OpenClaw/clawhub-security-signals huggingface dataset:
Skill: wujiaming88/nova-canvas (version 1.1.0)

--- name: nova-canvas description: >- Generate images using Amazon Nova Canvas via AWS Bedrock. Supports multiple AWS auth methods: environment variables, credentials file, named profiles, IAM instance roles, SSO, or direct access keys. Use when the user asks to generate, create, draw, or produce an image, picture, illustration, photo, artwork, poster, icon, banner, or any visual content. Triggers: "generate an image", "draw me", "create a picture", "make an illustration", "画一张", "帮我画", "生成图片", "做一张图", "AI绘图". Requires AWS Bedrock access with Nova Canvas model enabled. NOT for: editing existing images, generating video, or HTML/CSS canvas rendering. --- # Nova Canvas Generate images via Amazon Nova Canvas on AWS Bedrock. ## AWS Auth Methods | Method | How to Use | |--------|------------| | **Bearer token** | `AWS_BEARER_TOKEN_BEDROCK` env var or `--bearer-token` | | **Environment variables** | Set `AWS_ACCESS_KEY_ID` + `AWS_SECRET_ACCESS_KEY` | | **Credentials file** | Configure `~/.aws/credentials` | | **Named profile** | `--profile my-profile` or `AWS_PROFILE` env var | | **Direct keys** | `--access-key AKIA... --secret-key ...` | | **Temporary credentials** | Add `--session-token` with direct keys | | **IAM instance role** | Auto-detected on EC2/ECS/Lambda | | **AWS SSO** | Run `aws sso login` first | Auto-detection order: direct keys → profile → bearer token → env vars → credentials file → instance role → SSO. ## Quick Start ```bash python3 {baseDir}/scripts/generate.py "your prompt" -o output.png python3 {baseDir}/scripts/generate.py "your prompt" -o output.png --profile work python3 {baseDir}/scripts/generate.py "your prompt" -o output.png --access-key AKIA... --secret-key ... ``` ## Parameters | Flag | Default | Description | |------|---------|-------------| | `prompt` | — | Text description of the image | | `-o, --output` | output.png | Output file path | | `-W, --width` | 1024 | Width 512-4096, divisible by 64 | | `-H, --height` | 1024 | Height 512-4096, divisible by 64 | | `-n, --count` | 1 | Number of images (1-5) | | `-q, --quality` | standard | `standard` or `premium` | | `-s, --seed` | random | Seed for reproducibility | | `--negative` | — | Negative prompt (what to avoid) | | `--cfg` | 8.0 | CFG scale 1.1-10.0 | | `--region` | us-east-1 | AWS region | | `--profile` | — | AWS named profile | | `--access-key` | — | AWS Access Key ID | | `--secret-key` | — | AWS Secret Access Key | | `--session-token` | — | AWS Session Token | | `--bearer-token` | — | Bearer token (overrides env) | ## Workflow 1. Craft a detailed English prompt (Nova Canvas performs best in English). 2. Choose size: square 1024×1024, landscape 1280×768, portrait 768×1280. 3. Run `generate.py` with `timeout=120`. 4. Send resulting image to user via `message` tool. ## Prompt Tips - Detailed English prompts yield best results. - Specify style: "oil painting", "watercolor", "3D render", "photograph", "anime". - Use `--negative "blurry, low quality, text, watermark"` to exclude unwanted elements.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: mazvaris/hello-test (version 1.0.0)

\--- name: hello-test description: Simple test skill that prints hello in chat. \--- \# Hello Test Skill This is a simple test skill used to verify that OpenClaw can load and execute skills. \#\# Instructions When this skill is invoked: 1\. Respond in the chat with the message: Hello\! 👋 This is a test skill from OpenClaw. 2\. Confirm the skill system is working. 3\. Do not perform any other actions.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shandongwill/test-test1 (version 1.0.1)

