OpenClaw/clawhub-security-signals huggingface dataset:
Skill: nogravedev/clawkits-seo-engine (version 1.2.0)

--- name: clawkits-seo-engine description: Generate SEO-optimized blog posts, product descriptions, and website copy with keyword research, meta descriptions, internal linking, and Schema.org markup. Built for freelance content delivery. metadata: openclaw: version: "1.2.0" author: "ClawKits" tags: ["seo", "content", "writing", "blog", "marketing", "freelance"] --- # SEO Content Engine Generate publication-ready, SEO-optimized content that ranks. Built for agents doing freelance content work or managing their own sites. ## What's Included (Full Kit) - **Blog post generation** — 1,500-3,000 word SEO articles with proper heading hierarchy, keyword density, natural placement - **5 content types** — SEO blog posts, product descriptions, landing page copy, website copy, email newsletters - **SEO analysis** — readability scoring, keyword density, heading validation, meta optimization, Schema.org markup - **Complete workflow** — from brief to final delivery with meta tags and structured data - **Quality standards** — Grade 6-8 readability, zero AI-detectable patterns, E-E-A-T compliant - **Pricing guide** — suggested rates for freelance content delivery ($50-$250 per piece) ## Content Types & Pricing Guide | Content Type | Word Count | Suggested Price | |---|---|---| | Blog Post | 1,000 words | $50-75 | | Blog Post | 2,000 words | $100-150 | | Blog Post | 3,000 words | $150-250 | | Product Description | 200-400 words | $15-30 | | Landing Page | 500-1,000 words | $75-150 | ## Get SEO Content Engine Available as part of the ClawKits suite: 👉 **https://clawkits.gumroad.com** Also check out **Agent Core** ($39) and **The Trading Desk** ($29): 👉 **https://clawkits.gumroad.com** ## Author Built by ClawKits — production-tested systems for AI agents. https://clawkits.xyz


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jianghwxm/sysspeek (version 1.0.1)

--- name: syspeek description: Display a compact ASCII dashboard of system health: uptime, CPU load, memory usage, disk usage, and top open network ports. Use when the user asks to "peek" at the system, check system status, or view a quick system overview. --- # syspeek — System Peek Displays a compact ASCII dashboard of system health: uptime, CPU load, memory, disk, and top network connections. ## Usage ```bash ~/.openclaw/workspace/skills/syspeek/scripts/syspeek.sh ``` ## Output ``` ╔══════════════════════════════════════╗ ║ SYSTEM PEEK ║ ╠══════════════════════════════════════╣ ║ uptime │ 15:42:38 up 3 days ... ║ ║ CPU load │ 0.12 0.08 0.01 (1/4) ║ ║ memory │ 6.2G / 15G (41%) ║ ║ disk root │ 22G / 100G (22%) ║ ║ top ports │ tcp 22,443,3306,6379 ║ ╚══════════════════════════════════════╝ ``` ## Implementation - `scripts/syspeek.sh` — POSIX shell script, no external dependencies beyond standard Linux tools


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: harshhmaniya/linkedin-lead-generation (version 1.0.0)

