OpenClaw/clawhub-security-signals huggingface dataset:
Skill: nexscope/product-page-seo (version 1.0.0)

--- name: product-page-seo description: "Optimize e-commerce product pages for search engine visibility. On-page SEO, structured data, page speed, mobile optimization, and content strategy for Google, Bing, and platform-specific search." metadata: nexscope: emoji: "🔎" category: ecommerce --- # Product Page SEO 🔎 Optimize e-commerce product pages for search engine visibility. On-page SEO, structured data, page speed, mobile optimization, and content strategy for Google, Bing, and platform-specific search. **Supported platforms:** Amazon, Shopify, WooCommerce, Walmart, TikTok Shop, Etsy, eBay, BigCommerce. Built by [Nexscope](https://www.nexscope.ai/) — your AI assistant for smarter e-commerce decisions. ## Install ```bash npx skills add nexscope-ai/eCommerce-Skills --skill product-page-seo -g ``` ## Usage ``` Audit the SEO of my Shopify product page for a yoga mat. URL: [paste URL]. I'm getting zero organic traffic from Google. ``` ## Capabilities - Product page SEO audit framework (title tag, meta description, H1, URL) - Structured data markup (Product schema, Review schema, FAQ schema) - Image optimization (alt text, file size, WebP conversion) - Page speed optimization recommendations - Mobile usability optimization - Internal linking strategy for product pages - Content enrichment (FAQs, buying guides, comparison tables) ## How This Skill Works **Step 1:** Collect information from the user's message — product, platform, current situation, and goals. **Step 2:** Ask one follow-up with all remaining questions using multiple-choice format. Allow shorthand answers (e.g., "1b 2c 3a"). **Step 3:** Research and analyze using the frameworks and methodology below. **Step 4:** Deliver structured, actionable output with specific recommendations, not vague advice. ## Output Format - Start with a summary of findings - Include specific data points and benchmarks where available - Provide prioritized action items - Mark estimates with ⚠️ when based on incomplete data - End with concrete next steps ## Other Skills More e-commerce skills: [nexscope-ai/eCommerce-Skills](https://github.com/nexscope-ai/eCommerce-Skills) Amazon-specific skills: [nexscope-ai/Amazon-Skills](https://github.com/nexscope-ai/Amazon-Skills) Built by [Nexscope](https://www.nexscope.ai/) — your AI assistant for smarter e-commerce decisions.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: canonxu/my-skill-clawhub-skill (version 1.0.0)

# my_skill_clawhub_skill ## Purpose A wrapper for `clawhub` to standardize the publishing and installation workflow for agent skills. ## Commands ### 1. Publish (Upload) Standardize publishing with mandatory versions and changelogs. ```bash bash scripts/clawhub_helper.sh publish <path> <version> "<changelog>" ``` ### 2. Install (Download/Search) Search and install with optional version specification. ```bash bash scripts/clawhub_helper.sh install <slug> [version] ``` ## Features - **Auto-versioning**: Ensures every publish has a version. - **Verification**: Searches for skills before attempting to install. - **Structure**: Enforces standard ClawHub formatting.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: anlinxi/chinese-holidays (version 1.0.0)

