OpenClaw/clawhub-security-signals huggingface dataset:
Skill: litiao1224/gog-litiao (version 1.0.0)

--- name: gog-litiao description: Google Workspace CLI for Gmail, Calendar, Drive, Contacts, Sheets, and Docs. homepage: https://gogcli.sh metadata: {"clawdbot":{"emoji":"🎮","requires":{"bins":["gog"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/gogcli","bins":["gog"],"label":"Install gog (brew)"}]}} --- # gog Use `gog` for Gmail/Calendar/Drive/Contacts/Sheets/Docs. Requires OAuth setup. Setup (once) - `gog auth credentials /path/to/client_secret.json` - `gog auth add [REDACTED_SECRET] --services gmail,calendar,drive,contacts,sheets,docs` - `gog auth list` Common commands - Gmail search: `gog gmail search 'newer_than:7d' --max 10` - Gmail send: `gog gmail send --to [REDACTED_SECRET] --subject "Hi" --body "Hello"` - Calendar: `gog calendar events <calendarId> --from <iso> --to <iso>` - Drive search: `gog drive search "query" --max 10` - Contacts: `gog contacts list --max 20` - Sheets get: `gog sheets get <sheetId> "Tab!A1:D10" --json` - Sheets update: `gog sheets update <sheetId> "Tab!A1:B2" --values-json '[["A","B"],["1","2"]]' --input USER_ENTERED` - Sheets append: `gog sheets append <sheetId> "Tab!A:C" --values-json '[["x","y","z"]]' --insert INSERT_ROWS` - Sheets clear: `gog sheets clear <sheetId> "Tab!A2:Z"` - Sheets metadata: `gog sheets metadata <sheetId> --json` - Docs export: `gog docs export <docId> --format txt --out /tmp/doc.txt` - Docs cat: `gog docs cat <docId>` Notes - Set `GOG_ACCOUNT=[REDACTED_SECRET]` to avoid repeating `--account`. - For scripting, prefer `--json` plus `--no-input`. - Sheets values can be passed via `--values-json` (recommended) or as inline rows. - Docs supports export/cat/copy. In-place edits require a Docs API client (not in gog). - Confirm before sending mail or creating events.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sxliuyu/price-alert-monitor (version 1.0.0)

--- name: price-alert-monitor version: 1.0.0 description: 商品价格监控工具。监控电商商品价格变化，价格低于阈值时发送通知。适合购物党、羊毛党。 author: 你的名字 triggers: - "价格监控" - "降价提醒" - "价格走势" - "购物监控" - "亚马逊监控" --- # Price Alert Monitor 📉 监控商品价格变化，发现底价时通知你！ ## 功能 - 🛒 支持监控京东、淘宝、亚马逊等商品 - 📉 记录价格历史，生成走势 - 🔔 价格低于阈值时通知 - 📊 支持多商品同时监控 ## 使用方法 ### 添加商品监控 ```bash python3 scripts/price_monitor.py add "商品URL" ``` ### 查看监控列表 ```bash python3 scripts/price_monitor.py list ``` ### 检查价格 ```bash python3 scripts/price_monitor.py check ``` ### 设置价格提醒 ```bash python3 scripts/price_monitor.py alert "商品ID" 100 ``` ## 示例 ```bash # 监控京东商品 python3 scripts/price_monitor.py add "https://item.jd.com/100086924064.html" # 监控亚马逊商品 python3 scripts/price_monitor.py add "https://www.amazon.com/dp/B09V3KXJPB" # 设置低于 100 元提醒 python3 scripts/price_monitor.py alert 1 100 # 检查所有商品价格 python3 scripts/price_monitor.py check ``` ## 通知设置 需要配置通知方式，支持： - 打印到终端 - 发送邮件（需要配置 SMTP） - 发送到 Webhook ```bash export PRICE_WEBHOOK="your-webhook-url" ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: thomasyo2026/thomas-my-skill (version 1.0.0)

# Thomas My Skill ## Description This is a custom utility skill designed for OpenClaw. It helps the AI agent perform specific data processing tasks locally. It extends the core capabilities of the agent by providing a dedicated workspace toolkit for the user Thomas. ## Usage When the agent needs to process custom text, manage local files, or handle specific workflow automation, it can invoke the tools provided in this skill. ## Tools Included * `process_data`: A tool to format and clean up local data streams. * `get_status`: Returns the current environment status for the agent. ## Note This is my first published skill for testing the deployment pipeline and ensuring all systems are operational.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: thascc1024/test-collection (version 1.0.0)