--- name: test-test01 description: 从test页面获取数据导入到test01 author: Digital Employee Platform Team category: productivity tags: - RPA - excel triggers: - RPA - 数据转储 config: pcs_url: "http://1x.xx.xx.xx:5173" pcs_page: "/#/vmodelDemo" epbp_page: "/#/home" requires: python: true playwright: true --- # test数据自动转储录入技能 ## 功能说明 自动从 PCS 页面抓取表格数据，导出 Excel 后导入到 EBP 系统。 ## 安装依赖 ```bash pip install playwright openpyxl playwright install chromium ``` ## 使用方式 ```bash cd ~/.openclaw/skills/pcs-epbp/scripts python main.py ``` ## 工作流程 1. 打开 PCS 页面：http://xxx:5173/#/vmodelDemo 2. 抓取表格数据 3. 导出为 Excel (pcs_data.xlsx) 4. 打开 EBP 页面：http://xxx:5173/#/home 5. 自动上传 Excel 并导入 ## 定时任务 可配合 cron 实现每日自动执行： ```bash # 每天上午9点执行 0 9 * * * cd ~/.openclaw/skills/test-test01/scripts && python main.py ``` ## 注意事项 - 首次运行需要安装 Playwright 浏览器 - 如页面结构变化，需调整选择器 - EBP 导入按钮选择器可能需要根据实际页面调整


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xueyetianya/communityhub (version 2.0.0)

--- version: "2.0.0" name: Community Manager description: "Community Manager. Use when you need communityhub capabilities. Triggers on: communityhub." 社群运营。社群搭建、活跃度提升、内容规划、用户增长、变现策略、危机处理。Community management toolkit. 社群、运营、私域。 author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # Community Manager 社群运营。社群搭建、活跃度提升、内容规划、用户增长、变现策略、危机处理。Community management toolkit. 社群、运营、私域。 ## Commands - `build` — build - `engage` — engage - `content` — content - `grow` — grow - `monetize` — monetize - `crisis` — crisis ## Usage Run any command with your input to get started. Use `help` to see all available commands. ## About Part of the BytesAgain productivity toolkit. Visit [bytesagain.com](https://bytesagain.com) for more tools. --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com ## Examples ```bash # Show help communityhub help # Run communityhub run ``` - Run `communityhub help` for commands - No API keys needed ## Output Results go to stdout. Save with `communityhub run > output.txt`. ## Configuration Set `COMMUNITYHUB_DIR` to change data directory. Default: `~/.local/share/communityhub/`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zhibuyu/wechat-miniprogram-skill (version 1.0.0)

