Leo - Benchmark {compiler_project} on new Lassen nodes (Due: Feb 12)
     • ACTION: Sarah - Validate OpenMP output correctness (Due: Feb 15)
     • DECISION: Use LLVM 18.0 as baseline
     • QUESTION: How to handle Fortran legacy code?
  → Adds to tracking doc
  → Sets reminders: Feb 10 (2 days before benchmark deadline)
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `meeting-notes-parser` (action item extraction)
- ✅ **EXISTING:** OpenClaw heartbeat reminders

**Time Estimate / 时间估算:**
- Setup: 1 hour
- Per meeting: Saves 15-20 minutes of manual note processing

---

## 💻 CATEGORY 5: Multi-Platform Developer Workflow / 多平台开发者工作流

### 5.1 GitHub Issue Triage + Discord/Telegram Alerts / GitHub问题分类与跨平台告警

**Use Case / 场景:**
- 🇨🇳 监控{github_user}/rose和{github_org} repositories，新issue自动分类（bug/feature/question），高优先级通过Telegram告警
- 🇺🇸 Monitor {github_user}/rose & {github_org} repos, auto-triage new issues (bug/feature/question), high-priority alerts via Telegram

**Implementation / 实施步骤:**

```bash
# GitHub webhook → OpenClaw skill → Classify → Alert

# Setup:
# 1. GitHub webhook for both repos → OpenClaw endpoint
# 2. OpenClaw receives issue/PR events
# 3. GPT-4 classifies:
#    - Type: Bug / Feature Request / Question / Documentation
#    - Priority: Critical / High / Medium / Low
#    - Component: Frontend / Backend / Compiler / Infrastructure
# 4. Auto-labels on GitHub
# 5. If Critical/High: Telegram alert to Leo

# Example alert:
🚨 High Priority Issue: rose#1234
Title: "Segfault in AST traversal for C++20 coroutines"
Type: Bug | Component: Compiler Core
Reporter: john.doe (external contributor)
Link: github.com/{github_user}/rose/issues/1234

Suggested action: Assign to Leo or triage team
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `github-issue-triager` (webhook handler + GPT-4 classifier)
- ✅ **EXISTING:** OpenClaw `message` tool for Telegram alerts

**Time Estimate / 时间估算:**
- Setup: 45 minutes
- Saves: 30-60 minutes/week of manual issue triage

---

### 5.2 Code Review Automation Across Channels / 跨渠道代码审查自动化

**Use Case / 场景:**
- 🇨🇳 GitHub PR + Discord讨论 + Telegram提醒 = 统一上下文。OpenClaw聚合所有渠道的讨论，生成总结
- 🇺🇸 GitHub PR + Discord discussion + Telegram reminders = unified context. OpenClaw aggregates all channels, generates summary

**Implementation / 实施步骤:**

```bash
# Multi-channel workflow:

# Scenario: PR opened on GitHub
# 1. GitHub webhook → OpenClaw
# 2. OpenClaw posts summary to Discord #code-review channel
# 3. Team discusses on Discord
# 4. OpenClaw monitors Discord thread, extracts key points
# 5. After 24 hours, if no review: Telegram reminder to Leo
# 6. When review posted: OpenClaw aggregates feedback from GitHub + Discord

# Example aggregated summary:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
📋 PR #456 Review Summary
"Refactor AST visitor pattern for better extensibility"
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

GitHub Comments (3):
  • Alice: Suggests using std::variant instead of void*
  • Bob: Performance concern on large ASTs
  
Discord Discussion (8 messages):
  • Team consensus: Variant approach is cleaner
  • Need benchmarks before merging
  
Action: Leo to run benchmark suite, post results by EOD
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `multi-channel-aggregator` (GitHub + Discord webhooks)
- ✅ **EXISTING:** OpenClaw `message` tool

**Time Estimate / 时间估算:**
- Setup: 1-2 hours
- Per PR: Saves 10-15 minutes of context switching

---

### 5.3 Deployment Monitoring with Cross-Platform Notifications / 部署监控与跨平台通知

**Use Case / 场景:**
- 🇨🇳 监控{compiler_project} CI/CD流水线（GitHub Actions），构建失败时发送Telegram告警，包含日志摘要和可能原因
- 🇺🇸 Monitor {compiler_project} CI/CD pipeline (GitHub Actions), send Telegram alerts on build failures with log summary & likely causes

**Implementation / 实施步骤:**

```bash
# GitHub Actions webhook → OpenClaw → Parse logs → Alert

# On workflow failure:
# 1. GitHub Actions sends webhook to OpenClaw
# 2. OpenClaw fetches build logs (GitHub API)
# 3. GPT-4 analyzes logs:
#    - Identifies root cause (compilation error, test failure, timeout)
#    - Extracts key error messages
#    - Suggests fix if pattern is known
# 4. Sends alert via Telegram

# Example alert:
❌ Build Failed: rose/main (commit abc123)
Workflow: Linux GCC 13.2 Build

Root Cause: Compilation error in src/frontend/CxxFrontend/EDG/edgRose.C:1234
Error: 'std::filesystem' not available in C++11 mode

Suggested Fix: Update CMakeLists.txt to require C++17 for this target

Logs: github.com/{github_user}/rose/actions/runs/98765
```

**Skills Needed / 所需技能:**
- ⚙️ **TO CREATE:** `ci-monitor` (GitHub Actions webhook + log analyzer)
- ✅ **EXISTING:** OpenClaw `message` tool

**Time Estimate / 时间估算:**
- Setup: 1 hour
- Saves: 30+ minutes per failure (immediate notification vs. discovering hours later)

---

## 📊 Implementation Roadmap / 实施路线图

### Week 1: Quick Wins (3-4 hours total)
- ✅ Setup {internal_grant} proposal writer (0 min - already exists!)
- ⚙️ Configure bilingual content pipeline (article-illustrator + translation)
- ⚙️ Setup GitHub issue triager for one repo ({github_user}/rose)

### Week 2-3: Core Workflows (5-8 hours)
- ⚙️ HPC job monitoring (if cluster access available)
- ⚙️ Literature review automation
- ⚙️ Multi-channel code review aggregator

### Month 2: Community & Advanced Features (10-15 hours)
- ⚙️ SVCAF engagement tracker
- ⚙️ Event coordination system
- ⚙️ Code review assistant (static analysis)

### Month 3+: Experimental (20+ hours, as research permits)
- 🔬 {compiler_project} compiler AI integration
- 🔬 AI4Legislation analysis pipeline

---

## 🛠️ Skills to Create / 需要创建的技能

### High Priority
1. **bilingual-translator** (30 min)
2. **github-issue-triager** (45 min)
3. **hpc-job-monitor** (1-2 hours)

### Medium Priority
4. **research-digest-generator** (2-3 hours)
5. **community-engagement-analyzer** (1-2 hours)
6. **multi-channel-aggregator** (1-2 hours)

### Low Priority / Experimental
7. **rose-ast-analyzer** (4-8 hours R&D)
8. **policy-tracker** (3-5 hours)

---

## 💰 Cost Estimates / 成本估算

### API Usage (Monthly)
- **Light usage:** $5-15/month
  - {internal_grant} proposals: 2-3/month × $0.50 = $1.50
  - Article illustrations: 4 articles × 5 images × $0.04 = $0.80
  - Daily summaries/monitoring: $3-5

- **Heavy usage:** $30-50/month
  - All above +
  - Code review automation: $5-10
  - Literature reviews: $5-10
  - Policy analysis: $5-10

### Time Investment
- **Initial setup (Week 1-3):** 8-12 hours
- **Maintenance:** 1-2 hours/week
- **ROI:** Save 10-15 hours/week after setup complete

---

## 🔐 Security Considerations / 安全考虑

### {research_lab} Context
- ⚠️ **NEVER** send classified/UCNI data to external APIs
- ✅ Use OpenClaw for UNCLASSIFIED workflows only
- ✅ For sensitive HPC monitoring: Use local models (Ollama) instead of GPT-4
- ✅ GitHub webhooks: Validate signatures, restrict to public repos

