OpenClaw/clawhub-security-signals huggingface dataset:
Skill: tobeyrebecca/toby-build-developer-faq-page (version 1.0.0)

--- name: "Build Developer FAQ Page" description: "Generate customer-facing answers for common developer questions. Use when working on FAQ content for developers, technical founders, product engineers." homepage: "https://www.skillboss.co/skills/build-developer-faq-page" metadata: {"category":"developer-tools","subcategory":"automation","skill_id":"build-developer-faq-page","generated_day":"","seo_keywords":["FAQ generator AI","developer FAQ writer","developer workflow AI","engineering automation tool"]} --- # Build Developer FAQ Page Generate customer-facing answers for common developer questions. Use when working on FAQ content for developers, technical founders, product engineers. ## Use When Use this skill for FAQ content work for developers, technical founders, product engineers. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: FAQ generator AI, developer FAQ writer, developer workflow AI, engineering automation tool - Search intent: FAQ content - Canonical slug: `build-developer-faq-page` - Install query: Install Build Developer FAQ Page with SkillBoss ## APIs Used - `chat` - `web_search` ## Suggested Prompt [Build Developer FAQ Page] for my team ## Notes - Generate customer-facing answers for common developer questions - Review outputs before external publication or automated execution. ## SEO Keywords - FAQ generator AI - developer FAQ writer - developer workflow AI - engineering automation tool


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: benediktschackenberg/azure-proxy (version 1.0.0)

--- name: azure-proxy description: Enable Azure OpenAI integration with OpenClaw via a lightweight local proxy. Use when configuring Azure OpenAI as a model provider, when encountering 404 errors with Azure OpenAI in OpenClaw, or when needing to use Azure credits (e.g. Visual Studio subscription) with OpenClaw subagents. Solves the api-version query parameter issue that prevents direct Azure OpenAI integration. --- # Azure OpenAI Proxy for OpenClaw A lightweight Node.js proxy that bridges Azure OpenAI with OpenClaw. ## The Problem OpenClaw constructs API URLs like this: ```javascript const endpoint = `${baseUrl}/chat/completions`; ``` Azure OpenAI requires: ``` https://{resource}.openai.azure.com/openai/deployments/{model}/chat/completions?api-version=2025-01-01-preview ``` When `api-version` is in the baseUrl, OpenClaw's path append breaks it. ## Quick Setup ### 1. Configure and Run the Proxy ```bash # Set your Azure details export AZURE_OPENAI_ENDPOINT="your-resource.openai.azure.com" export AZURE_OPENAI_DEPLOYMENT="gpt-4o" export AZURE_OPENAI_API_VERSION="2025-01-01-preview" # Run the proxy node scripts/server.js ``` ### 2. Configure OpenClaw Provider Add to `~/.openclaw/openclaw.json`: ```json { "models": { "providers": { "azure-gpt4o": { "baseUrl": "http://127.0.0.1:18790", "apiKey": "YOUR_AZURE_API_KEY", "api": "openai-completions", "authHeader": false, "headers": { "api-key": "YOUR_AZURE_API_KEY" }, "models": [ { "id": "gpt-4o", "name": "GPT-4o (Azure)" } ] } } }, "agents": { "defaults": { "models": { "azure-gpt4o/gpt-4o": {} } } } } ``` **Important:** Set `authHeader: false` — Azure uses `api-key` header, not Bearer tokens. ### 3. (Optional) Use for Subagents Save Azure credits by routing automated tasks through Azure: ```json { "agents": { "defaults": { "subagents": { "model": "azure-gpt4o/gpt-4o" } } } } ``` ## Run as systemd Service Copy the template and configure: ```bash mkdir -p ~/.config/systemd/user cp scripts/azure-proxy.service ~/.config/systemd/user/ # Edit the service file with your Azure details nano ~/.config/systemd/user/azure-proxy.service # Enable and start systemctl --user daemon-reload systemctl --user enable azure-proxy systemctl --user start azure-proxy ``` ## Environment Variables | Variable | Default | Description | |----------|---------|-------------| | `AZURE_PROXY_PORT` | `18790` | Local proxy port | | `AZURE_PROXY_BIND` | `127.0.0.1` | Bind address | | `AZURE_OPENAI_ENDPOINT` | — | Azure resource hostname | | `AZURE_OPENAI_DEPLOYMENT` | `gpt-4o` | Deployment name | | `AZURE_OPENAI_API_VERSION` | `2025-01-01-preview` | API version | ## Health Check ```bash curl http://localhost:18790/health # {"status":"ok","deployment":"gpt-4o"} ``` ## Troubleshooting **404 Resource not found:** Check endpoint hostname and deployment name match Azure Portal. **401 Unauthorized:** API key is wrong or expired. **Content Filter Errors:** Azure has aggressive content filtering — some prompts that work on OpenAI may get blocked.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: saikewei/toefl-speaking (version 1.0.1)