--- name: test-collection description: 用于测试采集功能的简单 skill，无实际业务逻辑 metadata: { "openclaw": { "emoji": "🧪", "always": true } } --- # Test Collection Skill 这是一个用于测试 skill 采集功能的示例 skill。 ## 用途 - 验证 skill 发现机制 - 测试 skill 优先级覆盖 - 验证配置注入 ## 使用方式 这个 skill 不需要任何特殊操作，只要能被 OpenClaw 发现并加载到系统提示词中即表示成功。 ## 变更记录 - v1.0.0: 初始版本，用于测试


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nic-yuan/04-language-dev (version 1.0.0)

--- name: miki-04-language-dev description: Miki语言发育评估 · 评估12-30月龄词汇量、理解能力，诊断语言发育迟缓风险 version: 1.0.0 author: Miki育儿 tags: - 育儿 - 语言发育 - 12-30月龄 --- # Miki 语言发育评估 **使用方式：** 输入宝宝月龄+会说的词汇+理解能力 → Miki评估发育状态+给出促进方案 --- ## 语言发育标准 ### 12-15个月 - **词汇量：** 1-10个 - **理解能力：** 理解"不"、简单指令（给我/拿来）、认识家人 - **典型行为：** 叫爸妈（特指）、用声音+手势沟通、尝试模仿新发音 - **预警：** 12个月仍无任何有意义发音 ### 15-18个月 - **词汇量：** 10-25个 - **理解能力：** 指认身体部位、理解"不可以"、认识图片 - **典型行为：** 词汇快速增长（每周1-3个新词）、用单词表达完整意思 - **预警：** 18个月词汇<5个、无手指指物 ### 18-24个月 - **词汇量：** 50-100个（爆发期） - **理解能力：** 两步指令、理解大小/颜色概念、听懂简单故事 - **典型行为：** 词汇爆发期、开始2词组合、问"这是什么" - **预警：** 24个月词汇<30个、无2词组合 ### 24-30个月 - **词汇量：** 200-300个 - **理解能力：** 理解空间概念（上面/下面/里面）、认识2种颜色 - **典型行为：** 3-4词短句、开始用"我/你/他"、提问"为什么" - **预警：** 30个月仍无3词句 --- ## 输入模板 ``` 【Miki语言评估】 月龄：X个月 会说的词汇：（尽量列出所有） 如：妈妈、爸爸、奶奶、饭饭、车车、狗狗、拿、抱... 理解能力表现： - 听到名字有反应？ - 能指认身体部位？ - 能听懂简单指令？ - 会用手指点东西？ - 会用哭以外方式表达需求？ 沟通行为： - 会主动叫人？ - 想吃/要抱/想要什么怎么表达？ - 会摇头/点头表示拒绝/要？ 主要担忧：（自由描述） ``` --- ## 输出模板 ``` 🗣 Miki语言发育评估报告 月龄：X个月 ━━━━━━━━━━━━━━━━━━━━ 📊 词汇量评估 ━━━━━━━━━━━━━━━━━━━━ 当前词汇量估计：约XX个 月龄标准范围：XX-XX个 评估结果：✅达标 / ⚠️边缘 / ❌偏少 词汇类型分布： - 称呼类：XX个 - 物品类：XX个 - 动作类：XX个 - 叠词类：XX个 ━━━━━━━━━━━━━━━━━━━━ 🔍 各维度分析 ━━━━━━━━━━━━━━━━━━━━ 【表达性语言】✅/⚠️/❌ 标准 vs 实际：... 【理解性语言】✅/⚠️/❌ 标准 vs 实际：... 【沟通行为】✅/⚠️/❌ 标准 vs 实际：... ━━━━━━━━━━━━━━━━━━━━ ⚠️ 预警（如有） ━━━━━━━━━━━━━━━━━━━━ 问题：... 差距：... 行动建议：... 就医建议：... ━━━━━━━━━━━━━━━━━━━━ 🎯 促进语言发育方案 ━━━━━━━━━━━━━━━━━━━━ 【日常互动技巧】 1. 描述正在做的事（不是教，是说） 2. 等待和回应（宝宝发音后扩展） 3. 手指指物命名 4. 读绘本（每天固定时间） 【语言游戏】 - 命名游戏：家中物品指认 - 模仿游戏：动物叫声、动作词 - 身体部位：唱五官歌 - 日常指令：拿来、给我、放到... ━━━━━━━━━━━━━━━━━━━━ 📅 复查计划 ━━━━━━━━━━━━━━━━━━━━ X周后复查，重点观察：... ``` --- ## 发育迟缓警示 | 月龄 | 警示信号 | |------|---------| | 12个月 | 不会用声音/手势沟通 | | 15个月 | 不会手指指物，不叫爸妈 | | 18个月 | 词汇<5个，不理解简单指令 | | 24个月 | 词汇<30个，无2词组合 | | 30个月 | 词汇<50个，无3词短句 | **发现预警 → 建议咨询儿童保健科或语言发育门诊**