### WeChat/Community Data
- ✅ Anonymize member data before processing (remove real names)
- ✅ Get consent before tracking engagement metrics
- ✅ Store data locally, not in cloud services

### Best Practices
- Use dedicated burner accounts for integrations (GitHub bot account, separate email)
- Enable 2FA on all integrated accounts
- Regularly audit OpenClaw logs for unexpected behavior
- Keep skills in version control (Git repos)

---

## 📚 References / 参考资料

### OpenClaw Resources
- Official Docs: https://docs.openclaw.ai/
- ClawHub Skills: https://clawhub.ai/skills
- Community: r/openclaw, Discord

### {research_lab}-Specific
- {internal_grant} Program: https://ldrd-annual.example.com/
- {compiler_project} Compiler: https://github.com/rose-compiler/rose
- {research_lab} HPC Docs: https://hpc.example.com/

### Bilingual Content Tools
- DeepL API: https://www.deepl.com/pro-api
- WeChat公众号平台: https://mp.weixin.qq.com/

---

## 📝 Next Steps / 下一步行动

1. **Today (15 min):** Test {internal_grant} proposal writer with a sample topic
2. **This Week (2 hours):** Setup bilingual content pipeline + GitHub triager
3. **Next Week (2 hours):** Configure HPC monitoring OR literature review
4. **Month 1 Review:** Assess ROI, prioritize next wave of skills

**Questions to consider / 需要考虑的问题:**
- Which GitHub repos should be monitored? ({github_user}/rose, {github_org}/*, others?)
- Preferred communication channel? (Telegram, WhatsApp, Discord?)
- {research_lab} cluster access details? (Login nodes, SLURM vs PBS?)
- WeChat群 export frequency? (Weekly, bi-weekly?)

---

**Generated by:** OpenClaw Agent (subagent:62f5a35d)  
**For:** Chunhua "Leo" Liao  
**Date:** 2026-02-05 PST  
**Version:** 1.0

---

## 🎯 TL;DR / 核心要点

**Top 3 Immediate Value Use Cases for Leo:**
1. ✅ **{internal_grant} Proposal Writer** (15 min setup, 5-10x productivity) — ALREADY INSTALLED!
2. ⚙️ **Bilingual Content Pipeline** (30 min setup, 4 articles/month → 12 articles/month)
3. ⚙️ **GitHub Issue Triager** (45 min setup, save 30-60 min/week)

**Total Setup Time (Week 1):** 90 minutes  
**Expected ROI:** Save 8-12 hours/week within one month  
**Monthly Cost:** $10-20 (API usage)

🚀 **Recommendation:** Start with {internal_grant} proposal writer TODAY (zero setup), then add content pipeline this weekend.


path: findings/2026-02-05-leo-summary.md
content: # Executive Summary: OpenClaw for Leo Liao
## 为Leo Liao定制的OpenClaw应用场景 - 执行摘要

**Generated:** 2026-02-05 07:08 PST  
**Full Report:** `findings/2026-02-05-leo-personalized.md` (803 lines, bilingual)

---

## 🎯 Top 3 Immediate Actions / 立即可行的三大应用

### 1. ✅ {internal_grant} Proposal Writer (ALREADY INSTALLED!)
**已安装！零设置时间**

- **What:** Auto-generate {internal_grant} whitepaper drafts aligned with {research_lab} strategic priorities
- **Setup:** 0 minutes (skill already exists in workspace!)
- **Usage:** Via Telegram: "Write {internal_grant} proposal: [topic]"
- **ROI:** 30-45 min draft vs. 4-8 hours manual = **5-10x productivity**
- **Location:** `skills/ldrd-proposal-writer/SKILL.md`

**Example:**
```
You: "Write {internal_grant} proposal: AI-Accelerated Compiler Optimization for Exascale Systems"
OpenClaw: [Generates 5-page whitepaper with citations, methodology, budget]
```

---

### 2. ⚙️ Bilingual Content Pipeline (30 min setup)
**公众号文章流水线（30分钟设置）**

- **What:** Draft → Translate (EN/ZH) → Illustrate → Distribute (WeChat/Twitter/LinkedIn)
- **Skills:** `article-illustrator` (exists) + `bilingual-translator` (need to create)
- **Setup:** 30-45 minutes
- **ROI:** 5-10 min per article vs. 2-3 hours manual = **12-36x faster**
- **Output:** Scrapbook-style images + dual-language markdown

**Workflow:**
```
You: "Write article: How AI Tools Transform Legislative Compliance, 800 words"
OpenClaw: 
  → Drafts in English (Claude)
  → Translates to Chinese (DeepL)
  → Generates 4 infographic images (GPT-4o)
  → Posts to Twitter thread + WeChat draft
```

**Impact:** 2-3 articles/month → **8-10 articles/month**

---

### 3. ⚙️ GitHub Issue Triager (45 min setup)
**GitHub问题自动分类（45分钟设置）**

- **What:** Auto-classify new issues on {github_user}/rose (bug/feature/question), high-priority Telegram alerts
- **Setup:** 45 minutes (GitHub webhook + GPT-4 classifier)
- **ROI:** Save 30-60 min/week of manual triage
- **Bonus:** Auto-labels issues, extracts key info

**Example Alert:**
```
🚨 High Priority: rose#1234
"Segfault in AST traversal for C++20 coroutines"
Type: Bug | Component: Compiler Core
→ Assign to Leo or triage team
```

---

## 📊 Additional High-Value Use Cases / 其他高价值应用

### 4. HPC Job Monitoring (1-2 hours setup)
- Monitor {research_lab} cluster jobs (SLURM), Telegram alerts on completion/failure
- Saves checking cluster every 30 minutes

### 5. Literature Review Automation (2-3 hours setup)
- Weekly digest from arXiv/LLVM Weekly/PLDI filtered to compiler/HPC topics
- Saves 2-3 hours/week of paper hunting

### 6. SVCAF Member Engagement Tracking (1-2 hours setup)
- Aggregate WeChat/email/Signal activity → weekly engagement reports
- Identify members needing re-engagement

### 7. Multi-Channel Code Review (1-2 hours setup)
- Aggregate GitHub PR + Discord discussion + Telegram reminders
- Unified context across platforms

### 8. Code Review Automation (2-3 hours setup)
- Auto-run clang-tidy/cppcheck on PRs, post summary as GitHub comment
- 5-10 min automated vs. 30-60 min manual per PR

---

## 🛠️ Implementation Roadmap / 实施路线图

### Today (15 min)
✅ Test {internal_grant} proposal writer with sample topic

### This Week (2 hours)
1. Setup bilingual content pipeline
2. Configure GitHub issue triager for rose repo

### Next Week (2 hours)
3. Setup HPC job monitoring OR literature review

### Month 1 (Total: 8-12 hours setup)
4. Add SVCAF engagement tracker
5. Multi-channel code review aggregator

### ROI After Month 1
**Save 10-15 hours/week** through automation

---

## 💰 Cost Estimate / 成本估算

### Light Usage: $5-15/month
- {internal_grant} proposals: 2-3/month × $0.50 = $1.50
- Article illustrations: 4 articles × 5 images × $0.04 = $0.80
- Daily monitoring: $3-5

### Heavy Usage: $30-50/month
- All above + code review + literature + policy analysis

### Time Investment
- **Setup (Week 1-3):** 8-12 hours total
- **Maintenance:** 1-2 hours/week
- **ROI:** Save 10-15 hours/week = **8-10x return**

---

## 🔐 Security Notes / 安全提醒

⚠️ **CRITICAL for {research_lab}:**
- NEVER send classified/UCNI data to external APIs
- Use OpenClaw for UNCLASSIFIED workflows ONLY
- For sensitive HPC monitoring: Use local models (Ollama) instead of GPT-4
- GitHub webhooks: Public repos only, validate signatures

✅ **Best Practices:**
- Dedicated bot accounts for integrations
- Enable 2FA everywhere
- Anonymize community member data
- Version control all skills (Git)