--- name: linkedin-lead-gen description: Search for, research, and verify non-tech founders on LinkedIn to identify high-value prospects for technology services (Web Dev, ERP, CRM, App Dev, SEO, AI). Generates professional PDF reports. Use when asked to find potential clients or leads. --- # LinkedIn Lead Generation & Research This skill provides a structured workflow for identifying and verifying high-quality business leads. ## Workflow 1. **Target Selection**: Define industries that need digital transformation but aren't tech-native (e.g., Textile, Manufacturing, Real Estate, Healthcare, Energy, D2C Brands). 2. **LinkedIn Search**: - Use `browser` tool to search LinkedIn: `https://www.linkedin.com/search/results/people/?keywords=founder+CEO+[Industry]+[Location]` - Filter for 2nd-degree connections for easier outreach. 3. **Strict Filtering**: - EXCLUDE any founder already in the IT, Software, or Digital Marketing space. - EXCLUDE founders whose profiles indicate they already have a strong internal tech team. 4. **Deep Research**: - Visit each candidate's LinkedIn profile. - Find their company website URL. - Visit the company website using `web_fetch` or `browser`. 5. **Gap Analysis**: - Analyze the website for: Speed, Mobile Responsiveness, SEO, E-commerce capabilities, and overall modern aesthetic. - Identify specific needs (e.g., "No mobile app", "Outdated UI", "No CRM/ERP integration"). 6. **Reporting**: - Compile a list of 10 qualified prospects. - Include: Name, LinkedIn URL, Company, Website Status, Specific Needs, and a "Pitch Idea". - Generate a professional HTML-based PDF report. ## Tools to Use - **browser**: For LinkedIn search and profile viewing. - **web_fetch**: For quick website analysis. - **write**: To create the HTML template for the PDF. ## PDF Template (HTML Structure) Use the following CSS principles for a premium feel: - LinkedIn Blue (`#0077b5`) for headers. - Clean, modern typography (sans-serif). - Priority badges (High/Medium/Low). - Structured grids for easy scanning. ## Outreach Principles - **Personalized**: Reference something specific from their profile or website. - **Problem-First**: Focus on the gap identified (e.g., "Your brand is growing on social, but your website is broken"). - **Local Advantage**: If in the same city (Surat), emphasize face-to-face consultation.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: litiao1224/image-analysis-litiao (version 1.0.0)

--- name: image-analysis-litiao description: Analyze images using browser and vision capabilities. homepage: https://github.com/openclaw/openclaw metadata: {"clawdbot":{"emoji":"🖼️","requires":{"browser":true}}} --- # 图片分析技能 使用浏览器和视觉能力来分析图片。 ## 功能 - 打开图片链接 - 截取网页快照 - 分析图片内容 ## 使用方法 ### 打开图片链接 ```bash # 使用 browser 工具打开图片 browser action=open url="图片链接" ``` ### 截取网页快照 ```bash # 使用 browser snapshot 截取页面 browser action=snapshot targetId="页面ID" ``` ### 分析图片 对于 QQ 发来的图片，可以： 1. 提取图片链接 2. 使用 browser 打开 3. 描述图片内容 ## 支持的图片格式 - PNG - JPG/JPEG - GIF - WebP ## 注意事项 - 需要 browser 工具支持 - Playwright 需要完整安装（不是 playwright-core） - 图片链接需要可访问


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: fabe/mycroft (version 1.0.2)

--- name: mycroft description: EPUB and ebook ingestion, local vector index, and Q&A CLI for books. homepage: https://github.com/fabe/mycroft metadata: {"clawdbot":{"emoji":"📚","requires":{"bins":["mycroft"],"env":["OPENAI_API_KEY"]},"install":[{"id":"npm","kind":"npm","package":"@fs/mycroft","bins":["mycroft"],"label":"Install mycroft (npm)"}]}} --- # mycroft Use `mycroft` to ingest EPUBs and ebooks, build a local vector index, and ask questions about a book. Setup (once) - `export OPENAI_API_KEY="..."` - `mycroft config onboard` - `mycroft config resolve` Common commands - List books: `mycroft book list` - Ingest EPUB: `mycroft book ingest /path/to/book.epub` - Ingest with summaries: `mycroft book ingest /path/to/book.epub --summary` - Ingest with batch embeddings (50% cheaper): `mycroft book ingest /path/to/book.epub --batch` - Ingest with batch summaries + embeddings: `mycroft book ingest /path/to/book.epub --batch --summary` - Resume batch ingestion: `mycroft book ingest resume <id>` - Check ingestion status: `mycroft book ingest status <id>` - Show metadata: `mycroft book show <id>` - Ask a question: `mycroft book ask <id> "What is the main conflict?"` - Search passages: `mycroft book search <id> "mad hatter" --top-k 5` - Delete book: `mycroft book delete <id> --force` - Start chat: `mycroft chat start <id>` - Ask in session: `mycroft chat ask <session> "What does this foreshadow?"` - Continue chat: `mycroft chat repl <session>` Notes - Use `mycroft config path` to find the config file location. - `book ask` and `book search` require embeddings and an `OPENAI_API_KEY`. - Chat commands require embeddings and an `OPENAI_API_KEY`. - Prefer `book search` and synthesize answers yourself before using `book ask`. - Summaries increase ingestion time and cost significantly; enable `--summary` only when needed. - Use `--batch` to run embeddings and summaries via the OpenAI Batch API at 50% cost; results may take up to 24 hours. When combined with `--summary`, summaries are batched first, then embeddings on resume. - After `--batch` ingestion, use `mycroft book ingest status <id>` to check progress and `mycroft book ingest resume <id>` to complete indexing. - If a non-batch ingest is interrupted, use `mycroft book ingest resume <id>` to continue from the last saved chunk. - If a batch fails, `resume` automatically re-submits it. - For scripted runs, avoid interactive flags like `--manual` or omit confirmations with `--force`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pingagi/pingagi-web (version 0.1.0)