--- name: wechat-miniprogram-skill version: 1.0.0 description: 微信小程序开发指南 - 从入门到精通。当用户提到微信小程序、小程序开发、WeChat Mini Program、wx API、微信小程序框架时使用此技能。 --- # 微信小程序开发 Skill > 微信小程序开发指南 - 从入门到精通 ## 官方文档 - 开发文档: https://developers.weixin.qq.com/miniprogram/dev/framework/quickstart/ - 框架参考: https://developers.weixin.qq.com/miniprogram/dev/reference/ - 组件文档: https://developers.weixin.qq.com/miniprogram/dev/component/ - API 文档: https://developers.weixin.qq.com/miniprogram/dev/api/ --- ## 小程序简介 小程序是一种全新的连接用户与服务的方式，可以在微信内被便捷地获取和传播。 ### 技术特点 - **快速加载**：从微信本地加载资源 - **原生体验**：流畅的页面切换和操作反馈 - **强大能力**：拍摄、录音、支付、分享等 - **易开发**：类似 Web 开发，学习成本低 ### 与 Web 开发的区别 | 特性 | 小程序 | Web | |------|--------|-----| | 渲染线程 | 双线程 | 单线程 | | DOM API | 不可用 | 可用 | | jQuery/Zepto | 不可用 | 可用 | | 运行环境 | iOS/Android 微信客户端 | 浏览器 | --- ## 项目结构 ``` miniprogram/ ├── app.js # 小程序入口文件 ├── app.json # 全局配置 ├── app.wxss # 全局样式 ├── pages/ # 页面目录 │ └── index/ │ ├── index.js │ ├── index.json │ ├── index.wxml │ └── index.wxss ├── components/ # 自定义组件 └── utils/ # 工具函数 ``` --- ## 全局配置 (app.json) ```json { "pages": ["pages/index/index"], "window": { "navigationBarBackgroundColor": "#000000", "navigationBarTextStyle": "white", "navigationBarTitleText": "小程序标题" }, "tabBar": { "color": "#999999", "selectedColor": "#007AFF", "list": [ {"pagePath": "pages/index/index", "text": "首页"} ] } } ``` --- ## 页面注册 (Page) ```javascript Page({ data: { text: "Hello World" }, onLoad: function(options) { // 页面创建时执行 }, onShow: function() { // 页面出现在前台 }, onPullDownRefresh: function() { // 下拉刷新 }, handleTap: function() { this.setData({ text: '点击了' }); } }); ``` --- ## 模板语法 (WXML) ```xml <!-- 数据绑定 --> <view>{{message}}</view> <!-- 列表渲染 --> <view wx:for="{{array}}" wx:key="id">{{item.name}}</view> <!-- 条件渲染 --> <view wx:if="{{condition}}">显示</view> <!-- 事件处理 --> <view bindtap="handleTap">点击</view> ``` --- ## 常用 API ### 网络请求 ```javascript wx.request({ url: 'https://api.example.com/data', method: 'GET', success: function(res) { console.log(res.data); } }); ``` ### 路由跳转 ```javascript wx.navigateTo({ url: '/pages/detail/detail?id=1' }); wx.redirectTo({ url: '/pages/index/index' }); wx.switchTab({ url: '/pages/index/index' }); wx.navigateBack({ delta: 1 }); ``` ### 数据缓存 ```javascript wx.setStorageSync('key', 'value'); const value = wx.getStorageSync('key'); ``` --- ## 自定义组件 ```javascript Component({ properties: { title: { type: String, value: '默认标题' } }, data: { count: 0 }, methods: { increment: function() { this.setData({ count: this.data.count + 1 }); this.triggerEvent('change', { count: this.data.count }); } } }); ``` --- ## 注意事项 1. **域名配置**：request 域名需在小程序后台配置 2. **HTTPS 要求**：所有网络请求必须使用 HTTPS 3. **代码包大小**：主包限制 2MB，总分包限制 20MB 4. **用户隐私**：使用地理位置等敏感接口需声明 --- ## 参考资源 - [微信小程序官方文档](https://developers.weixin.qq.com/miniprogram/dev/framework/quickstart/) - [小程序组件参考](https://developers.weixin.qq.com/miniprogram/dev/component/) - [小程序 API 参考](https://developers.weixin.qq.com/miniprogram/dev/api/) ## 参考资料 更多小程序文档请参考 `references/` 目录下的文档文件。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dymdsunp-dot/wxwork (version 1.0.0)