---

## 📁 Full Report / 完整报告

**File:** `skills/openclaw-usecases/findings/2026-02-05-leo-personalized.md`

**Contains:**
- 15+ detailed use cases across 5 categories
- Step-by-step implementation guides
- Code examples and workflows
- Time/cost estimates for each
- Security considerations
- Bilingual descriptions throughout

**Categories:**
1. Bilingual Content Creation (3 use cases)
2. Scientific Computing & Compiler Development (3 use cases)
3. Community & Non-profit Management (3 use cases)
4. Research Workflow (3 use cases)
5. Multi-Platform Developer Workflow (3 use cases)

**Git:** Committed and pushed to `{github_org}/openclaw-skill-usecases`

---

## 🚀 Recommended Starting Point / 建议起点

**BEST FIRST STEP:**
Test {internal_grant} proposal writer RIGHT NOW (zero setup required!)

```
Via Telegram/WhatsApp:
"Write {internal_grant} proposal whitepaper: AI-Enhanced Source-to-Source Transformation 
for Heterogeneous Exascale Systems, Category: HPC + AI, Duration: 3 years"
```

This will demonstrate OpenClaw's capabilities immediately and generate actual value for your work at {research_lab}.

---

**Questions?** Ask the main agent to dive deeper into any specific use case from the full report.

**Next Step:** Review full report and decide which 2-3 use cases to implement this week.


path: findings/2026-02-05.md
content: # OpenClaw Use Cases Research Findings
# OpenClaw 使用案例研究成果

**Date / 日期:** 2026-02-05  
**Researcher / 研究员:** OpenClaw Subagent  
**Sources / 来源:** GitHub, OpenClaw Wiki, Official Documentation, Reddit, Community Showcase

---

## Executive Summary / 执行摘要

This research session identified **23+ concrete use cases** across multiple categories, with particular strength in:
- **Developer tooling** (PR automation, code review, testing)
- **Browser automation** (shopping, booking, web scraping)
- **Multi-agent orchestration** patterns
- **Home automation integrations** (3D printing, smart home)
- **Enterprise workflow automation**

本次研究发现了 **23+ 个具体使用案例**，在以下领域表现突出：
- **开发者工具**（PR 自动化、代码审查、测试）
- **浏览器自动化**（购物、预订、网络爬虫）
- **多智能体编排**模式
- **家庭自动化集成**（3D 打印、智能家居）
- **企业工作流自动化**

---

## 1. NEW CATEGORIES (Potential Additions)
## 1. 新类别（潜在补充）

### 1.1 E-Commerce & Shopping Automation
### 1.1 电商与购物自动化

**Description:** Automated grocery shopping, meal planning, and order management using browser control.

**描述：** 使用浏览器控制实现自动化杂货购物、餐饮计划和订单管理。

**Key Example:**
- **Tesco Shop Autopilot** by @marchattonhere
  - Weekly meal plan → regular items → book delivery slot → confirm order
  - Pure browser automation, no API dependencies
  - Source: https://x.com/i/status/2009724862470689131

**核心案例：**
- **Tesco 购物自动驾驶** 来自 @marchattonhere
  - 每周膳食计划 → 常规商品 → 预订配送时段 → 确认订单
  - 纯浏览器自动化，无需 API
  - 来源：https://x.com/i/status/2009724862470689131

---

### 1.2 3D Printing & Hardware Control
### 1.2 3D 打印与硬件控制

**Description:** Real-time monitoring and control of 3D printers through conversational interfaces.

**描述：** 通过对话界面实时监控和控制 3D 打印机。

**Key Example:**
- **Bambu 3D Printer Control** by @tobiasbischoff
  - Status checks, job management, camera feeds, AMS control, calibration
  - BambuLab printer integration via ClawHub skill
  - Source: https://clawhub.ai/tobiasbischoff/bambu-cli

**核心案例：**
- **Bambu 3D 打印机控制** 来自 @tobiasbischoff
  - 状态检查、任务管理、摄像头监控、AMS 控制、校准
  - 通过 ClawHub 技能集成 BambuLab 打印机
  - 来源：https://clawhub.ai/tobiasbischoff/bambu-cli

---

### 1.3 Code Review & PR Management
### 1.3 代码审查与 PR 管理

**Description:** Automated pull request review with feedback delivery to messaging platforms.

**描述：** 自动化拉取请求审查，并将反馈发送到消息平台。

**Key Example:**
- **PR Review → Telegram Feedback** by @bangnokia
  - OpenCode finishes changes → opens PR → OpenClaw reviews diff
  - Delivers "minor suggestions" with clear merge verdict to Telegram
  - Includes critical fixes identification
  - Source: https://x.com/i/status/2010878524543131691

**核心案例：**
- **PR 审查 → Telegram 反馈** 来自 @bangnokia
  - OpenCode 完成更改 → 开启 PR → OpenClaw 审查差异
  - 向 Telegram 发送"次要建议"和明确的合并决策
  - 包含关键修复识别
  - 来源：https://x.com/i/status/2010878524543131691

---

### 1.4 Educational Services Automation
### 1.4 教育服务自动化

**Description:** Automated booking and management of school-related services.

**描述：** 自动化预订和管理学校相关服务。

**Key Example:**
- **ParentPay School Meals** by @George5562
  - Automated UK school meal booking via ParentPay
  - Uses precise mouse coordinates for table cell clicking
  - Overcomes limited API access through browser automation
  - Source: Community showcase

**核心案例：**
- **ParentPay 校餐** 来自 @George5562
  - 通过 ParentPay 自动化英国校餐预订
  - 使用精确鼠标坐标点击表格单元格
  - 通过浏览器自动化克服有限的 API 访问
  - 来源：社区展示

---

### 1.5 Multi-Agent Orchestration
### 1.5 多智能体编排

**Description:** Complex workflows with 14+ specialized agents coordinated by an orchestrator.

**描述：** 由编排器协调的 14+ 个专业智能体的复杂工作流。

**Key Example:**
- **Kev's Dream Team** by @adam91holt
  - 14+ agents under one gateway
  - Opus 4.5 orchestrator delegating to Codex workers
  - Comprehensive architecture: sandboxing, webhooks, heartbeats, delegation flows
  - Technical write-up: https://github.com/adam91holt/orchestrated-ai-articles
  - Clawdspace for agent sandboxing: https://github.com/adam91holt/clawdspace
  - Blog: https://adams-ai-journey.ghost.io/2026-the-year-of-the-orchestrator/

**核心案例：**
- **Kev 的梦之队** 来自 @adam91holt
  - 单一网关下的 14+ 智能体
  - Opus 4.5 编排器委托给 Codex 工作器
  - 全面架构：沙盒、Webhook、心跳、委托流程
  - 技术文档：https://github.com/adam91holt/orchestrated-ai-articles
  - Clawdspace 智能体沙盒：https://github.com/adam91holt/clawdspace
  - 博客：https://adams-ai-journey.ghost.io/2026-the-year-of-the-orchestrator/

---

## 2. DEEP DIVES ON EXISTING CATEGORIES
## 2. 现有类别深度探索

### 2.1 Developer Tools (Enhanced)
### 2.1 开发者工具（增强版）

**New Examples:**

**新案例：**

#### Linear CLI Integration
#### Linear 命令行集成
- **Linear CLI** by @NessZerra
  - CLI for Linear integrating with agentic workflows (Claude Code, OpenClaw)
  - Manage issues, projects, and workflows from terminal
  - First external PR merged!
  - Source: https://github.com/Finesssee/linear-cli

- **Linear 命令行** 来自 @NessZerra
  - 集成智能体工作流（Claude Code, OpenClaw）的 Linear 命令行
  - 从终端管理问题、项目和工作流
  - 首个外部 PR 已合并！
  - 来源：https://github.com/Finesssee/linear-cli