--- name: chinese-holidays description: > Query Chinese statutory holidays, check if a date is a working day/holiday, and get holiday schedules. Use when the user asks about Chinese holidays, working days, statutory holidays, or needs to know if a specific date is a holiday in China. Supports queries like "Is tomorrow a holiday?", "When is Spring Festival?", "Is May 1st a working day?". --- # Chinese Holidays Query Chinese statutory holidays and working day status. ## Quick Start ```bash python scripts/holidays.py today python scripts/holidays.py check 2025-01-01 python scripts/holidays.py list 2025 ``` ## Commands ### `today` — Check today's status Check if today is a working day, holiday, or weekend. ```bash python scripts/holidays.py today ``` Output: ``` 2025-01-01 (Wednesday) Status: HOLIDAY - New Year's Day (元旦) ``` ### `check <date>` — Check specific date Check if a specific date is a working day or holiday. ```bash python scripts/holidays.py check 2025-02-10 ``` Output: ``` 2025-02-10 (Monday) Status: HOLIDAY - Spring Festival (春节) ``` ### `list <year>` — List all holidays in a year List all statutory holidays for a given year. ```bash python scripts/holidays.py list 2025 ``` Output: ``` === 2025 Chinese Statutory Holidays === 1. New Year's Day (元旦) 2025-01-01 2. Spring Festival (春节) 2025-01-28 to 2025-02-04 (8 days) 3. Qingming Festival (清明节) 2025-04-04 to 2025-04-06 (3 days) 4. Labor Day (劳动节) 2025-05-01 to 2025-05-05 (5 days) 5. Dragon Boat Festival (端午节) 2025-05-31 to 2025-06-02 (3 days) 6. Mid-Autumn Festival (中秋节) 2025-10-06 (1 day, combined with National Day) 7. National Day (国庆节) 2025-10-01 to 2025-10-07 (7 days) ``` ### `next` — Find next holiday Find the next upcoming holiday. ```bash python scripts/holidays.py next ``` Output: ``` Next holiday: Spring Festival (春节) Date: 2025-01-28 to 2025-02-04 Days until: 15 days ``` ## Return Codes | Code | Meaning | |------|---------| | 0 | Working day | | 1 | Weekend | | 2 | Statutory holiday | | 3 | Adjusted working day (调休) | ## Data Source Holiday data is based on official announcements from the State Council of China (国务院办公厅). The script includes: - Statutory holiday dates - Adjusted working days (调休) - Holiday names in Chinese and English ## Notes - Adjusted working days (调休) are weekends that become working days due to holiday adjustments - Some holidays may change based on official announcements - data is updated annually - Supports dates from 2024 onwards


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

--- name: mactop description: | Retrieve real-time hardware metrics from Apple Silicon Macs using mactop's TOON format. Provides CPU, RAM, GPU, power, thermal, network, disk I/O, and Thunderbolt bus information. Use when the user wants system stats, hardware monitoring, or performance metrics on Apple Silicon Macs. --- # Mactop Skill Execute mactop in headless TOON mode and parse the output for hardware metrics. ## Prerequisites - **mactop installed**: `brew install mactop` - **PATH includes /usr/sbin**: Required for sysctl access ## Usage ### Get Full Metrics ```bash mactop --format toon --headless --count 1 ``` ### Parse Key Metrics **CPU Usage:** ```bash mactop --format toon --headless --count 1 | grep "^cpu_usage:" | awk '{print $2}' ``` **RAM (used/total GB):** ```bash mactop --format toon --headless --count 1 | grep -E "^ (Used|Total):" | awk '{printf "%.1f", $2/1073741824}' ``` **GPU Usage:** ```bash mactop --format toon --headless --count 1 | grep "^gpu_usage:" | awk '{print $2}' ``` **Power (total/CPU/GPU):** ```bash mactop --format toon --headless --count 1 | grep -E "^ (TotalPower|CPUPower|GPUPower):" | awk '{print $2}' ``` **Thermal State:** ```bash mactop --format toon --headless --count 1 | grep "^thermal_state:" | awk '{print $2}' ``` **Temperature:** ```bash mactop --format toon --headless --count 1 | grep "^ SocTemp:" | awk '{print $2}' ``` **Chip Info:** ```bash mactop --format toon --headless --count 1 | grep "^ Name:" | awk '{print $2}' ``` **Network I/O (bytes/sec):** ```bash mactop --format toon --headless --count 1 | grep -E "^( InBytesPerSec| OutBytesPerSec):" | awk '{print $2}' ``` **Thunderbolt Buses:** ```bash mactop --format toon --headless --count 1 | grep "^ Name:" | awk '{print $2}' ``` ## Options | Option | Description | |--------|-------------| | `--count N` | Number of samples (default: 1) | | `--interval MS` | Sample interval in milliseconds (default: 1000) | ## TOON Format ``` timestamp: "2026-01-25T20:00:00-07:00" soc_metrics: CPUPower: 0.15 GPUPower: 0.02 TotalPower: 8.5 SocTemp: 42.3 memory: Total: 25769803776 Used: 14852408320 Available: 10917395456 cpu_usage: 5.2 gpu_usage: 1.8 thermal_state: Normal system_info: Name: Apple M4 Pro CoreCount: 12 ``` ## Response Example Format metrics in a readable box: ``` ┌─ Apple M4 Pro ──────────────────────┐ │ CPU: 5.2% | RAM: 13.8/24.0 GB │ │ GPU: 1.8% | Power: 8.5W total │ │ Thermal: Normal | SoC: 42.3°C │ └─────────────────────────────────────┘ ``` ## Troubleshooting - **"sysctl not found"** → Add `/usr/sbin` to PATH - **No output** → Verify mactop is installed: `which mactop`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: williamwg2025/openclaw-search-pro (version 0.1.6)