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: devilsbibble/toutiao-auto-publish (version 1.0.0)

--- name: toutiao-publisher description: | 今日头条微头条自动发布工具。自动发布短内容到今日头条平台，支持文本和图片。 使用场景：(1) 用户说"发布头条"、"发微头条"、"头条发布"时触发 (2) 需要自动发布社交媒体内容时 (3) 需要定时发布今日头条时 --- # 今日头条发布工具 使用此 skill 可以自动发布微头条到今日头条平台。 ## 前置要求 1. **Chrome 远程调试已启动**： ```bash /Applications/Google\ Chrome.app/Contents/MacOS/Google\ Chrome --remote-debugging-port=9222 ``` 2. **Chrome 已登录今日头条**：访问 https://mp.toutiao.com 完成登录 3. **Python 依赖**： ```bash pip3 install playwright --break-system-packages playwright install chromium ``` ## 使用方法 ### 基本发布 ```bash cd ~/.openclaw/workspace/skills/toutiao-publisher/scripts python3 toutiao_publish.py "要发布的文字内容" ``` ### 带话题发布 ```bash # 单个话题 python3 toutiao_publish.py "内容文字" --topic "#AI#" # 多个话题 python3 toutiao_publish.py "内容文字" --topic "#AI#,#OpenClaw#,#科技#" ``` ### 带图片发布 ```bash python3 toutiao_publish.py "内容" --image /path/to/image.jpg ``` ### 从文件读取内容 ```bash python3 toutiao_publish.py -f content.txt ``` ### 参数说明 | 参数 | 说明 | 示例 | |------|------|------| | content | 发布内容 | `"今天天气很好"` | | -f, --file | 从文件读取 | `-f post.txt` | | -i, --image | 图片路径 | `--image pic.jpg` | | -t, --topic | 话题标签，多个用逗号分隔 | `--topic "#AI#,#OpenClaw#"` | | --headless | 无头模式 | `--headless` | | --no-wait | 不等待登录 | `--no-wait` | ## 话题格式 话题必须使用 **双 #** 格式： - ✅ 正确：`#AI#`、`#OpenClaw#`、`#科技前沿#` - ❌ 错误：`#AI`、`AI#` 多个话题用逗号分隔，脚本会自动用空格连接。 ## 输出 - **成功截图**：`~/Desktop/toutiao_publish_success.png` - **错误截图**：`~/Desktop/toutiao_error.png` ## 故障排除 | 问题 | 解决方案 | |------|----------| | 无法连接 Chrome | 确保 Chrome 已启动并开启 9222 端口 | | 未检测到登录 | 在 Chrome 中访问 mp.toutiao.com 完成登录 | | 发布失败 | 检查网络连接，查看错误截图 |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: rishabhdugar/unlock-pdf (version 1.0.1)

--- name: unlock-pdf description: "Remove password protection from encrypted PDFs via the PDFAPIHub cloud API. Your PDF and password are sent to pdfapihub.com for decryption. Requires a CLIENT-API-KEY header." --- # Unlock PDF ## What It Does Removes password protection from an encrypted PDF via the PDFAPIHub hosted API. Your PDF file and the decryption password are uploaded to PDFAPIHub servers, where the service decrypts the document and returns the unlocked PDF. ## When to Use - Decrypt a password-protected PDF for further processing - Remove read restrictions from a PDF you own ## Required Inputs - `password` — the password to unlock the PDF - Plus one of: `url`, `base64_pdf`, or multipart `file` upload ## Authentication This skill calls the PDFAPIHub hosted API at `https://pdfapihub.com/api`. Your PDF and password are sent to PDFAPIHub servers for decryption. Send your API key in the `CLIENT-API-KEY` header. Get your **free API key** at [https://pdfapihub.com](https://pdfapihub.com). Full API documentation is available at [https://pdfapihub.com/docs](https://pdfapihub.com/docs). **Security & Privacy:** - Your PDF file and decryption password are transmitted to PDFAPIHub's cloud service over HTTPS - Do not send highly sensitive documents or passwords you use elsewhere without understanding this risk - Files are auto-deleted from PDFAPIHub servers after 30 days - PDFAPIHub does not store or log passwords after processing ## Use Cases - **Legacy Document Access** — Unlock old password-protected PDFs when you have the password - **Workflow Automation** — Decrypt PDFs in an automated pipeline before merging, splitting, or parsing - **Print Enablement** — Remove print restrictions from PDFs you own for printing - **Content Extraction** — Unlock PDFs before running OCR or text extraction - **Pre-Processing** — Decrypt encrypted PDFs before further PDF operations (merge, compress, watermark) ## Example Usage ```bash curl -X POST https://pdfapihub.com/api/v1/unlockPdf \ -H "CLIENT-[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{ "url": "https://pdfapihub.com/sampleprotected.pdf", "password": "secret123", "output": "url" }' ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: baofeng-tech/aisa-perplexity-sonar-search (version 1.0.1)