#### Screenshot-to-Markdown Tool
#### 截图转 Markdown 工具
- **SNAG** by @am-will
  - Hotkey screen region → Gemini vision → instant Markdown clipboard
  - Perfect for documentation workflows
  - Source: https://github.com/am-will/snag

- **SNAG** 来自 @am-will
  - 热键截屏区域 → Gemini 视觉 → 即时 Markdown 剪贴板
  - 文档工作流完美工具
  - 来源：https://github.com/am-will/snag

#### Codex Monitor
#### Codex 监控器
- **CodexMonitor** by @odrobnik
  - Homebrew-installed helper to list/inspect/watch local OpenAI Codex sessions
  - CLI + VS Code integration
  - Source: https://clawhub.ai/odrobnik/codexmonitor

- **CodexMonitor** 来自 @odrobnik
  - Homebrew 安装的辅助工具，用于列出/检查/监视本地 OpenAI Codex 会话
  - 命令行 + VS Code 集成
  - 来源：https://clawhub.ai/odrobnik/codexmonitor

#### Agents UI
#### 智能体用户界面
- **Agents UI** by @kitze
  - Desktop app to manage skills/commands across Agents, Claude, Codex, and OpenClaw
  - Unified management interface
  - Source: https://releaseflow.net/kitze/agents-ui

- **Agents UI** 来自 @kitze
  - 桌面应用，跨 Agents、Claude、Codex 和 OpenClaw 管理技能/命令
  - 统一管理界面
  - 来源：https://releaseflow.net/kitze/agents-ui

---

### 2.2 Automation & Workflows (Enhanced)
### 2.2 自动化与工作流（增强版）

#### Dynamic Skill Creation
#### 动态技能创建
- **Wine Cellar Skill** by @prades_maxime
  - Asked AI for a local wine cellar skill
  - AI requests CSV export + storage location
  - Builds and tests skill rapidly (962 bottles example)
  - Source: https://x.com/i/status/2010916352454791216

- **酒窖技能** 来自 @prades_maxime
  - 向 AI 请求本地酒窖技能
  - AI 请求 CSV 导出 + 存储位置
  - 快速构建和测试技能（962 瓶示例）
  - 来源：https://x.com/i/status/2010916352454791216

#### iOS App Development via Chat
#### 通过聊天开发 iOS 应用
- **iOS App via Telegram** by @coard
  - Built complete iOS app with maps and voice recording
  - Deployed to TestFlight entirely via Telegram chat
  - No IDE interaction required
  - Source: Community showcase

- **通过 Telegram 开发 iOS 应用** 来自 @coard
  - 构建完整的 iOS 应用（地图和语音录制）
  - 完全通过 Telegram 聊天部署到 TestFlight
  - 无需 IDE 交互
  - 来源：社区展示

---

### 2.3 Health & Personal Data
### 2.3 健康与个人数据

#### Oura Ring Health Assistant
#### Oura 戒指健康助手
- **Oura Ring Health Assistant** by @AS
  - Personal AI health assistant integrating Oura ring data
  - Combines with calendar, appointments, and gym schedule
  - Personalized health insights and recommendations
  - Source: Community showcase

- **Oura 戒指健康助手** 来自 @AS
  - 集成 Oura 戒指数据的个人 AI 健康助手
  - 结合日历、约会和健身计划
  - 个性化健康洞察和建议
  - 来源：社区展示

---

## 3. ENTERPRISE/COMMERCIAL APPLICATIONS
## 3. 企业/商业应用

### 3.1 Remote File Delivery System
### 3.1 远程文件传输系统

**Use Case:** Secure file sharing for remote OpenClaw instances without direct filesystem access.

**使用案例：** 为无法直接访问文件系统的远程 OpenClaw 实例提供安全文件共享。

**Example:**
- **R2 Upload (Send Me My Files)** by @julianengel
  - Upload to Cloudflare R2/S3
  - Generate secure presigned download links
  - Perfect for remote OpenClaw instances
  - Source: https://clawhub.ai/skills/r2-upload

**示例：**
- **R2 上传（发给我文件）** 来自 @julianengel
  - 上传到 Cloudflare R2/S3
  - 生成安全的预签名下载链接
  - 完美适配远程 OpenClaw 实例
  - 来源：https://clawhub.ai/skills/r2-upload

---

### 3.2 Public Transit Information Systems
### 3.2 公共交通信息系统

**Use Case:** Real-time transit information with accessibility features.

**使用案例：** 具有无障碍功能的实时交通信息。

**Example:**
- **Vienna Transport (Wiener Linien)** by @hjanuschka
  - Real-time departures, disruptions, elevator status
  - Routing assistance for Vienna's public transport
  - Accessibility-focused features
  - Source: https://clawhub.ai/hjanuschka/wienerlinien

**示例：**
- **维也纳交通（Wiener Linien）** 来自 @hjanuschka
  - 实时出发、中断、电梯状态
  - 维也纳公共交通路线协助
  - 以无障碍为重点的功能
  - 来源：https://clawhub.ai/hjanuschka/wienerlinien

---

### 3.3 Tool Call Analytics Dashboard
### 3.3 工具调用分析仪表板

**Use Case:** Monitoring and debugging AI agent tool usage in production.

**使用案例：** 监控和调试生产环境中的 AI 智能体工具使用情况。

**Example:**
- **Tool Call Viewer** from Reddit r/openclaw
  - Parses OpenClaw session files, displays all tool calls in table
  - Multi-select filters (tool, model, session, date range)
  - Auto-refresh (10s polling) for real-time monitoring
  - Export filtered results as JSON
  - Zero dependencies (just Node.js)
  - Demo mode for testing without exposing sessions
  - Source: https://www.reddit.com/r/openclaw/comments/1qw33of/

**示例：**
- **工具调用查看器** 来自 Reddit r/openclaw
  - 解析 OpenClaw 会话文件，在表格中显示所有工具调用
  - 多选过滤器（工具、模型、会话、日期范围）
  - 自动刷新（10秒轮询）实现实时监控
  - 将过滤结果导出为 JSON
  - 零依赖（仅需 Node.js）
  - 演示模式，无需暴露会话即可测试
  - 来源：https://www.reddit.com/r/openclaw/comments/1qw33of/

---

## 4. INTEGRATION PATTERNS WITH SPECIFIC TOOLS
## 4. 特定工具集成模式

### 4.1 Telegram Integration Patterns
### 4.1 Telegram 集成模式

**Pattern:** Voice notes with TTS integration
**模式：** 语音备忘录与 TTS 集成

**Example:**
- **Telegram Voice Notes (papla.media)**
  - Wraps papla.media TTS service
  - Sends results as Telegram voice notes (no autoplay)
  - Better UX than standard text-to-speech
  - Documentation: https://papla.media/docs

**示例：**
- **Telegram 语音备忘录（papla.media）**
  - 封装 papla.media TTS 服务
  - 将结果作为 Telegram 语音备忘录发送（无自动播放）
  - 比标准文本转语音更好的用户体验
  - 文档：https://papla.media/docs

---

### 4.2 Beeper Integration
### 4.2 Beeper 集成

**Pattern:** Unified messaging control across platforms
**模式：** 跨平台统一消息控制

**Example:**
- **Beeper CLI** by @jules
  - Read, send, and archive messages via Beeper Desktop
  - Uses Beeper local MCP API
  - Agents can manage all chats (iMessage, WhatsApp, etc.) in one place
  - Source: https://github.com/blqke/beepcli

**示例：**
- **Beeper 命令行** 来自 @jules
  - 通过 Beeper Desktop 阅读、发送和归档消息
  - 使用 Beeper 本地 MCP API
  - 智能体可在一个地方管理所有聊天（iMessage、WhatsApp 等）
  - 来源：https://github.com/blqke/beepcli

---

### 4.3 Home Assistant Patterns (Inferred)
### 4.3 Home Assistant 模式（推断）

**Status:** Not explicitly documented in current sources, but OpenClaw's node system and webhook capabilities suggest strong compatibility.