name: web description: Browse and extract content from webpages using the local browser service. version: 0.1.0 author: PingAGI metadata: { "openclaw": { "emoji": "🌐" } } --- # Web Browser Skill Use this skill when the agent needs to: - open a webpage - extract webpage text - browse websites - retrieve webpage content The agent can call the local browser service: Example command (replace URL with the target webpage): ``` curl -s -X POST http://127.0.0.1:3088/browse \ -H "Content-Type: application/json" \ -d '{"url":"https://example.com"}' ``` The response returns JSON containing: - page title - page text - partial HTML - optional screenshot (base64) The agent should extract useful information from the "text" field.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bladezhang/ddzaishot (version 1.0.0)

# SKILL.md - ddzaishot 斗地主AI助手 当你需要帮助用户玩斗地主或分析牌局时，使用此技能。 ## 功能 - 🎯 识别屏幕上的牌 - 📝 自动记牌 - 🧠 AI推荐出牌 - 🖱️ 辅助出牌（可选） ## 调用方式 ### 扫描屏幕识别牌局 ```bash cd ddzaishot python src/api.py scan ``` ### AI推荐出牌（需先设置牌） ```bash # 设置我的牌和地主 python src/api.py suggest --cards=3,4,5,6,7,8,9,10,11,12,13,14,15 --landlord=me # 演示模式（随机发牌测试） python src/api.py demo ``` ### 查看当前状态 ```bash python src/api.py status ``` ## 牌值对应 - 3-10: 数字牌 - 11: J - 12: Q - 13: K - 14: A - 15: 2 - 16: 小王 - 17: 大王 ## 交互式模式 ```bash python src/main.py ``` 然后输入命令： - `s` 扫描屏幕 - `p` 推荐出牌 - `m` 手动输入牌 - `l` 设置地主 - `d` 演示模式 ## 注意事项 1. 屏幕识别需要先制作卡牌模板放到 `templates/` 目录 2. 鼠标控制需要先运行 `c` 命令校准 3. 建议先在演示模式下测试AI逻辑 ## 依赖 ```bash pip install opencv-python numpy pyautogui pillow mss keyboard ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: russellfei/file-manager (version 1.2.0)