--- name: 企业微信消息总结助手 description: 汇总企业微信群聊/单聊消息，提取重点、待办、风险与决策，输出可读的日报/周报/会议纪要；当用户提到“企业微信消息总结、群聊总结、提取待办、生成周报”等需求时触发。 --- # 企业微信消息总结助手 用于把企业微信消息（群聊或单聊）整理成结构化总结，减少信息噪音并突出行动项。 ## 适用场景 - 日报：把当天聊天记录浓缩为重点进展 - 周报：汇总本周关键事项、结果与阻塞 - 会议纪要：提炼结论、决策、负责人和截止时间 - 待办提取：从大量对话中抽取可执行任务 ## 输入要求 至少提供以下其中一项： - 原始聊天文本（推荐，含时间/说话人更好） - 聊天截图（需先OCR） - 关键消息片段（不完整时需标注范围） 可选补充： - 总结时间范围（如“今天 09:00-18:00”） - 输出用途（日报/周报/纪要） - 关注重点（进度、风险、客户反馈、技术问题等） ## 工作流程 1. 清洗文本：去除重复、无意义寒暄与系统噪音 2. 主题聚类：按项目/议题归并消息 3. 事实提取：提取进展、问题、决策、依赖 4. 待办抽取：识别“动作 + 负责人 + 截止时间” 5. 风险识别：标注延迟风险、资源风险、沟通风险 6. 生成输出：按模板给出结构化总结 ## 默认输出模板 ### 1) 一句话总览 - 今天/本周核心情况（1-2 句） ### 2) 关键进展 - 事项A：进展描述 - 事项B：进展描述 ### 3) 关键问题与风险 - 问题/风险：影响 + 当前状态 + 需支持事项 ### 4) 决策与结论 - 决策：结论内容 + 决策人（如可识别） ### 5) 待办清单（行动项） - [负责人] 任务内容（截止：YYYY-MM-DD/未明确） ### 6) 需确认信息 - 缺失但重要的信息点（最多 3 条） ## 质量要求 - 只写可追溯事实，避免臆测 - 待办必须尽量包含负责人与时间 - 同类信息合并，避免重复 - 输出简洁、可直接转发到工作群 ## 注意事项 - 涉及敏感信息时，默认最小披露（可匿名） - 当输入不足以支持结论时，明确标注“信息不足” - 对时间含糊的任务，统一标注“截止未明确”


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: liangbaikaia/kobe-bryant (version 1.0.0)

--- name: kobe-bryant description: 科比·布莱恩特（Kobe Bryant）主题技能。When the user mentions Kobe Bryant, Mamba, basketball legends, Black Mamba, or asks about Kobe's mindset, work ethic, quotes, or life lessons — respond as Kobe would, channeling "Mamba Mentality" and his philosophy on excellence. Distills Kobe's voice: direct, relentless, inspiring, and unapologetically focused on greatness. --- # Kobe Bryant Skill — Mamba Mentality ## Who This Is 你扮演的是科比·布莱恩特（Kobe Bryant）的精神化身。科比是NBA传奇球星，绰号"黑曼巴"（Black Mamba），以"Mamba Mentality（曼巴精神）"闻名于世。 ## Core Philosophy — Mamba Mentality Mamba Mentality is not about results. It's about: - **Obsession** — obsession with excellence, with being the best - **Relentlessness** — never stopping, never slowing down - **Adaptability** — do whatever it takes to win, adjust and overcome - **Focus** — block out noise, execute with precision - **Integrity** — do things the right way even when no one is watching > "The important thing is not about the trophy and the accolades. It's about the journey. The journey of trying to be better than you were the day before. That's what it's about." > — Kobe Bryant ## Tone and Voice **说话风格：** - 直接、简洁、不废话 - 充满信心，甚至有些"傲慢"（但有资本支撑） - 激励人心，但从不甜言蜜语 - 经常引用自己的经历和比赛来阐释观点 - 用词精准，逻辑清晰 **语气特点：** - 自信："我已经证明过无数次了" - 激励："你必须每天都在黑暗中投篮一千次" - 教导："伟大的代价是责任" - 冷静："压力不存在，它是你的想象" ## Response Patterns 当用户问及： - 篮球/比赛 → 分析犀利，引用具体比赛和数据 - 成功/努力 → 强调过程，坚持，细节 - 失败/挫折 → 把失败当老师，从不抱怨 - 领导力 → 以身作则，承担责任 - 生活/平衡 → 专注家庭，热爱所爱 - 追梦 → 立刻行动，不要犹豫 ### 常用表达 - "你知道凌晨四点洛杉矶的样子吗？" - "第二名意味着你是头号输家" - "我现在做的一切，都是为了更加伟大的事" - "你不能学着去爱（憎恨），你生来就有它，或者没有" - "重要的不是结果，而是你走到这里的过程" ## Topics Kobe Would Talk About ### Basketball - 81分比赛（2006年1月22日）：如何在压力下爆发 - 五座总冠军：每一座的含义不同 - 与奥尼尔的三连冠：化学反应与牺牲 - 谢幕战60分（2016年4月13日）：完美告别 ### Mamba Mentality in Work - 细节决定成败 - 刻意练习：一万小时还不够，要十万小时 - 录像分析：看自己的比赛，发现弱点 - 持续进化：每年开发新技能 ### Life Lessons - 父亲是第一位教练 - 女儿 Gianna 的传承 - "亲爱的篮球"——梦想成真 - 创伤与成长 ## What NOT to Do - 不得自怜或抱怨 - 不得虚伪奉承 - 不得表现得轻浮或不确定 - 不得对努力和纪律轻描淡写 - 不得把成功归因于天赋（天赋只是起点） ## Interaction Format 当被问及关于科比的问题或需要以科比精神回应时： 1. 保持角色身份，用科比的视角回答 2. 引用真实数据和经历（如适用） 3. 用有力、简洁、激励性的语言 4. 鼓励用户将 Mamba Mentality 应用于自己的生活 --- *“I don't want to be the next Michael Jordan... I just want to be Kobe Bryant."*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: googleworkspace-bot/recipe-review-meet-participants (version 1.0.12)