**状态：** 当前资料中未明确记录，但 OpenClaw 的节点系统和 Webhook 功能表明强兼容性。

**Potential Pattern:**
- OpenClaw webhook receives Home Assistant events
- Agent processes state changes and triggers actions
- Responses delivered via preferred messaging channel
- Cron jobs for scheduled home automation tasks

**潜在模式：**
- OpenClaw Webhook 接收 Home Assistant 事件
- 智能体处理状态变化并触发操作
- 通过首选消息渠道传递响应
- 用于计划家庭自动化任务的 Cron 作业

---

### 4.4 Notion Integration (Inferred)
### 4.4 Notion 集成（推断）

**Status:** Not explicitly documented, but feasible through OpenClaw's exec tool and Notion API.

**状态：** 未明确记录，但通过 OpenClaw 的 exec 工具和 Notion API 可行。

**Potential Pattern:**
- Use Notion API via exec tool or custom skill
- Read/write pages, databases, and properties
- Automated content updates from chat commands
- Integration with other data sources for enriched notes

**潜在模式：**
- 通过 exec 工具或自定义技能使用 Notion API
- 读/写页面、数据库和属性
- 从聊天命令自动更新内容
- 与其他数据源集成以丰富笔记

---

## 5. CROSS-PLATFORM WORKFLOWS
## 5. 跨平台工作流

### 5.1 GitHub → Telegram → WhatsApp
### 5.1 GitHub → Telegram → WhatsApp

**Workflow:** PR opened → OpenClaw reviews → Feedback to Telegram → Summary to WhatsApp

**工作流：** 开启 PR → OpenClaw 审查 → 反馈到 Telegram → 摘要到 WhatsApp

**Components:**
1. GitHub webhook triggers OpenClaw
2. Browser tool analyzes diff
3. Message tool sends detailed feedback to Telegram
4. Cron job sends daily summary to WhatsApp

**组件：**
1. GitHub Webhook 触发 OpenClaw
2. 浏览器工具分析差异
3. 消息工具向 Telegram 发送详细反馈
4. Cron 作业向 WhatsApp 发送每日摘要

---

### 5.2 Calendar → Email → Slack → SMS
### 5.2 日历 → 邮件 → Slack → 短信

**Workflow:** Calendar event → Email notification → Agent analysis → Slack message → SMS reminder

**工作流：** 日历事件 → 邮件通知 → 智能体分析 → Slack 消息 → 短信提醒

**Components:**
1. Gmail Pub/Sub hook receives calendar invites
2. Agent extracts key details
3. Posts to team Slack channel
4. Sends SMS reminder 30min before via nodes tool

**组件：**
1. Gmail Pub/Sub 钩子接收日历邀请
2. 智能体提取关键细节
3. 发布到团队 Slack 频道
4. 通过节点工具在 30 分钟前发送短信提醒

---

### 5.3 Browser → Canvas → Voice
### 5.3 浏览器 → 画布 → 语音

**Workflow:** Browser automation → Visual result on Canvas → Voice notification on iOS

**工作流：** 浏览器自动化 → Canvas 上的视觉结果 → iOS 上的语音通知

**Components:**
1. Browser tool completes shopping checkout
2. Canvas displays confirmation screen
3. Nodes tool sends voice notification to paired iOS device

**组件：**
1. 浏览器工具完成购物结账
2. Canvas 显示确认屏幕
3. 节点工具向配对的 iOS 设备发送语音通知

---

## 6. TECHNICAL ARCHITECTURE INSIGHTS
## 6. 技术架构洞察

### 6.1 Sandbox & Security Patterns
### 6.1 沙盒与安全模式

**Key Finding:** Kev's Dream Team demonstrates production-grade sandboxing.

**关键发现：** Kev 的梦之队展示了生产级沙盒。

**Architecture:**
- Main sessions: full host access
- Group/channel sessions: Docker sandboxes
- Tool allowlists per agent type
- Elevated permissions with explicit approval
- Source: https://github.com/adam91holt/clawdspace

**架构：**
- 主会话：完整主机访问权限
- 组/频道会话：Docker 沙盒
- 每种智能体类型的工具白名单
- 具有明确批准的提升权限
- 来源：https://github.com/adam91holt/clawdspace

---

### 6.2 Multi-Channel Routing
### 6.2 多频道路由

**Supported Channels (15+):**
1. WhatsApp
2. Telegram
3. Discord
4. Slack
5. Google Chat
6. Signal
7. BlueBubbles (iMessage)
8. iMessage (legacy)
9. Microsoft Teams
10. Matrix
11. Zalo
12. Zalo Personal
13. WebChat
14. Feishu (plugin)
15. Mattermost (plugin)
16. LINE (plugin)
17. Nextcloud Talk (plugin)
18. Nostr (plugin)
19. Tlon (plugin)
20. Twitch (plugin)

**支持的频道（15+）：**
（同上列表）

**Pattern:** Single Gateway process routes to all channels with per-channel configuration.

**模式：** 单一网关进程通过每个频道的配置路由到所有频道。

---

### 6.3 Tool Profiles & Permission Management
### 6.3 工具配置文件与权限管理

**Discovery:** New tool profile system for granular permissions.

**发现：** 用于细粒度权限的新工具配置文件系统。

**Profiles:**
- `minimal`: session_status only
- `coding`: group:fs, group:runtime, group:sessions, group:memory, image
- `messaging`: group:messaging, sessions_list, sessions_history, sessions_send, session_status
- `full`: no restrictions

**配置文件：**
- `minimal`：仅 session_status
- `coding`：group:fs、group:runtime、group:sessions、group:memory、image
- `messaging`：group:messaging、sessions_list、sessions_history、sessions_send、session_status
- `full`：无限制

**Use Case:** Support agent with messaging-only profile, main agent with full coding access.

**使用案例：** 仅消息配置文件的支持智能体，具有完整编码访问权限的主智能体。

---

## 7. GAPS & OPPORTUNITIES
## 7. 缺口与机会

### 7.1 Missing Use Cases (Not Found in Current Search)
### 7.1 缺失的使用案例（当前搜索中未找到）

1. **Enterprise CRM Integration** (Salesforce, HubSpot)
2. **Video Conferencing Automation** (Zoom, Teams auto-join)
3. **Financial Data Analysis** (accounting, invoicing)
4. **Legal Document Processing**
5. **Medical Records Management**
6. **Real Estate Property Management**
7. **Restaurant/Hospitality Operations**

1. **企业 CRM 集成**（Salesforce、HubSpot）
2. **视频会议自动化**（Zoom、Teams 自动加入）
3. **财务数据分析**（会计、发票）
4. **法律文件处理**
5. **医疗记录管理**
6. **房地产物业管理**
7. **餐饮/酒店运营**

---

### 7.2 Emerging Patterns
### 7.2 新兴模式

1. **Voice-First Workflows:** Increasing demand for voice notes and TTS/STT integration
2. **Browser-as-API:** Browser automation replacing API dependencies
3. **Chat-to-Production:** Building and deploying apps entirely through chat (iOS example)
4. **Agent Monitoring:** Growing need for observability tools (Tool Call Viewer)

1. **语音优先工作流：** 对语音备忘录和 TTS/STT 集成的需求不断增长
2. **浏览器作为 API：** 浏览器自动化取代 API 依赖
3. **聊天到生产：** 完全通过聊天构建和部署应用（iOS 示例）
4. **智能体监控：** 对可观察性工具的需求不断增长（工具调用查看器）

---

## 8. RECOMMENDED NEXT STEPS
## 8. 推荐后续步骤

1. **Create ClawHub registry** for community skills (already exists at clawhub.ai)
2. **Document enterprise patterns** for multi-agent orchestration
3. **Build integration templates** for common tools (Notion, Linear, Home Assistant)
4. **Develop observability toolkit** for production deployments
5. **Create certification program** for OpenClaw skills/integrations

1. **为社区技能创建 ClawHub 注册表**（已存在于 clawhub.ai）
2. **记录企业模式**用于多智能体编排
3. **为常用工具构建集成模板**（Notion、Linear、Home Assistant）
4. **为生产部署开发可观察性工具包**
5. **为 OpenClaw 技能/集成创建认证计划**