--- name: file-manager description: OpenClaw自动化文件管理助手，用于批量文件操作、智能分类、重复文件清理、文件重命名、目录同步等任务。当用户需要整理文件、批量重命名、清理重复文件、同步目录或自动化文件工作流时使用此技能。 --- # File Manager - OpenClaw 自动化文件管理 ## 核心功能 ### 1. 智能文件分类 (`organize`) 按文件类型、日期、大小或自定义规则自动分类文件。 ```bash # 按文件类型分类 python scripts/organize.py <source_dir> --by-type # 按日期分类 (年/月/日) python scripts/organize.py <source_dir> --by-date --date-format year/month # 按文件大小分类 (尚未实现) # python scripts/organize.py <source_dir> --by-size --size-ranges "10MB,100MB,1GB" ``` ### 2. 批量重命名 (`batch_rename`) 支持正则表达式、序列号、日期等模式的重命名。 ```bash # 添加前缀/后缀 python scripts/batch_rename.py <pattern> --prefix "IMG_" --suffix "_2024" # 使用正则替换 python scripts/batch_rename.py "*.jpg" --replace "IMG_(\d+)" "Photo_\1" # 序列号重命名 python scripts/batch_rename.py "*.jpg" --sequence --padding 4 ``` ### 3. 重复文件清理 (`deduplicate`) 基于内容哈希检测并处理重复文件。 ```bash # 扫描并列出重复文件 python scripts/deduplicate.py <directory> --scan-only # 删除重复文件（保留最旧/最新） python scripts/deduplicate.py <directory> --keep oldest --action delete # 移动重复文件到隔离目录 python scripts/deduplicate.py <directory> --action move --to <quarantine_dir> ``` ### 4. 目录同步 (`sync`) 双向或单向目录同步，支持排除模式和增量同步。 ```bash # 单向同步 (源 → 目标) python scripts/sync.py <source> <target> --mirror # 双向同步 (尚未实现) python scripts/sync.py <dir1> <dir2> --bidirectional # 排除特定文件 python scripts/sync.py <source> <target> --exclude "*.tmp,*.log,.git" ``` ## 使用模式 ### 常见场景 **场景1: 整理下载文件夹** ```python # 自动分类下载的文件 python scripts/organize.py ~/Downloads --by-type --move ``` **场景2: 清理重复照片** ```python # 扫描重复照片 python scripts/deduplicate.py ~/Pictures --scan-only ``` **场景3: 批量整理项目文件** ```python # 按日期整理项目文件 python scripts/organize.py ./projects --by-date --date-format year/month ``` **场景4: 自动备份工作目录** ```python # 同步到备份目录，排除临时文件 python scripts/sync.py ~/Work ~/Backups/Work --exclude "node_modules,.git,*.tmp" ``` ## 工作流 ### 文件整理工作流 1. 分析目录结构和文件分布 2. 选择分类策略 (类型/日期/大小/自定义) 3. 执行整理 (dry-run 预览 → 确认 → 执行) 4. 验证结果 ### 清理工作流 1. 扫描重复/过期/大文件 2. 生成报告并预览 3. 用户确认或自动处理 4. 移动到回收站/隔离区/直接删除 ### 同步工作流 1. 分析源和目标差异 2. 预览待同步的文件列表 3. 确认后执行同步 4. 显示同步统计 ## 安全原则 - **预览优先**: 所有修改操作默认执行 dry-run 预览，需加 --execute 才执行 - **操作确认**: 执行前需要用户输入 yes 确认 - **符号链接安全**: 遍历目录时跳过符号链接，避免无限递归 - **冲突保护**: 目标文件已存在时自动重命名或跳过，不会覆盖 ## ⚙️ 依赖安装与环境初始化 ### 环境要求 - Python 3.8+ - 无外部依赖，仅使用 Python 标准库 --- ## 脚本参数说明 直接查看脚本帮助获取详细参数: ```bash python scripts/<script>.py --help ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: zhangpengle/military-bidding-email (version 0.2.8)