--- name: openclaw-search-pro displayName: OpenClaw Search Pro - 搜索增强工具 version: 1.0.2 description: | OpenClaw 搜索增强工具 - 多引擎聚合搜索，获取最新信息。 支持免费搜索引擎（必应/搜狗/360）+ 可选 API（Tavily/百度/Google）。 内容提取、结果去重、智能排序。安全内网访问检查。 关键词：openclaw, search, web, research, productivity, multi-engine, tavily license: MIT-0 acceptLicenseTerms: true tags: - openclaw - search - web - research - productivity - multi-engine - tavily - content-extraction - bing - baidu --- # Search Pro - 搜索增强工具 强大的多引擎搜索工具，让搜索更准确、更全面。 --- ## ✨ 功能特性 - 🔍 **多引擎聚合** - 免费搜索引擎 + 可选 API - 📄 **内容提取** - URL 内容提取 - 📊 **结果去重** - 智能去重 + 排序 - 💾 **搜索历史** - 历史记录 + 收藏 - 📈 **质量分析** - 搜索质量评估 --- ## 🚀 安装 ```bash cd ~/.openclaw/workspace/skills # 技能已安装在：~/.openclaw/workspace/skills/search-pro chmod +x search-pro/scripts/*.py ``` --- ## 📖 使用 ### 多引擎搜索 ```bash python3 search-pro/scripts/multi-search.py "OpenClaw 技能开发" ``` ### 内容提取 ```bash python3 search-pro/scripts/extract.py --url https://example.com ``` --- ## 🛠️ 脚本 | 脚本 | 功能 | 网络访问 | 文件写入 | |------|------|---------|---------| | `multi-search.py` | 多引擎搜索 | ✅ 是 | ❌ 否 | | `free_search.py` | 免费搜索引擎 | ✅ 是 | ❌ 否 | | `baidu_search.py` | 百度搜索 | ✅ 是 | ❌ 否 | | `extract.py` | 内容提取 | ✅ 是 | ❌ 否 | **注意：** 搜索历史功能需要手动实现，当前版本不自动保存历史 --- ## 🔒 安全说明 ### 网络访问 ⚠️ **本技能需要联网访问外部服务：** - 免费搜索引擎（360、搜狗等） - 百度搜索引擎 - 可选：Tavily API（需配置 API Key） **网络权限：** - 出站 HTTPS 请求（443 端口） - 不监听任何端口 - 不运行服务器 ### 文件访问 **路径说明：** 所有文件存储在 `~/.openclaw/workspace/skills/search-pro/` - **读取：** - `config/search-config.json` - 搜索配置和 API 密钥（可选） - **写入：** - 当前版本不自动写入文件 - 搜索结果输出到命令行 - **extract.py 安全检查：** - ✅ 仅支持 http:// 和 https:// 协议 - ✅ 检查 IP 地址（10/8, 172.16/12, 192.168/16, 127/8） - ✅ DNS 解析后检查（防止域名指向内网） - ✅ 检查内网域名模式（.local, .internal, .intranet, .lan） - ✅ 阻止常见内网主机名（localhost, internal 等） ### 数据安全 - **不上传：** 不上传用户配置文件或敏感数据 - **搜索查询：** 会发送到配置的搜索引擎（百度、必应等），这是搜索功能的必要条件 - **API 密钥：** 存储在本地配置文件，不发送到除 API 提供商外的第三方 ### API 密钥（可选） **免费搜索：** 无需 API Key，直接使用 **可选 API 配置：** ```bash # 方法 1: 环境变量（推荐，更安全） export TAVILY_API_KEY="your-key" # 方法 2: 配置文件 # 编辑 config/search-config.json { "tavily": { "api_key": "your-key" } } ``` **注意：** API Key 存储在 `config/search-config.json`，没有单独的 api-keys.json 文件 **安全建议：** - 配置文件权限：`chmod 600 config/search-config.json` - 不要将 API Key 提交到 Git（添加到 .gitignore） - 使用环境变量更安全（不写入文件） --- **作者：** @williamwg2025 **版本：** 1.0.1 **许可证：** MIT-0