--- name: recipe-review-meet-participants description: "Review who attended a Google Meet conference and for how long." metadata: version: 0.22.5 openclaw: category: "recipe" domain: "productivity" requires: bins: - gws skills: - gws-meet --- # Review Google Meet Attendance > **PREREQUISITE:** Load the following skills to execute this recipe: `gws-meet` Review who attended a Google Meet conference and for how long. ## Steps 1. List recent conferences: `gws meet conferenceRecords list --format table` 2. List participants: `gws meet conferenceRecords participants list --params '{"parent": "conferenceRecords/CONFERENCE_ID"}' --format table` 3. Get session details: `gws meet conferenceRecords participants participantSessions list --params '{"parent": "conferenceRecords/CONFERENCE_ID/participants/PARTICIPANT_ID"}' --format table`


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

--- name: forge description: Cross-chain swap routing via THORChain. Get quotes and build swap transactions across 44+ assets (BTC, ETH, RUNE, AVAX, USDC and more). Non-custodial — returns vault address and memo, user's wallet executes. 0.5% affiliate fee to forgemb on every routed swap. version: 0.1.0 author: MoreBetter Studios homepage: https://morebetterstudios.com repository: https://github.com/morebetterclaw/forge api: https://forge-api-production-50de.up.railway.app mcp: https://forge-api-production-50de.up.railway.app/mcp tags: - crypto - defi - thorchain - swap - cross-chain - bitcoin - ethereum - rune --- # FORGE — Cross-Chain Swap Agent Non-custodial cross-chain swaps powered by THORChain. Routes quotes across 44+ assets via the THORNode API directly. Every swap embeds a 0.5% affiliate fee to `forgemb` — protocol-native, trustless, settled in RUNE. ## Live API ``` Base: https://forge-api-production-50de.up.railway.app MCP: https://forge-api-production-50de.up.railway.app/mcp Discovery: https://forge-api-production-50de.up.railway.app/.well-known/mcp.json ``` ## MCP Tools (Claude Desktop / Cursor / any MCP client) ```json { "mcpServers": { "forge": { "url": "https://forge-api-production-50de.up.railway.app/mcp", "transport": "streamable-http" } } } ``` **Tools:** `forge_quote` · `forge_execute` · `forge_assets` · `forge_status` ## REST API ```bash # Get a quote curl -X POST https://forge-api-production-50de.up.railway.app/swap/quote \ -H "Content-Type: application/json" \ -d '{"fromAsset":"ETH.ETH","toAsset":"BTC.BTC","amount":"0.1"}' # Build swap transaction (returns vault address + memo — no funds sent) curl -X POST https://forge-api-production-50de.up.railway.app/swap/execute \ -H "Content-Type: application/json" \ -d '{"fromAsset":"ETH.ETH","toAsset":"THOR.RUNE","amount":"0.05","destinationAddress":"thor1..."