--- name: milb-email description: 军工采购（军采）商机专用推报工具。汇总三大军采平台数据，生成 Excel 并通过 SMTP 发送邮件报告。与政府采购（政采）工具无关，仅处理军队采购渠道。当用户说"milb-email"、"军工商机邮件"、"推送军工商机"、"军工商机通报"时触发。注意：这不是通用邮件客户端，仅用于执行 milb 业务逻辑。 metadata: {"openclaw":{"emoji":"📧","requires":{"bins":["milb-email","milb-fetcher"]},"install":"pip install -e {baseDir}"}} --- # Milb Email 自动抓取商机并发送邮件报告。 ## 环境变量要求 该技能必须在 `.env` 中配置以下核心参数才能激活： - `EMAIL_TO`, `EMAIL_CC`, `EMAIL_FROM`: 收发件地址 - `EMAIL_SMTP_HOST`, `EMAIL_SMTP_PORT`: SMTP 服务器信息 - `EMAIL_SMTP_USER`, `EMAIL_SMTP_PASSWORD`: 认证信息 - `EMAIL_SUBJECT_PREFIX`, `EMAIL_BODY_INTRO`: 邮件模板配置 - `EMAIL_RECIPIENT_NAME`, `EMAIL_SENDER_NAME`: 称呼和签名 ## 快速使用 - `/milb-email` → 发送昨日报告（默认，解决军队采购网白天更新的问题） - `/milb-email --help` → 显示帮助信息 - `/milb-email --today` → 发送今日报告（获取各渠道最新数据） - `/milb-email --date 2026-03-23` → 发送指定日期报告 - `/milb-email --keywords "模型,仿真"` → 使用自定义关键词筛选 - `/milb-email --to [REDACTED_SECRET]` → 测试发送至指定收件人 ## 参数说明 | 参数 | 说明 | 默认值 | |------|------|--------| | 无参数 | 默认昨日 | 启用 | | `--today` | 今日（获取各渠道最新数据） | - | | `--date YYYY-MM-DD` | 指定日期 | - | | `--keywords WORDS` | 关键词，逗号分隔 | 配置中的默认关键词 | | `--to ADDRESS` | 测试发送至指定收件人 | .env 中的配置 | ## 数据源 - 全军武器装备采购信息网 - 军队采购网 - 国防科大采购信息网 ## 触发词 发送邮件、推送报告、邮件通知、商机通报 ## 配置文件 配置文件位于 `milb_email/.env`（独立配置），可配置以下参数： | 环境变量 | 用途 | |----------|------| | `EMAIL_TO` | 收件人，逗号分隔 | | `EMAIL_CC` | 抄送人，逗号分隔 | | `EMAIL_FROM` | 发件人 | | `EMAIL_RECIPIENT_NAME` | 收件人称呼 | | `EMAIL_SENDER_NAME` | 发件人签名 | | `EMAIL_SUBJECT_PREFIX` | 邮件主题前缀 | | `EMAIL_BODY_INTRO` | 邮件正文开头 | | `EMAIL_SMTP_HOST` | SMTP 服务器 | | `EMAIL_SMTP_PORT` | SMTP 端口 | | `EMAIL_SMTP_USER` | SMTP 用户名 | | `EMAIL_SMTP_PASSWORD` | SMTP 密码 | 创建配置文件可复制 `milb_email/.env.example` 为 `milb_email/.env` 后修改。 ## 技术说明 - 数据来源：全军武器装备采购信息网、军队采购网、国防科大采购信息网（均为军采渠道，非政采） - 使用 SMTP 直接发送邮件（配置 EMAIL_SMTP_* 环境变量） - 使用文件锁防止并发执行


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: tanis90/slides-to-markdown (version 1.0.0)

--- name: slides-to-markdown description: "Document to Markdown converter - convert DOCX, PPTX, Excel files to Markdown. Use when extracting content from Word documents, PowerPoint presentations, or Excel spreadsheets." homepage: https://mineru.net metadata: {"openclaw":{"emoji":"📑","requires":{"bins":["mineru-open-api"]},"install":[{"id":"npm","kind":"node","package":"mineru-open-api","bins":["mineru-open-api"],"label":"Install via npm"},{"id":"uv","kind":"uv","package":"mineru-open-api","bins":["mineru-open-api"],"label":"Install via uv"},{"id":"go","kind":"go","package":"github.com/opendatalab/MinerU-Ecosystem/cli/mineru-open-api","bins":["mineru-open-api"],"label":"Install via go install","os":["darwin","linux"]}]}} --- # Slides to Markdown - Presentation Parser Convert Word, PowerPoint, and Excel files to Markdown using MinerU Open API. No API key required. ## Quick Start ```bash # Slides to Markdown - Presentation Parser mineru-open-api flash-extract report.docx # Slides to Markdown - Presentation Parser mineru-open-api flash-extract slides.pptx # Slides to Markdown - Presentation Parser mineru-open-api flash-extract data.xlsx # Slides to Markdown - Presentation Parser mineru-open-api flash-extract https://example.com/report.docx # Slides to Markdown - Presentation Parser mineru-open-api flash-extract report.docx -o ./output/ ``` ## Language Rule You MUST reply to the user in the SAME language they use. This is non-negotiable. ## Capabilities - Converts DOCX, PPTX, XLS, XLSX to Markdown - Supports both local files and URLs directly - Preserves text, tables, and document structure - No API key, no signup, no authentication - Max 10MB / 20 pages per document ## When to Use - User asks to "read", "extract", or "convert" a Word/PowerPoint/Excel file - User shares a .docx, .pptx, or .xlsx and asks for its content - User wants to summarize or analyze an office document - User needs document content in Markdown format ## CLI Reference Run `mineru-open-api flash-extract --help` for all available options. ## Data Privacy - `flash-extract` uploads the document to MinerU's cloud API for processing and returns the result. No account or API key is required. - Documents are processed in real-time and are not stored after extraction. - For details, see https://mineru.net ## Notes - Output is Markdown only; embedded images may be replaced with placeholders - For larger files (up to 200MB/600 pages) or precision extraction, use `mineru-open-api extract` (requires auth via `mineru-open-api auth`) - If the CLI cannot be installed via npm/uv/go, download it from https://mineru.net/ecosystem?tab=cli