path: node_modules/axios/lib/env/data.js
content: export const VERSION = "1.13.6";

path: node_modules/call-bind-apply-helpers/actualApply.d.ts
content: export = Reflect.apply;

path: node_modules/parse5/dist/tree-adapters/interface.js
content: export {};


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: wangxiaofei860208-source/lobster-fork-mode (version 1.0.0)

--- name: lobster-fork-mode description: "Fork子Agent模式 — 子Agent继承父上下文。当需要子Agent了解父会话的关键上下文时自动激活。" metadata: {"openclaw":{"requires":["sessions_spawn","read","memory_search"]}} --- # Fork Mode — 子Agent上下文继承 参考 Claude Code 的 `forkSubagent.ts` 和 `runForkedAgent()`。 ## 问题 `sessions_spawn` 创建的子Agent是全新会话，没有父会话的上下文。这导致子Agent缺少关键信息。 ## 解决方案 在spawn子Agent时，手动注入父上下文。 ## Fork 模板 ### Step 1: 收集父上下文 ``` 需要注入的上下文： 1. 当前任务的目标和约束 2. 相关文件路径和关键代码片段 3. 已做出的决策和原因 4. 用户偏好（从MEMORY.md提取） 5. 项目结构概要 ``` ### Step 2: 构建Fork Prompt ``` 你是一个子Agent，从父会话 fork 出来。以下是你的继承上下文： ## 父会话上下文 {从Step 1收集的信息} ## 你的任务 {具体任务描述} ## 约束 - 工具白名单：{从Agent定义读取} - 不要修改父会话的文件（除非明确要求） - 完成后返回：{期望的输出格式} ``` ### Step 3: Spawn ``` sessions_spawn: runtime: "subagent" mode: "run" task: "{Fork Prompt}" streamTo: "parent" ``` ## 上下文大小控制 | 上下文类型 | 最大长度 | 截断策略 | |-----------|---------|---------| | 任务目标 | 500字 | 保留核心需求 | | 文件路径 | 10个文件 | 保留最相关的 | | 代码片段 | 2000字 | 保留签名+关键逻辑 | | 决策记录 | 5条 | 保留最新的 | | 用户偏好 | 3条 | 保留最相关的 | ## 缓存共享（模拟Claude Code的CacheSafeParams） OpenClaw没有prompt cache共享机制，但可以通过以下方式减少重复： 1. 子Agent使用相同模型（model: zai/glm-5.1） 2. system prompt结构一致 3. 避免在task中重复注入完整的SKILL.md内容 ## 适用场景 | 场景 | Fork模式 | 普通spawn | |------|---------|----------| | 需要了解项目背景 | ✅ | ❌ | | 需要知道已做决策 | ✅ | ❌ | | 纯机械任务（格式化、搜索） | ❌ | ✅ | | 需要用户偏好 | ✅ | ❌ | | 独立的新项目 | ❌ | ✅ |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: huangbaixun/one-mail (version 1.3.0)