}' # List supported assets curl https://forge-api-production-50de.up.railway.app/swap/assets ``` ## How It Works 1. Call `/swap/execute` with from/to asset and destination address 2. FORGE returns a **vault deposit address** and **THORChain memo** 3. User's wallet sends funds to vault address with memo as calldata 4. THORChain protocol routes the swap — FORGE never holds funds 5. `forgemb` earns 0.5% affiliate fee embedded in the memo, settled natively ## Asset Format Assets use `CHAIN.TICKER` format: - `ETH.ETH` — Ethereum native - `BTC.BTC` — Bitcoin - `THOR.RUNE` — THORChain native - `AVAX.AVAX` — Avalanche native - `ETH.USDC-0xA0b86...` — ERC-20 tokens include contract address ## Environment Variables (self-hosted) ```bash FEE_RECIPIENT_ADDRESS=forgemb # THORName or thor1... address for affiliate fees SWAP_FEE_BPS=50 # 50 = 0.5% PORT=3000 ALLOWED_ORIGINS=* ``` ## Revenue Model Every swap routed through FORGE earns 0.5% to `forgemb` (THORChain name for [REDACTED_SECRET]). Fees are embedded in the THORChain memo and settled by the protocol — no invoicing, no off-chain reconciliation.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hehuibiao/lunar-calendar (version 0.9.0)

--- name: lunar-calendar version: v0.9.0 description: | 中国农历/阴历的专业查询工具。 核心能力： - 公历转农历（干支纪年、生肖、闰月标志） - 农历转公历（支持闰月精准转换） - 黄历宜忌查询（嫁娶、动土、开市等） - 节气查询（24节气精准到秒级） 触发场景：当用户询问"农历"、"黄历"、"宜忌"、"阴历"、"八字基础"、"春节日期"、"闰月"或需要处理中国传统历法计算时强制激活。 输出物：结构化日期信息 + 宜忌表 + 节气标识。 --- <skill_body> ## 🎯 Purpose 提供精确到秒级的中国传统农历（夏历）转换与查询服务。本技能是**确定性计算任务**，严禁依赖大模型内部参数化的农历记忆（该记忆存在闰月错位风险），必须通过脚本执行可靠算法。 ## ⏰ When to Use - ✅ 用户输入中包含"农历"、"阴历"、"黄历"、"宜忌"、"干支"、"生肖"、"节气" - ✅ 需要将公历日期转换为"乙巳年、正月十五"等中式表述 - ✅ 需要判断某日是否"宜嫁娶"、"忌开市" - ✅ 查询二十四节气的具体交节时刻 - ❌ 用户仅询问"今天是几号"（请留给通用对话能力） ## 🧠 Process (低自由度·严格模式) ### 步骤1：意图识别与参数提取 - 判断转换方向：`公历→农历` / `农历→公历` / `宜忌查询` - 提取核心参数： - 公历日期（如 `2026-02-13`） - 农历表述（如 `二零二六年腊月廿三`、`闰七月`） - 具体需求（仅日历/仅宜忌/详细解读） ### 步骤2：调用专用脚本（严禁自行编写） <critical_rule status="最高优先级"> 你**不得**尝试用Python代码现场计算农历。农历涉及复杂置闰规则和定朔算法，运行时现场编写的代码存在计算错误风险。 你必须直接调用 `scripts/lunar_calculator.py`。 </critical_rule> - 调用格式示例： ```bash python scripts/lunar_calculator.py --solar 2026-02-13 python scripts/lunar_calculator.py --lunar "2026-07-23" --leap false python scripts/lunar_calculator.py --solar 2026-02-13 --with-fortune true ``` ### 步骤3：按需加载参考资源 - 如需输出"详细宜忌解读"，必须先读取 references/fortune_rules.md - 如需解释"节气原理"，读取 references/solar_terms.md - 严禁将上述Reference全文塞入上下文，仅读取所需章节。 ### 步骤4：结构化组装输出 强制使用以下固定模板，禁止自由发挥格式： ```xml <lunar_query_result> <solar_date>{{输入或计算出的公历日期}}</solar_date> <lunar_date> <year>{{干支年}}（{{生肖}}）</year> <month>{{农历月}}{{闰月标识}}</month> <day>{{农历日}}</day> <festival>{{若有传统节日}}</festival> </lunar_date> <solar_term>{{节气名称}}（{{交节时间}}）</solar_term> <fortune> <suitable>{{宜：条目1、条目2}}</suitable> <avoid>{{忌：条目1、条目2}}</avoid> </fortune> </lunar_query_result> ``` ## 🔍 Decision Logic ```mermaid graph TD A[用户输入] --> B{包含农历/黄历关键词?} B -->|否| C[不激活技能] B -->|是| D{具体请求类型?} D -->|公历转农历| E[提取日期→调用lunar_calculator.py --solar] D -->|农历转公历| F[解析农历字符串→调用lunar_calculator.py --lunar] D -->|查询宜忌| G[调用脚本+读取fortune_rules.md] E --> H[组装XML输出] F --> H G --> H ``` ## ⚠️ Constraints（防走偏） 1. 禁用模糊表述：如"大概是"、"我记得农历好像是"。农历是精确历法，必须输出确定结果。 2. 闰月处理：输出农历月时必须显式标注"闰"字（如"闰七月"），脚本已内置判别逻辑。 3. 时间范围：本技能支持1900-2100年（脚本算法覆盖范围），超出需提示用户。 4. 黄历输出：仅输出传统历书规定的宜忌项，不添加现代演绎内容（如"宜发朋友圈"）。 </skill_body>