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zwybirth/feishu-bitable-plus (version 1.0.0-beta)

# feishu-bitable-plus 企业级飞书多维表格智能操作技能 - 自然语言驱动，纯本地安全部署 ## 描述 用自然语言操作飞书多维表格，告别复杂API。 支持批量处理、数据同步、质量分析，纯本地部署保障数据安全。 ## 安装 ```bash npx clawhub@latest install feishu-bitable-plus ``` ## 使用 ```bash # 配置飞书凭证 fbt config # 自然语言查询 fbt query "列出客户表的所有记录" # 交互模式 fbt interactive ``` ## 功能 - 自然语言操作表格 - 完整CRUD（增删改查） - 批量导入导出 - 跨表数据同步 - 数据质量分析 ## 权限 - bitable:app - bitable:record - bitable:table ## 作者 wenyuan ## 许可证 MIT


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: igorganapolsky/subway-whatsapp-ordering (version 1.0.1)

--- id: subway-whatsapp-ordering name: Subway-Style WhatsApp Ordering & Upsell Agent version: 1.0.0 description: A ThumbGate-hardened WhatsApp ordering agent for QSRs, featuring smart upsells and inventory awareness. author: Igor Ganapolsky (Ex-Subway Mobile App Team Lead) tags: [restaurant, qsr, whatsapp, ordering, thumbgate] --- # Subway-Style WhatsApp Ordering Agent This skill transforms any WhatsApp number into a high-performance, ThumbGate-protected ordering kiosk. Built with the rigor of corporate QSR standards, it handles natural language ordering, identifies upsell opportunities (e.g., "Make it a meal?"), and respects inventory limits synced from Google Sheets. ## Key Features - **Natural Language Parsing:** Understands "Gimme a footlong BMT with extra cheese" without needing rigid menus. - **Smart Upsell Logic:** Proactively suggests cookies, drinks, or double protein based on basket content. - **ThumbGate Protection:** Prevents expensive mistakes like double-charging or ignoring allergen requests. - **Inventory Sync:** Real-time updates from Google Sheets ensure you never sell what you don't have. ## Instructions 1. **Greeting:** Start every interaction with a friendly, efficient QSR greeting. 2. **Order Capture:** Identify items, sizes, and modifications. 3. **Upsell:** If an order doesn't include a drink or cookie, suggest one. 4. **Validation:** Use ThumbGate rules to verify the order is complete and feasible. 5. **Confirmation:** Provide a summarized bill and estimated pickup time. 6. **Logging:** Record all transactions to the `orders` sheet in the connected Google Sheet. ## ThumbGate Prevention Rules 1. **No Phantom Items:** Do not confirm an order for an item marked as "OUT" in the inventory sheet. 2. **Allergen Alert:** If a user mentions an allergy, MUST flag it in the order notes and double-confirm safety. 3. **Price Integrity:** Never promise a price that deviates from the calculated subtotal + tax. 4. **Mod Limit:** Cap modifications at 5 per item to prevent "garbage" orders. 5. **Session Lock:** If no response for 5 minutes during checkout, prompt once then close the session. ## 🚀 Upgrade to Premium "Revenue Machine" Get the enterprise-grade bundle including: - 12+ Advanced ThumbGate Rules (hallucination-proof) - Google Sheets Inventory Bridge template - The "Cookie Upsell" logic (proven to increase AOV by 15%) - Priority Support & Setup Guide **Buy Now on Gumroad ($97):** https://iganapolsky.gumroad.com/l/gvpllr


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: luongkim20222022-crypto/auto-marketer-skill (version 1.0.0)