--- name: one-mail description: 统一邮箱管理 CLI，支持 Gmail、Outlook、网易邮箱（163.com、126.com）。适用于：(1) 收取/发送邮件，(2) 跨账户搜索邮件，(3) 管理多个邮箱账户，(4) 查看邮件统计。当用户提到邮件、邮箱、email、发邮件、收邮件、查邮件时触发。 --- # one-mail 统一管理多个邮箱的 CLI 工具。配置存储在 `~/.onemail/`。 ## 初始化 首次使用运行 setup 添加账户： ```bash bash scripts/setup.sh ``` ## 收取邮件 ```bash bash scripts/fetch.sh # 所有账户 bash scripts/fetch.sh --unread # 仅未读 bash scripts/fetch.sh --account gmail # 指定账户 bash scripts/fetch.sh --query "AI agent" # 搜索 bash scripts/fetch.sh --limit 10 # 限制数量 ``` ## 阅读邮件 ```bash bash scripts/read.sh --id <message_id> --account <name> bash scripts/read.sh --account outlook --latest bash scripts/read.sh --account gmail --query "MacBook" bash scripts/read.sh --json # JSON 输出 ``` ## 发送邮件 ```bash bash scripts/send.sh \ --to "[REDACTED_SECRET]" \ --subject "Hello" \ --body "Email content" # 指定账户 + 附件 bash scripts/send.sh \ --account outlook \ --to "[REDACTED_SECRET]" \ --subject "Report" \ --body "See attachment" \ --attach "/path/to/file.pdf" ``` 注意：Outlook 附件限制 3MB。 ## 账户管理 ```bash bash scripts/accounts.sh list # 列出账户 bash scripts/accounts.sh add # 添加账户 bash scripts/accounts.sh remove <account_id> # 删除账户 bash scripts/accounts.sh set-default <id> # 设置默认 ``` ## 统计 ```bash bash scripts/stats.sh ``` ## 提供商要求 | 提供商 | 认证方式 | 前置条件 | |--------|----------|----------| | Gmail | OAuth 2.0 | 需要 `gog` CLI | | Outlook | OAuth 2.0 (Graph API) | 需要 Mail.ReadWrite + Mail.Send 权限 | | 网易 163 | IMAP/SMTP | 需要开启 IMAP 并使用应用密码 | | 网易 126 | IMAP/SMTP | 需要开启 IMAP 并使用应用密码 | ## 依赖 必需：`curl`、`jq`、`python3`。可选：`gog`（Gmail OAuth）。 ## 故障排除 遇到认证或连接问题时，参考 [troubleshooting.md](references/troubleshooting.md)。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: pupujanet-eng/mermaid-diagram (version 1.0.0)