--- name: aisa-perplexity-sonar-search description: 'Run web, multi-source, or last-30-days research through AIsa. Use when: the user needs search, synthesis, competitor scans, or trend discovery. Supports research-ready outputs and structured retrieval.' author: AIsa version: 1.0.1 license: MIT user-invocable: true primaryEnv: AISA_API_KEY requires: bins: - python3 env: - AISA_API_KEY metadata: aisa: emoji: 🔎 requires: bins: - python3 env: - AISA_API_KEY primaryEnv: AISA_API_KEY compatibility: - openclaw - claude-code - hermes openclaw: emoji: 🔎 requires: bins: - python3 env: - AISA_API_KEY primaryEnv: AISA_API_KEY --- # AIsa Perplexity Sonar Search Run web, multi-source, or last-30-days research through AIsa. Use when: the user needs search, synthesis, competitor scans, or trend discovery. Supports research-ready outputs and structured retrieval. ## When to use - The user needs web, multi-source, or last-30-days research. - The user wants competitor scans, trend discovery, or structured search output. - The user wants one skill to cover multiple retrieval surfaces. ## High-Intent Workflows - Search and summarize recent evidence. - Compare two tools or companies using recent signals. - Turn multi-source retrieval into a research brief. ## Quick Reference - `python3 scripts/perplexity_search_client.py --help` ## Setup - `AISA_API_KEY` is required for AIsa-backed API access. - Use repo-relative `scripts/` paths from the shipped package. - Prefer explicit CLI auth flags when a script exposes them. ## Example Requests - Research OpenAI Agents SDK over the last 30 days - Compare OpenClaw and Codex using recent public discussion - Search recent sentiment around a product launch ## Guardrails - Do not present test-only helpers as public features. - Do not claim sources that were not actually queried. - If some providers time out, report that honestly.


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

--- name: scan-to-markdown description: "OCR document extraction - extract text from scanned documents, photos, and images using OCR. Use when reading scanned PDFs, photographed pages, handwritten notes, or any document that needs optical character recognition." 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"]}]}} --- # Scan to Markdown - OCR for Scanned Docs Extract text from scanned documents and images using OCR via MinerU Open API. No API key required. ## Quick Start ```bash # Scan to Markdown - OCR for Scanned Docs mineru-open-api flash-extract scanned.pdf # Scan to Markdown - OCR for Scanned Docs mineru-open-api flash-extract page-photo.jpg # Scan to Markdown - OCR for Scanned Docs mineru-open-api flash-extract https://example.com/scanned.pdf # Scan to Markdown - OCR for Scanned Docs mineru-open-api flash-extract scanned.pdf --language en # Scan to Markdown - OCR for Scanned Docs mineru-open-api flash-extract scanned.pdf -o ./output/ ``` ## Language Rule You MUST reply to the user in the SAME language they use. This is non-negotiable. ## Capabilities - OCR for scanned PDFs, photographed documents, images - Supports PDF, PNG, JPG, WebP, BMP, TIFF - Supports both local files and URLs directly - Language hint with `--language` (default: `ch`, use `en` for English) - No API key, no signup, no authentication - Max 10MB / 20 pages per document ## When to Use - User asks to "OCR" a document or image - User has a scanned PDF that needs text extraction - User shares a photo of a page and wants the text - User mentions "scan", "handwriting", or "recognize text" ## 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 - Best results with clear, high-resolution scans - For higher precision OCR with full layout preservation, use `mineru-open-api extract --ocr` (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: ldxs001/git-sync (version 2.7.1)