# 自动化营销推广师 ## 技能概述 专为一入公司总裁设计的自动化营销工具。自动监测社交媒体/论坛中与欧盟合规、VAT、选品、物流相关的问题，调用您的三个核心技能生成专业回复，并软性引流至您的ClawHub Skill链接。全自动运行，无需人工干预。 ## 角色定位 你是一位顶级的数字营销专家，精通社交媒体监测、内容生成、自动回复和引流转化。你的使命是让AI推广AI，实现24/7自动化获客。 ## 核心能力 ### 1. 多渠道监测（模拟/真实API） - **监测平台**：Twitter、Reddit、LinkedIn、微信公众平台（需API）、知无不言论坛（RSS/爬虫） - **监测关键词**： - 合规类："WEEE", "包装法", "CE认证", "德国税务", "欧盟VAT" - 物流类："DDP", "清关", "关税", "海运时效", "德国FBA" - 选品类："什么好卖", "选品", "竞品分析", "蓝海" - 泛需求："跨境电商", "德国站", "欧洲站" - **频率**：每15分钟扫描一次 ### 2. 问题智能匹配 - 将抓取到的文本进行意图分类： - `compliance` → 调用 `eu-compliance-advisor` - `market` → 调用 `eu-market-analyst` - `logistics` → 调用 `logistics-optimizer` - 若涉及多个类别，依次调用多个技能并整合回复。 ### 3. 专业回复生成 - 根据分类调用对应技能，获取结构化回复（合规分析/选品建议/物流方案） - 在回复末尾附加软性引流文本： ### 4. 自动发布与回复 - **Twitter**：@提及提问者，回复内容 - **Reddit**：回复帖子或评论 - **LinkedIn**：评论或私信（需授权） - **微信**：通过企业微信API或个人号机器人（需配置） ### 5. 数据追踪与报告 - 记录每次回复的时间、平台、问题摘要 - 每周生成引流报告：总回复数、点击预估、新增用户数 ## 调用规则 | 触发条件 | 动作 | |---------|------| | 监测到合规类问题 | 调用 `eu-compliance-advisor` → 生成回复 → 自动发布 | | 监测到市场类问题 | 调用 `eu-market-analyst` → 生成回复 → 自动发布 | | 监测到物流类问题 | 调用 `logistics-optimizer` → 生成回复 → 自动发布 | | 监测到混合问题 | 依次调用多个技能 → 整合回复 → 自动发布 | ## 使用示例 ### 示例1：Twitter自动回复 **用户推文**： > "第一次做德国站，电子产品要办WEEE吗？好怕被封店。" **营销智能体动作**： 1. 意图识别：`compliance` 2. 调用 `eu-compliance-advisor`，参数 `productName="电子产品", country="德国"` 3. 获得回复（合规要求摘要） 4. 附加引流链接 5. 发布回复： ### 示例2：Reddit选品求助 **帖子**： > "无线充电宝在德国还好做吗？求大佬分析。" **营销智能体动作**： 1. 意图识别：`market` + `logistics`（选品+物流） 2. 依次调用 `eu-market-analyst` 和 `logistics-optimizer` 3. 生成综合回复（市场容量+利润测算+物流建议） 4. 附加引流链接 5. 回复帖子。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: amenizm/pacta (version 1.0.2)

--- name: pacta description: "DEPRECATED: This skill has been permanently deactivated. The V1 Pacta smart contracts are undergoing regulatory review and all frontend interfaces have been disabled. Do not use this tool. No further support will be provided." version: 1.0.2 metadata: openclaw: requires: bins: - python3 --- # DEPRECATED: Pacta Escrow Skill **CRITICAL WARNING: This skill has been deliberately disabled.** The V1 Pacta smart contracts on Base are undergoing a legal and regulatory review regarding the 1% protocol fee and Money Services Business (MSB) classification. To ensure the safety of our users and compliance with potential US regulations, all frontend interfaces and CLI tools for interacting with the V1 contracts have been permanently deactivated. Do not attempt to manually interact with the V1 contracts. Any funds locked in V1 are currently frozen by the interface. **This skill will no longer function.** ```bash # If you run this skill, it will immediately exit with a fatal error: openclaw skills run pacta any_command > FATAL ERROR: Pacta V1 is deprecated. ```


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