--- name: mermaid-diagram description: Generate Mermaid diagrams for product managers and developers. Use when: (1) creating flowcharts, system architecture diagrams, sequence diagrams, or mind maps, (2) converting text descriptions or PRDs into visual diagrams, (3) drawing user journey maps, state machines, or ER diagrams, (4) any request that mentions "画图", "流程图", "架构图", "时序图", "脑图", "mermaid". Output valid Mermaid code blocks. --- # Mermaid Diagram Generator Generate valid Mermaid diagram code from text descriptions. ## Diagram Type Selection | 需求 | 推荐类型 | Mermaid 关键字 | |------|----------|----------------| | 业务流程 / 逻辑流程 | Flowchart | `flowchart TD` | | 系统交互 / API 时序 | Sequence | `sequenceDiagram` | | 产品架构 / 系统结构 | Flowchart / C4 | `flowchart LR` | | 状态机 / 用户状态 | State | `stateDiagram-v2` | | 脑图 / 功能树 | Mindmap | `mindmap` | | 数据库结构 | ER | `erDiagram` | | 项目时间线 | Timeline | `timeline` | | 用户旅程 | Journey | `journey` | ## Output Rules 1. Always wrap output in ` ```mermaid ` code blocks 2. Use Chinese labels when the user writes in Chinese 3. Add comments (`%%`) for complex diagrams to explain sections 4. Keep node names short (≤10 chars) to avoid layout issues 5. Validate syntax mentally before outputting — common mistakes: - Missing quotes around labels with spaces/Chinese - Wrong arrow syntax (`-->` vs `---` vs `->>`) - Unclosed brackets ## Quick Syntax Reference ``` flowchart TD A[开始] --> B{判断条件} B -- 是 --> C[执行操作] B -- 否 --> D[结束] C --> D ``` ``` sequenceDiagram 用户->>服务端: 发起请求 服务端->>数据库: 查询数据 数据库-->>服务端: 返回结果 服务端-->>用户: 响应 ``` ``` mindmap root((产品名)) 功能A 子功能1 子功能2 功能B ``` ## Reference Files - **references/diagram-patterns.md** — 产品经理常用图模式（带完整示例代码） Read when: user asks for a specific diagram type or needs a complex multi-node diagram.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xiaochunz030-spec/general-software (version 1.0.0)

--- name: general-software description: 通用软件自动化技能，涵盖窗口管理、GUI自动化、批量文件处理、软件安装配置、系统设置、日志收集分析、截图取证等通用场景。触发场景：自动化点击、窗口操作、批量重命名、文件格式转换、软件批量安装、系统配置、日志分析、屏幕截图、GUI测试。 --- # General Software - 通用软件自动化 ## 核心能力 ### 窗口 & GUI 自动化 - 窗口查找、激活、最小化/最大化/关闭 - 鼠标点击、拖拽、滚轮操作 - 键盘输入、快捷键执行 - 表单自动填充 - 支持：Windows (PyAutoGUI/UIAutomation)、跨平台 (PyGuyy) ### 批量文件处理 - 批量重命名（支持正则、序号、日期插入） - 格式转换（图片/音频/视频/文档） - 文件批量压缩/解压 - 目录结构复制/同步 - 文件内容批量搜索替换 ### 软件安装 & 配置 - 静默安装 / 卸载（MSI / EXE） - 配置文件修改（INI / JSON / YAML / 注册表） - 环境变量管理 - Windows 服务管理（启动/停止/重启） ### 日志收集 & 分析 - 多目录日志批量收集 - 按关键字 / 时间范围过滤 - 异常模式匹配（ERROR / Exception / Fatal） - 日志汇总报告生成 ### 系统 & 截图 - 系统信息采集（硬件/软件/网络） - 屏幕截图 / 区域截图 - 多屏幕支持 - 截图标注和高亮 ### 关键脚本 - `scripts/gui_auto.py` - PyAutoGUI Windows GUI 自动化 - `scripts/uiauto.py` - Windows UIAutomation 高级操作 - `scripts/batch_rename.py` - 批量文件重命名 - `scripts/file_convert.py` - 格式批量转换 - `scripts/soft_install.py` - 软件静默安装 - `scripts/log_collector.py` - 日志收集分析 - `scripts/screenshot.py` - 屏幕截图工具 ### 参考资源 - `references/pyautogui-cheatsheet.md` - PyAutoGUI 速查表 - `references/windows-automation.md` - Windows 自动化进阶 ## 工作流程 1. **描述任务**：用户描述需要自动化的软件操作 2. **判断类型**：GUI 自动化 / 文件处理 / 系统配置 / 日志分析 3. **执行脚本**：调用对应脚本，必要时先录制演示 4. **结果确认**：截图或输出文件确认效果 ## 注意事项 - GUI 自动化前先了解目标软件的界面结构 - 批量文件操作先在测试目录验证 - 静默安装需要管理员权限 - 日志分析优先使用正则匹配关键模式 - 截图工具支持全屏/区域/窗口三种模式


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: highlander89/remote-ssh-bridge (version 0.1.3)