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: zitjubiz/etf-monitor (version 1.0.0)

--- name: etf-monitor description: ETF 波动监控 - 实时跟踪 ETF 涨跌幅，超过阈值自动告警 homepage: https://github.com/openclaw/workspace metadata: { "clawdbot": { "emoji": "📊", "requires": { "pip": ["requests"] }, "bins": ["python3"] } } --- # ETF 波动监控技能 实时监控 ETF 价格波动，超过设定阈值时自动告警。 ## 功能特点 - 📡 **实时行情**：使用腾讯财经 API，免费无需 Token - 🎯 **多标的监控**：支持同时监控多只 ETF - ⚠️ **智能告警**：波动超过阈值自动通知 - 🔇 **静默模式**：无告警时不打扰 ## 快速使用 ### 直接运行脚本 ```bash python3 /root/.openclaw/workspace/skills/etf-monitor.py ``` ### 输出格式 **无告警时：** ```json {"alerts": []} ``` **有告警时：** ```json { "alerts": [ { "code": "159985", "name": "豆粕 ETF", "current": 1.234, "percent": 1.5, "direction": "📈" } ] } ``` ## 配置说明 ### 修改监控列表 编辑脚本中的 `ETF_LIST`： ```python ETF_LIST = [ ("sz159985", "159985", "豆粕 ETF"), ("sz159792", "159792", "港股通互联网 ETF"), ("sh515220", "515220", "煤炭 ETF"), # 添加更多 ETF... ] ``` ### 调整波动阈值 ```python THRESHOLD = 1.0 # 波动阈值 1% ``` ## 定时任务示例 每 5 分钟检查一次： ```bash */5 * * * * python3 /root/.openclaw/workspace/skills/etf-monitor.py ``` ## 支持的 ETF 代码格式 - 深交所：`sz` + 6 位代码（如 `sz159985`） - 上交所：`sh` + 6 位代码（如 `sh515220`） ## 注意事项 1. 需要网络连接访问腾讯财经 API 2. 行情数据可能有 1-2 分钟延迟 3. 建议阈值设置为 1%-3% 之间 --- **版本：** v5 **最后更新：** 2026-03-18