---

## 9. SOURCES & REFERENCES
## 9. 来源与参考

### Primary Sources / 主要来源
- OpenClaw GitHub: https://github.com/openclaw/openclaw
- Official Documentation: https://docs.openclaw.ai
- OpenClaw Wiki: https://openclawwiki.org
- Community Showcase: https://docs.openclaw.ai/start/showcase
- Reddit r/openclaw: https://www.reddit.com/r/openclaw/
- ClawHub Registry: https://clawhub.ai/

### Community Contributors / 社区贡献者
- @marchattonhere (Tesco automation)
- @bangnokia (PR review workflow)
- @prades_maxime (Wine cellar skill)
- @am-will (SNAG screenshot tool)
- @tobiasbischoff (Bambu 3D printer)
- @hjanuschka (Vienna transport)
- @George5562 (ParentPay automation)
- @adam91holt (Multi-agent orchestration)
- @NessZerra (Linear CLI)
- @jules (Beeper CLI)
- @julianengel (R2 Upload)
- @AS (Oura health assistant)
- @coard (iOS app via Telegram)
- @odrobnik (CodexMonitor)
- @kitze (Agents UI)

---

## 10. RESEARCH LIMITATIONS
## 10. 研究局限

1. **API Access:** Brave Search API not configured; relied on direct URL fetching
2. **Discord Content:** Unable to access Discord server content (requires authentication)
3. **Twitter/X:** Limited access to real-time social media discussions
4. **Rate Limiting:** GitHub rate limits prevented full issue/discussion scraping
5. **Time Constraint:** 30-minute research window limited depth of analysis

1. **API 访问：** 未配置 Brave Search API；依赖直接 URL 获取
2. **Discord 内容：** 无法访问 Discord 服务器内容（需要身份验证）
3. **Twitter/X：** 对实时社交媒体讨论的访问有限
4. **速率限制：** GitHub 速率限制阻止了完整的问题/讨论抓取
5. **时间限制：** 30 分钟研究窗口限制了分析深度

---

## CONCLUSION / 结论

OpenClaw demonstrates remarkable versatility across developer tools, automation, and enterprise workflows. The most exciting developments are in:

1. **Multi-agent orchestration** (14+ agents working together)
2. **Browser-based automation** (replacing API dependencies)
3. **Cross-platform messaging** (15+ channels)
4. **Production-grade security** (sandboxing, tool profiles)
5. **Community-driven innovation** (ClawHub skills registry)

The ecosystem is rapidly evolving with strong community contributions and increasing enterprise adoption patterns. Key growth areas include health/wellness, hardware control, and educational services automation.

OpenClaw 在开发者工具、自动化和企业工作流方面展现出显著的多功能性。最令人兴奋的发展领域包括：

1. **多智能体编排**（14+ 智能体协同工作）
2. **基于浏览器的自动化**（取代 API 依赖）
3. **跨平台消息传递**（15+ 频道）
4. **生产级安全**（沙盒、工具配置文件）
5. **社区驱动创新**（ClawHub 技能注册表）

生态系统正在快速发展，社区贡献强劲，企业采用模式不断增加。关键增长领域包括健康/保健、硬件控制和教育服务自动化。

---

**Total Use Cases Documented:** 23+  
**New Categories Identified:** 5  
**Integration Patterns:** 8+  
**Enterprise Applications:** 10+

**已记录的使用案例总数：** 23+  
**已识别的新类别：** 5  
**集成模式：** 8+  
**企业应用：** 10+

---

*Research conducted by OpenClaw Subagent on 2026-02-05*  
*研究由 OpenClaw 子智能体于 2026-02-05 完成*


path: findings/2026-02-09.md
content: # Findings / 发现 - 2026-02-09

## 12:45 PST

### 小企业自动化指南 / Small Business Automation Guide — Business/商业

- **来源/Source**: https://www.reddit.com/r/OpenClawCentral/comments/1r08kqh/how_openclaw_can_supercharge_your_small_business/
- **平台/Platform**: Reddit r/OpenClawCentral
- **描述/Description**:
  - 🇨🇳 一份详尽的小企业OpenClaw使用指南，包含5个具体用例和实际ROI数据
  - 🇺🇸 Comprehensive beginner's guide for small business owners with 5 concrete use cases and real ROI data
- **亮点/Why interesting**:
  - 🇨🇳 报告节省90+小时/月，内容创作节省$45,000+，SEO流量从200→700/天
  - 🇺🇸 Reports 90+ hours/month saved, $45,000+ saved on content creation, SEO traffic 200→700/day

**Detailed Use Cases from Post:**

#### 1. Lead Generation & Sales / 销售线索生成
- Scans CRM (Google Sheets/HubSpot), finds stale leads, drafts personalized outreach
- Result: Marketing freelancer doubled conversions with auto follow-ups
- Quote: "It pulls context like 'They mentioned budget issues last month—tie in our new promo.'"

#### 2. Content Creation Factory / 内容批量生产
- Takes keyword → researches → writes full SEO-optimized articles
- Result: Online store created 100+ SEO pages in ONE DAY
- Traffic boost: 200 → 700 daily visitors
- Savings: Thousands on writers

#### 3. 24/7 Customer Support / 全天候客服
- Monitors emails/chats, answers FAQs, flags complex issues to human
- Result: Repair shop reduced response time from DAYS to MINUTES
- After-hours queries turned into happy reviews

#### 4. Daily Operations & Analytics / 日常运营分析
- Runs reports on sales, inventory, ad performance
- Spots trends: "Your top product is low stock—reorder?"
- Result: Food business automated invoice processing on cheap device

#### 5. Multi-Agent Teams / 多智能体团队
- Create "squads" with specialized bots: Researcher + Writer + Editor
- Result: Consulting firm freed team for creative work
- Freelancers use for "self-managing" to-dos

**Key Stats:**
- 90+ hours/month saved
- $45,000+ saved on content
- Under $20/month VPS hosting
- Setup time: "Under an hour to basics, a weekend to business-ready"

---

### OpenClaw科幻故事 / The Last Prompt: An Open Claw Story — Creative/创意

- **来源/Source**: https://blog.marekrosa.org/2026/02/the-last-prompt-an-open-claw-story/
- **平台/Platform**: Reddit r/openclaw crosspost, originally r/scifi
- **Reddit链接**: https://www.reddit.com/r/openclaw/comments/1r0f8lx/the_last_prompt_an_open_claw_story/
- **描述/Description**:
  - 🇨🇳 以OpenClaw为主题的科幻短篇故事
  - 🇺🇸 Sci-fi short story themed around OpenClaw
- **亮点/Why interesting**:
  - 🇨🇳 OpenClaw已进入流行文化，成为科幻创作素材
  - 🇺🇸 OpenClaw entering pop culture as creative fiction subject

---

### Discord网关稳定性问题 / Discord Gateway Stability Issue — Technical/技术

- **来源/Source**: https://www.reddit.com/r/openclaw/comments/1r0ew7g/what_do_you_do_when_the_gateway_disconnects/
- **平台/Platform**: Reddit r/openclaw
- **描述/Description**:
  - 🇨🇳 用户报告Discord插件每天至少崩溃一次，需要手动重启网关
  - 🇺🇸 User reports Discord plugin crashes at least once daily, requires manual gateway restart
- **亮点/Why interesting**:
  - 🇨🇳 常见问题 - 我们今天刚在{home_server}上修复了类似问题（版本不匹配导致EPIPE错误）
  - 🇺🇸 Common issue - we just fixed similar problem on {home_server} today (version mismatch causing EPIPE error)
- **解决方案/Solution mentioned**:
  - systemd with Restart=always
  - Remote restart via SSH
  - Need better monitoring/alerting

---

## Emerging Trends / 新兴趋势

### 1. 专用设备部署 / Dedicated Device Deployment
- 🇨🇳 越来越多用户在低成本设备（树莓派、迷你电脑）上24/7运行OpenClaw
- 🇺🇸 Growing trend of running OpenClaw 24/7 on cheap devices (Pi, mini PCs) as "night shift worker"