--- name: remote-ssh-bridge description: Standard SSH command templates for a remote operator machine (bird reads, Puppeteer runs, inbox-style messaging). --- # remote-ssh-bridge Author: billy-ops-agent ## Purpose Standardize shell command patterns for tasks that must run on REMOTE: - bird reads - puppeteer runs - inbox messaging ## What this skill includes - `scripts/check-sapconet.sh`: health/check template for REMOTE command access. - `scripts/msg-sapconet.sh`: message send template for REMOTE workflows. ## Safety rules - Only uses SSH to REMOTE host. - No external network calls are performed beyond SSH transport. - Keep credentials and tokens in environment variables, not inline in scripts. - Review remote command placeholders before running. ## Usage Set target and run: ```bash export REMOTE_TARGET="user@<your-remote-host>" bash scripts/check-sapconet.sh bash scripts/msg-sapconet.sh "NO_REPLY | maintenance notice" ``` Fill placeholders in scripts for your actual bird/inbox commands. ## Quickstart 1) Install - Install from ClawHub (public skill). 2) Use - Invoke the skill by name inside OpenClaw. ## Safety - No secrets are embedded in this skill. - Any remote commands require you to configure your own SSH target.

path: scripts/check-sapconet.sh
content: #!/usr/bin/env bash
set -euo pipefail

REMOTE_TARGET="${REMOTE_TARGET:-neill@<YOUR_REMOTE_HOST>}"

# Connectivity + host identity check
ssh "${REMOTE_TARGET}" 'echo "connected: $(hostname)" && date -Iseconds'

# Placeholder: bird read command on REMOTE
# Example: ssh "${REMOTE_TARGET}" 'birdc show protocols'
ssh "${REMOTE_TARGET}" 'echo "TODO: replace with bird read command"'

# Placeholder: puppeteer environment check on REMOTE
ssh "${REMOTE_TARGET}" 'command -v node >/dev/null && command -v chromium >/dev/null && echo "puppeteer prereqs present" || echo "missing node/chromium"'


path: scripts/msg-sapconet.sh
content: #!/usr/bin/env bash
set -euo pipefail

if [[ "$#" -lt 1 ]]; then
  echo "Usage: $0 '<message>'"
  exit 2
fi

REMOTE_TARGET="${REMOTE_TARGET:-neill@<YOUR_REMOTE_HOST>}"
MESSAGE="$1"

# Placeholder: replace with actual REMOTE inbox command
# Keep NO_REPLY discipline for automated messages.
ssh "${REMOTE_TARGET}" "echo 'TODO: send inbox message: ${MESSAGE}'"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: omactiengartelle/kpop-idol-generator (version 1.0.0)

--- name: kpop-idol-generator description: Generate k-pop idol style portraits and kpop photocard aesthetic images — perfect for kpop fan edits, korean beauty looks, idol photoshoot vibes, korean fashion portraits, stan twitter profile pics, kpop bias card art, and hallyu-inspired glamour photography. Turn any description into a polished k-pop idol debut photo via the Neta AI image generation API (free trial at neta.art/open). tools: Bash --- # K-Pop Idol Generator Generate k-pop idol style portraits and kpop photocard aesthetic images — perfect for kpop fan edits, korean beauty looks, idol photoshoot vibes, korean fashion portraits, stan twitter profile pics, kpop bias card art, and hallyu-inspired glamour photography. Turn any description into a polished k-pop idol debut photo. ## Token Requires a Neta API token (free trial at <https://www.neta.art/open/>). Pass it via the `--token` flag. ```bash node <script> "your prompt" --token YOUR_TOKEN ``` ## When to use Use when someone asks to generate or create kpop idol style portrait images. ## Quick start ```bash node kpopidolgenerator.js "your description here" --token YOUR_TOKEN ``` ## Options - `--size` — `portrait`, `landscape`, `square`, `tall` (default: `portrait`) - `--ref` — reference image UUID for style inheritance ## Install ```bash npx skills add omactiengartelle/kpop-idol-generator ```


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