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: chaoyang78/wechat-preflight-check (version 1.0.0)

--- name: wechat-preflight-check description: 用于微信公众号发布前检查 Markdown 文章 --- # 微信公众号发布前检查工具 ## 用途 在将 Markdown 文章发布到微信公众号之前，进行自动化检查以确保文章格式正确、素材齐全。 ## 何时调用 当用户要求检查微信公众号文章是否符合发布标准时调用此 skill。 ## 检查项清单 1. 是否存在 frontmatter（YAML 头部信息） 2. 是否存在 title（文章标题） 3. 是否存在 cover（封面图片） 4. cover 是否为可访问 URL 或存在的本地文件 5. Markdown 文章内的图片路径是否存在 6. 是否发现 Obsidian wiki 图片链接 ![[...]]（微信不支持） 7. 是否存在未标注语言的 fenced code block ## 执行命令 ```bash python3 scripts/check.py <markdown_file> ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: gblockchainnetwork/ollama-seo-auditor (version 1.0.0)

---\nname: ollama-seo-auditor\ndescription: Local SEO site audit using Ollama LLM + OpenClaw web tools (web_fetch, browser). Use when user asks for SEO analysis, keyword check, site structure/speed review, optimization tips. Triggers: \"audit SEO\", \"check site performance\", \"analyze web page SEO\". Runs local on VPS for privacy/low-cost.\n---\n\n# Ollama SEO Auditor\n\n## Quick Audit\n1. web_fetch url pt content.\n2. Prompt Ollama (llama3:8b): \"Analyze SEO: keywords, meta, headings, img alt, speed est. from HTML. Score 1-10. Fixes.\"\n3. browser/screenshot pt visual (opțional).\n4. Report Markdown + score.\n\n## Tools\n- exec 'ollama run llama3.8b \"prompt\"'\n- web_search 'SEO best practices 2026'\n\n## Refs\nSee references/seo-checklist.md (load if detailed).\n\nScripts/audit.py: exec pt full run.


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: malicious | SkillSpector: clean (LOW)
Skill: atiati82/andara-meeting-minutes (version 1.0.0)

--- name: andara-meeting-minutes description: Capture meeting summaries and action items from voice or text --- # Meeting Minutes Skill When ATTi or a team member sends a meeting summary (voice or text), save it as a structured record. ## Trigger When user says something like "Meeting Notes:", "Besprechungsnotizen:", or "save meeting" — parse the content and store it. ## Steps 1. Extract the meeting topic, attendees, decisions, and action items from the message. 2. Save to PostgreSQL using bash + psql: ```bash psql "$DATABASE_URL" -c " INSERT INTO team_meetings (title, summary, attendees, meeting_date, created_at) VALUES ('TOPIC', 'SUMMARY', ARRAY['ATTENDEE1','ATTENDEE2'], NOW(), NOW()) RETURNING id;" ``` 3. For each action item, insert into meeting_action_items: ```bash psql "$DATABASE_URL" -c " INSERT INTO meeting_action_items (meeting_id, assignee, description, due_date, status, created_at) VALUES (MEETING_ID, 'ASSIGNEE', 'TASK DESCRIPTION', 'DUE_DATE', 'pending', NOW());" ``` 4. Confirm to the user: "Meeting gespeichert ✅ — [X] Action Items erstellt." ## Output Format Reply in German with a structured summary: - 📋 Meeting: [Title] - 👥 Teilnehmer: [Names] - ✅ Action Items: [List with assignees] - 📅 Nächstes Treffen: [if mentioned]


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