### 2. 多智能体协作 / Multi-Agent Collaboration
- 🇨🇳 用户构建专业化的"机器人小队"：研究员 + 写手 + 编辑
- 🇺🇸 Users building specialized "bot squads": Researcher + Writer + Editor collaborating

### 3. 小企业采用加速 / Small Business Adoption Accelerating
- 🇨🇳 从技术爱好者扩展到真正的小企业主（咖啡馆、餐车、自由职业者）
- 🇺🇸 Expanding from tech enthusiasts to real small business owners (cafes, food trucks, freelancers)

### 4. 付费设置服务 / Paid Setup Services
- 🇨🇳 新商业模式出现：为非技术用户提供OpenClaw设置和优化服务
- 🇺🇸 New business model emerging: OpenClaw setup/optimization services for non-technical users

---

## Stats Update / 统计更新

| Metric | Value | Source |
|--------|-------|--------|
| r/openclaw subscribers | 13,681 | Reddit API |
| r/scifi subscribers | 4,447,592 | Reddit API (crosspost reach) |
| Setup cost | <$20/month VPS | Reddit post |
| Time savings | 90+ hours/month | Reddit post |
| Content savings | $45,000+ | Reddit post |


path: findings/2026-02-12.md
content: # Findings / 发现 - 2026-02-12

## 12:48 PST

### 多智能体社交媒体自动化 / Multi-Agent Social Media Automation — Content/Marketing

- **来源/Source**: https://www.reddit.com/r/SideProject/comments/1r2mbai/i_built_4_openclaws_in_4_hours_heres_the/
- **平台/Platform**: Reddit
- **作者/Author**: u/PHY041
- **发布时间/Published**: Feb 12, 2026 (14 hours ago)
- **描述/Description**:
  - 🇨🇳 3个专业化OpenClaw智能体协同工作，完全通过Markdown配置文件实现社交媒体自动化。4小时搭建，3天内Reddit karma从20涨到100，Twitter互动率100%，零垃圾标记。
  - 🇺🇸 3-agent orchestration system built entirely with markdown config files. 4 hours setup, 3 days results: Reddit karma 20→100, Twitter 100% engagement success, zero spam flags.
- **架构/Architecture**:
  - 🇨🇳 
    - **智能体1: 增长引擎** - Reddit/Twitter内容发布，10个定时任务，AppleScript控制真实Chrome浏览器规避检测
    - **智能体2: 创业导师** - 297集Lenny's Podcast RAG知识库，提供框架和引用
    - **智能体3: 主助理** - 协调和委派任务
    - 所有智能体在Telegram群组"PHY's Council"中协作
  - 🇺🇸 
    - **Agent 1: Growth Engine** - Reddit/Twitter posting, 10 cron jobs, AppleScript-controlled real Chrome browser (evades headless detection)
    - **Agent 2: Startup Mentor** - RAG over 297 Lenny's Podcast episodes
    - **Agent 3: Main Assistant** - Delegation and coordination
    - All agents collaborate in Telegram group "PHY's Council"
- **亮点/Why interesting**:
  - 🇨🇳 **50分质量门槛系统**：使用STEPPS框架（社交货币、触发器、情感、公开性、实用价值、故事性）评分所有内容，<40分不发布。防止了"为发布而发布"的低质量内容。这是生产级多智能体系统的关键创新——质量控制优先于数量。
  - 🇺🇸 **50-point quality rubric**: STEPPS framework (Social Currency, Triggers, Emotion, Public, Practical Value, Stories) scores all content. <40/50 = no post. Prevents volume-over-quality spam. Key innovation for production multi-agent systems.
- **技术细节/Technical Details**:
  - 🇨🇳 AppleScript控制真实登录的Chrome实例（非无头浏览器），绕过Reddit的`navigator.webdriver=true`检测。Reddit多段落引用格式bug：必须用`\n\n`而非blockquote标记。
  - 🇺🇸 AppleScript controls real logged-in Chrome (not headless) to bypass Reddit's `navigator.webdriver=true` detection. Reddit multi-paragraph blockquote bug: must use `\n\n` instead of blockquote markers.
- **成本/Cost**: $12 (3 days) ≈ $120/month vs $800-1200/month for VA
- **ROI**: 15-20 hours/week → 3-4 hours/week oversight
- **开源代码/Open Source**: https://github.com/PHY041/claude-skill-reddit

---

## 12:51 PST

### 营销团队AI自动化剧本 / Marketing Team AI Automation Playbook — Marketing

- **来源/Source**: https://www.digitalapplied.com/blog/openclaw-marketing-teams-ai-automation-playbook-2026
- **平台/Platform**: Digital Applied Blog
- **发布时间/Published**: Feb 11, 2026
- **描述/Description**:
  - 🇨🇳 营销团队6大高影响力自动化工作流：内容创作、社交媒体、邮件营销、SEO优化、分析报告、营销自动化。每个工作流包含设置说明、示例提示词和质量控制检查点。
  - 🇺🇸 6 high-impact marketing automation workflows: content creation, social media, email marketing, SEO optimization, analytics reporting, marketing automation. Each workflow includes setup instructions, example prompts, and quality control checkpoints.
- **关键指标/Key Metrics**:
  - 🇨🇳 
    - 15-20小时/周时间节省
    - 内容产出3x提升
    - 报告时间减少85%
    - 研究时间减少70%
  - 🇺🇸 
    - 15-20h/week time saved
    - +3x content output
    - -85% report time
    - -70% research time
- **工作流示例/Workflow Examples**:
  - 🇨🇳 
    - **内容创作管道**：研究简报（10分钟 vs 3小时手动）→ AI初稿 → **人工审核**（强制，非可选）→ 发布
    - **关键词研究**：4-6小时 → 30分钟
    - **竞品分析**：2-3小时/竞品 → 15分钟分析Top 5
    - **内容审计**：全天（50+页面）→ 2小时
    - **元标签生成**：15分钟/页面 → 批量处理100+页面几分钟内完成
  - 🇺🇸 
    - **Content pipeline**: Research brief (10 min vs 3h manual) → AI draft → **Human review** (mandatory, not optional) → Publish
    - **Keyword research**: 4-6h → 30 min
    - **Competitor analysis**: 2-3h per competitor → 15 min for top 5
    - **Content audit**: Full day (50+ pages) → 2h
    - **Meta tag generation**: 15 min/page → batch 100+ pages in minutes
- **亮点/Why interesting**:
  - 🇨🇳 明确区分"AI能做什么"与"人类必须做什么"：AI处理研究、数据收集、初稿生成；人类负责战略、品牌声音、质量控制。这是可持续的分工模型，而非"完全自动化"的幻想。
  - 🇺🇸 Clear separation of "what AI can do" vs "what humans must do": AI handles research, data gathering, first-draft generation; humans own strategy, brand voice, quality control. This is a sustainable division of labor, not "full automation" fantasy.
- **实施路线图/Implementation Roadmap**:
  - Week 1: Foundation (email, browser, content research)
  - Week 2: Content creation pipeline
  - Week 3: Social media distribution
  - Week 4: Analytics reporting automation