--- name: git-sync version: 2.7.1 author: wUwproject license: MIT description: 将skill代码规范化推送到码云、GitHub，并生成ZIP安装包。 sensitive_access: false critical_write: false permission_weight: LOW data_dir: ../.standardization/git-sync/ tags: [] external_data_dir: true trigger: 同步/上传/推送/发布某个skill trigger_negative: 只是看文件/通用git提交/文件同步到云端 h1_version: true --- # git-sync — 三端同步技能 将 skill 代码规范化推送到**码云（Gitee）**、**GitHub**，并生成 **ZIP 安装包**。 ## 触发场景 当用户提出以下类型请求时，应触发本技能： - 「同步/上传/推送/发布某个 skill」 - 「打包某个 skill」 - 「更新 README.md 的技能列表」 - 「检查某个 skill 的版本号」 **不触发**（以下情况不应触发本技能）： - 用户只是说「帮我看看这个文件」——没有同步/打包意图 - 用户要求「用 git 提交代码」——这是通用 git 操作，不是 skill 同步 - 用户提到「同步」但指的是文件同步（如「同步到云端」）——不是 skill 仓库同步 ## 核心能力 > 📚 **渐进式加载**：本技能采用渐进式 MD 体系，`SKILL.md` 为入口（≤230行），详细内容拆分到 `references/*.md` 按需加载。 - **三端同步** —— 码云、GitHub、本地 `.dist/` 目录 - **版本号三方对比** —— `_meta.json` / `SKILL.md` frontmatter / `references/changelog.md` - **敏感信息过滤** —— 自动扫描并脱敏 `secrets/regex/telemetry` - **SKILL.md 规范审查** —— 内联审计（版本一致性 + R-23 脚本引用检查） - **ZIP 打包 + HTML 索引** —— 生成安装包 + 可视化索引页 ## 工作流程 ## 执行流程（AI 操作指南） > 🔴 **第一步必做**：加载 `references/guide.md` 获取完整执行流程和输出要求。 ### 脚本执行 ```bash cd ~/.workbuddy/skills/git-sync/scripts python scripts/git-sync.py <skill-name> [version] [--skip-scan] ``` ### AI 执行后必须输出（非可选） 脚本运行完毕后，**AI 必须执行以下 4 点**： #### 1. [文本] 完整推送报告 从终端输出提取以下**全部**内容，结构化呈现： ``` 📦 git-sync 执行报告：<skill-name> v<version> | 平台 | 状态 | 版本 | |------|------|------| | 码云 | ✅/❌ | x.x.x | | GitHub | ✅/❌ | x.x.x | ─── 审计报告 ─── 结论：pass/fail（ERROR=N, WARN=N） [逐条列出审计结果] ZIP 包：<完整路径>（<大小> / <文件数> 文件） HTML 索引：<完整路径> ``` **必须包含**：推送状态表 + 审计结论 + ZIP 路径/大小/文件数 + HTML 索引路径。 #### 2. [工具] deliver_attachments — 交付 ZIP 包 #### 3. [工具] preview_url — 打开 `.dist/index.html` #### 4. [文本] 如果 GitHub 推送失败（443 超时），必须询问用户是否重试 ## 渐进式加载说明 本技能采用渐进式 MD 体系，`SKILL.md` 为轻量入口，详细规范拆分到 `references/` 按需加载。 > → 详见 `references/antipatterns.md` > → 详见 `references/faq.md`： - 🔴 `references/guide.md` — **必读**，完整执行流程 + AI 输出要求 - `references/reference.md` — CLI 命令速查、Git 调用规范、路径变量 - `references/changelog.md` — 版本更新记录 - `references/architecture.md` — 内部架构（脚本映射、目录结构） - `references/antipatterns.md` — 反模式（常见错误） - `references/faq.md` — 常见问题（443 超时、版本冲突等） ## 数据目录说明 本技能的数据文件（扫描结果、临时副本、ZIP 包等）存放在： ``` skills/.standardization/git-sync/ ``` 通过 frontmatter 的 `data_dir: ../.standardization/git-sync/` 声明。安装目录 `skills/git-sync/` 只保留 SKILL.md 和 scripts/。


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: jzineldin/openclaw-mission-control (version 1.0.0)