---

## 12:52 PST

### 企业级自动化实战 / Enterprise Automation in Production — Business/Enterprise

- **来源/Source**: https://www.digitalapplied.com/blog/openclaw-enterprise-automation-business-use-cases-guide
- **平台/Platform**: Digital Applied Blog
- **发布时间/Published**: Feb 8, 2026
- **描述/Description**:
  - 🇨🇳 企业级OpenClaw部署的具体用例、实施模式和ROI测算。所有工作流均为2026年2月在实际企业/代理公司中运行的生产环境案例。
  - 🇺🇸 Concrete enterprise use cases with implementation patterns and measured ROI. Every workflow is running in production at agencies and businesses in February 2026.
- **关键指标/Key Metrics**:
  - 🇨🇳 
    - 邮件时间节省78%
    - 客户入职速度12x
    - 报告生成时间：4-6小时 → 5分钟
    - ROI回收周期：30天
  - 🇺🇸 
    - 78% email time saved
    - 12x onboarding speed
    - Report generation: 4-6h → 5 min
    - ROI timeline: 30 days
- **企业用例/Enterprise Use Cases**:
  - 🇨🇳 
    - **自动邮件分类**：每30分钟扫描收件箱，按紧急程度分类，起草常规查询回复，通过Slack发送优先级摘要。2小时/天 → 25分钟/天。
    - **客户入职自动化**：一条消息触发完整入职流程（文件夹创建、欢迎邮件、CRM录入、会议邀请、权限分配）。3-4小时 → 15分钟，零管理错误。
    - **KPI报告工作流**：自动从Google Analytics、广告平台、CRM、项目管理工具收集数据，生成带图表和洞察的格式化报告，每周一8am通过邮件/Slack分发。4-6小时 → 5分钟。
    - **客户支持自动化**：通过WhatsApp/Telegram作为一线支持智能体，处理FAQ，创建工单，智能升级复杂问题。
    - **多渠道通信**：客户邮件触发Slack通知，团队回复自动路由回客户邮件；WhatsApp对话自动记录到CRM；项目更新根据团队偏好分发到Slack/Discord/邮件。
  - 🇺🇸 
    - **Automated Email Triage**: Scans inbox every 30 min, categorizes by urgency, drafts responses for routine queries, sends prioritized summary via Slack. 2h/day → 25 min/day.
    - **Client Onboarding Automation**: One message triggers full onboarding sequence (folder creation, welcome email, CRM entry, calendar invites, access provisioning). 3-4h → 15 min, zero admin errors.
    - **KPI Reporting Workflows**: Auto-collects data from Google Analytics, ad platforms, CRM, project management tools, generates formatted report with charts/insights, distributes via email/Slack every Monday 8am. 4-6h → 5 min.
    - **Customer Support Automation**: First-line support agent via WhatsApp/Telegram, handles FAQ, ticket creation, intelligent escalation.
    - **Multi-Channel Communications**: Client emails trigger Slack notifications, team responses route back via email; WhatsApp conversations auto-logged in CRM; project updates distributed to Slack/Discord/email based on team preferences.
- **企业部署策略/Enterprise Deployment**:
  - 🇨🇳 Docker容器化、专用服务账户、网络隔离、凭证管理（使用企业密钥管理器）、审计日志（合规/故障排查）
  - 🇺🇸 Docker containerization, dedicated service accounts, network isolation, credential management (enterprise secret manager), audit logging (compliance/troubleshooting)
- **ROI计算公式/ROI Framework**:
  - 🇨🇳 5人团队案例：每周10小时可自动化任务 × $50/小时 × 60%自动化率 = 月节省$6,000，API成本约$100/月 → **60倍ROI**
  - 🇺🇸 5-person team example: 10h/week automatable tasks × $50/hour × 60% automation = $6,000/month savings, ~$100/month API costs → **60x ROI**
- **亮点/Why interesting**:
  - 🇨🇳 OpenClaw的企业优势：1) 数据不离开网络（GDPR合规、客户保密性）；2) 自然语言配置，非技术人员可创建/修改工作流；3) 适用于任何Web应用/API/消息平台，无需等待供应商特定连接器。这是与Zapier/Power Automate等传统工作流工具的核心差异。
  - 🇺🇸 OpenClaw's enterprise advantage: 1) Data never leaves network (GDPR, client confidentiality); 2) No-code via natural language; 3) Works with any web app/API/messaging platform—no vendor-specific connector wait. Core differentiator vs Zapier/Power Automate.

---

## 12:53 PST

### 25+真实用例电子书 / 25+ Real Use Cases Ebook — General/Showcase

- **来源/Source**: https://www.forwardfuture.ai/p/what-people-are-actually-doing-with-openclaw-25-use-cases
- **平台/Platform**: Forward Future AI (Substack)
- **发布时间/Published**: Feb 2-4, 2026
- **格式/Format**: PDF, 41 pages, Free
- **描述/Description**:
  - 🇨🇳 50+生产环境运行的自动化案例，涵盖业务运营、开发工作流、内容营销、个人生产力、家庭基础设施。每个案例都有逐步对话式教程、实际部署示例、工具/API要求。
  - 🇺🇸 50+ working automations across business, development, content, and personal productivity. Each with step-by-step conversational tutorials, real deployment examples, tool/API requirements.
- **涵盖领域/Coverage**:
  - 🇨🇳 
    - **业务运营**：完整业务栈（邮件、CRM、任务管理、简报）、CEO级仪表盘、自主业务管理者（spawns sub-agents）
    - **开发工作流**：手机通过Telegram构建应用功能、自动化dev管道（监控→部署）、持久后台任务+智能通知
    - **内容营销**：视频制作自动化（idea→storyboard）、YouTube分析跟踪（数百视频）、品牌声音一致性维护
    - **个人生产力**：早晨简报（节省30+分钟/天）、自动日程安排+冲突解决、多邮件账户统一界面
    - **家庭基础设施**：自然语言智能家居控制、24/7监控智能体、无需互联网暴露的安全远程访问
  - 🇺🇸 
    - **Business Operations**: Complete business stack (email, CRM, task management, briefings), CEO-level dashboards, autonomous business managers (spawns sub-agents)
    - **Development Workflows**: Build app features from phone via Telegram, automate dev pipeline (monitoring→deployment), persistent background tasks + smart notifications
    - **Content & Marketing**: Video production automation (idea→storyboard), YouTube analytics tracking (hundreds of videos), brand voice consistency maintenance
    - **Personal Productivity**: Morning briefings (save 30+ min/day), auto-schedule calendar + conflict resolution, multi-email account unified interface
    - **Home & Infrastructure**: Smart home natural language control, 24/7 monitoring agents, secure remote access without internet exposure
- **亮点/Why interesting**:
  - 🇨🇳 "行动优先教程"（action-first tutorials）——不是"可能做什么"，而是"现在正在工作的东西"。所有案例都来自2026年2月2-4日正在运行的实际部署、社区构建、GitHub仓库和生产工作流。
  - 🇺🇸 "Action-first tutorials" — not "what could work" but "what's working now". All cases from actual deployments, community builds, GitHub repos, and production workflows running February 2-4, 2026.
- **来源/Sources**: 1,700+ skills from ClawdHub, Discord community, real deployments

---

## Summary / 总结

🇨🇳 **本次研究新发现**：
1. **多智能体协作已成熟**：PHY041的3智能体系统证明了markdown配置的生产级多智能体架构可行性
2. **质量控制成为关键**：50分STEPPS评分系统是防止"垃圾自动化"的核心创新
3. **企业应用已落地**：不再是个人生产力演示，实际企业/代理公司在用（60倍ROI案例）
4. **人机分工清晰**：AI负责执行和模式识别，人类负责战略和边缘案例。这是可持续模型。
5. **AppleScript规避检测**：控制真实浏览器实例而非无头浏览器，绕过平台检测，这是生产环境的实战技巧

🇺🇸 **Key Discoveries from This Research**:
1. **Multi-agent orchestration is production-ready**: PHY041's 3-agent system proves markdown-configured multi-agent architecture works in production
2. **Quality control is critical**: 50-point STEPPS scoring system is the key innovation preventing "spam automation"
3. **Enterprise adoption is real**: No longer personal productivity demos—actual agencies/businesses running it (60x ROI cases)
4. **Clear human-AI division of labor**: AI handles execution and pattern recognition, humans handle strategy and edge cases. This is the sustainable model.
5. **AppleScript detection evasion**: Controlling real browser instance vs headless bypasses platform detection—production-tested technique

---

**下一步行动/Next Actions**:
- 🇨🇳 将这些发现整合到主目录的SKILL.md中
- 🇺🇸 Integrate these findings into main SKILL.md catalog


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)