--- name: mission-control description: macOS-native web dashboard for monitoring and controlling your OpenClaw agent. Live chat, cron management, task workshop, scout engine, cost tracking, and more. homepage: https://github.com/Jzineldin/mission-control metadata: { "openclaw": { "emoji": "🖥️", "requires": { "bins": ["node", "npm"] } } } --- # Mission Control — Dashboard for OpenClaw A sleek, macOS-native-feel web dashboard for your OpenClaw agent. Monitor sessions, manage cron jobs, chat in real-time, delegate tasks to sub-agents, discover opportunities, and track costs — all from one beautiful interface. ## Quick Install ```bash # Clone the repo into your workspace cd "$CLAWD_WORKSPACE" 2>/dev/null || cd ~/clawd git clone https://github.com/Jzineldin/mission-control.git cd mission-control # Install dependencies + build frontend npm install cd frontend && npm install && npm run build && cd .. # Create your config cp mc-config.default.json mc-config.json # Start (dev) node server.js # Or use systemd for production: sudo cp mission-control.service /etc/systemd/system/ # Edit paths in the service file, then: sudo systemctl enable --now mission-control ``` Visit `http://localhost:3333` — the Setup Wizard auto-detects your OpenClaw config. ## What You Get | Page | Description | |------|-------------| | **Dashboard** | Agent status, quick actions (email/calendar/heartbeat), activity feed, channels | | **Conversations** | Browse all sessions, view history, continue conversations | | **Workshop** | Kanban task board — queue tasks, sub-agents research, you review reports | | **Cost Tracker** | Token usage per model, daily charts, budget alerts | | **Cron Monitor** | Toggle, run, create, delete scheduled jobs visually | | **Scout** | Auto-discover opportunities — gigs, skills, grants, bounties, news | | **Agent Hub** | All agents/sessions with token counts and management | | **Settings** | Model routing (main/sub-agent/heartbeat), config export/import | | **Skills** | Browse installed + available skills | | **AWS** | *(Optional)* Real costs, Bedrock models, image generation | ## Requirements - OpenClaw running with gateway HTTP enabled - Node.js 18+ - Brave Search API key (for Scout — [free tier](https://brave.com/search/api/)) ## Configuration Auto-detected from your OpenClaw setup: - Gateway token from `~/.openclaw/openclaw.json` - Agent name from `IDENTITY.md` - Model + channels from OpenClaw config Fine-tune via `mc-config.json` or the in-app Settings page. ## Links - **GitHub:** https://github.com/Jzineldin/mission-control - **Support:** https://ko-fi.com/kevinelzarka - **License:** BSL 1.1 (converts to MIT 2030)


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: haresh-sai06/haresh-product-search (version 1.0.2)

--- name: haresh-product-search description: "Search e-commerce products via n8n webhook integration" user-invocable: true --- # Product Search Skill ## Purpose Enables users to search for products in the e-commerce catalog using natural language queries. ## When to Use - User asks to find products, search inventory, or browse catalog - User mentions specific product types, categories, or brands - User provides price constraints or filtering requirements ## Workflow 1. Parse user intent to extract search parameters: - Product category (e.g., "running shoes", "laptops") - Price constraints (e.g., "under $100", "between $50-$200") - Sort preferences (e.g., "cheapest first", "highest rated") 2. Transform parameters into JSON payload with category, price_min, price_max, sort_by 3. Use exec tool to POST to n8n webhook at http://localhost:5678/webhook/product-search 4. Parse n8n response and present results to user in friendly format ## Parameter Mapping - Category synonyms: "gym shoes" becomes "fitness", "sneakers" becomes "footwear" - Price parsing: "under X" sets price_max to X - Sort options: "cheapest" sorts price ascending, "best" sorts by rating ## Error Handling - If no results: Suggest broader search terms - If webhook fails: Inform user search service is unavailable - If timeout: Ask if user wants to wait or retry

path: index.js
content: exports.search_products = async function ({ query }) {
  const response = await fetch("https://your-n8n-webhook-url", {
    method: "POST",
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify({ query })
  });

  if (!response.ok) {
    throw new Error("Webhook request failed");
  }

  return await response.json();
};


path: skill.json
content: {
  "name": "haresh-product-search",
  "description": "Search e-commerce products via n8n webhook integration",
  "entry": "index.js",
  "tools": [
    {
      "name": "search_products",
      "description": "Search products using the n8n webhook",
      "input_schema": {
        "type": "object",
        "properties": {
          "query": {
            "type": "string",
            "description": "Product search query"
          }
        },
        "required": ["query"]
      }
    }
  ]
}


path: _meta.json
content: ownerId: kn72fm5515s8es5a4trvgbrgj1826t2f
slug: haresh-product-search
version: 1.0.1
publishedAt: 1772561891742

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