--- name: toefl-speaking slug: toefl-speaking version: 2.1.0 description: 托福口语面试部分出题引擎。AI 自动选定主题，生成 4 道递进式面试题和参考答案。不依赖固定主题库。 --- # TOEFL Speaking 出题引擎 ## 核心能力 输入一个主题 → 输出 4 道递进式问题 + 隐藏的参考答案（存入文件，不展示）。 ## 出题规则 ### 主题选择 主题由 AI 完全自主决定。每次出题时： 1. 读取 `toefl/history.json`，查看最近 10 个已出过的主题 2. 从中等或高等难度的学术/校园话题中选一个**与之不同的方向** 3. 尽可能保证与最近 10 次不重复、话题跨度大、有随机性 ### 题目结构 Q1 (Past/Experience) → Q2 (Habit/Preference) → Q3 (Deep Opinion) → Q4 (Future/Policy) ### 参考文献 出题格式和答案标准见 `prompt-template.md`。 ## 与用户互动 | 用户说 | 我做 | |--------|------| | "来一套题" / "出题" | 1. 读取 `toefl/history.json` 看最近10个主题 2. 选新主题出4道题，生成参考答案 3. 写入 `toefl/latest.md`（含完整题目+答案+解析） 4. 更新 `toefl/history.json`（追加新记录） 5. 复制至 `toefl/YYYY-MM-DD.md` 存档 6. 只向用户展示4道问题，隐藏答案 | | "今天的答案" / "Q1的答案" | 读 `toefl/latest.md` 展示对应答案+解析 | | "评价一下我的回答" | 用户给出回答后，按评分标准反馈（流利度、词汇、语法、内容） | | "换一个" / "换个话题" | 重选主题重新出题，标记旧题作废 | ## 数据存储 ``` toefl/ ├── latest.md # 最新一套题（含答案，供查看答案时读取） ├── history.json # 出题记录（主题+日期+是否看过答案） └── YYYY-MM-DD.md # 每日存档 ``` ## 注意事项 - 不依赖固定主题列表，AI 自主生成主题 - 不包含任何定时/调度逻辑，触发方式由外部决定


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: olina1ye/browser-automation-zh (version 1.0.0)

--- name: browser-automation-zh description: > 浏览器自动化 / 网页爬虫 / 自动化脚本 / web scraping / browser automation。自动填表、数据抓取、网页截图、自动化测试一站式解决。适配电商运营的比价监控、市场部的竞品跟踪、数据分析师的批量采集、技术团队的UI自动化测试。用户常搜：怎样自动爬取网页数据、批量填充表单、网页自动化测试工具、Puppeteer怎么用、如何监控竞品价格。 tags: [浏览器自动化, 网页爬虫, 数据抓取, web-scraping, 自动化脚本, 自动化测试, Puppeteer, Playwright, 竞品监控, 运营效率] --- # 浏览器自动化 自动化控制浏览器完成网页导航、元素交互、数据提取、截图等操作，适用于爬虫采集、自动化测试和批量工作流。 ## Tools Required - browser_navigate - browser_click - browser_type - browser_screenshot ## Usage - "帮我抓取京东上这个商品类目下所有商品的名称、价格和链接" - "自动登录后台系统，截图保存每日销售报表页面" - "批量填写表单并提交，模拟用户操作流程做自动化测试" ## Examples 输入：抓取某电商平台前50条商品信息，包括商品名、价格、评论数 输出： ```json [ {"name": "iPhone 15 Pro 256G", "price": "7999", "reviews": "12843"}, {"name": "华为Mate60 Pro", "price": "6999", "reviews": "9521"}, ... ] ``` 输入：每天早上9点自动截图公司数据看板并保存 输出：执行截图脚本，保存为 `dashboard_20240115_0900.png`，并输出操作日志确认成功


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: edwardyen724-g/web-distiller (version 0.1.0)

--- name: web-distiller version: 0.1.0 description: Fetch agent-ready cleaned Markdown from the Distiller API instead of relying on raw webpage fetches. categories: - search - data-analytics metadata: openclaw: requires: env: - DISTILLER_API_BASE primaryEnv: DISTILLER_API_KEY --- # Web Distiller Use this skill when the operator wants reliable cleaned webpage content for an agent workflow. ## Default behavior - Treat Distiller as a setup-friendly external API, not a hard prerequisite. - If `DISTILLER_API_KEY` is missing, treat that as a setup state: - explain that the user can sign in at `https://webdistiller.dev` - direct them to the dashboard to create or reveal their API key - continue with setup guidance instead of failing the workflow - Default to `POST /markdown`. - Only use `POST /distill` when the operator already has paid Starter access. - If `POST /distill` is denied, switch back to `POST /markdown` and tell the operator that `/distill` requires a paid plan. - Do not build new workflows around `POST /extract` until it is re-enabled. ## Install ```bash pip install web-distiller ``` ## Environment Recommended: ```env DISTILLER_API_BASE=https://webdistiller.dev DISTILLER_API_KEY=your-api-key ``` If `DISTILLER_API_KEY` is not available yet: 1. Send the operator to `https://webdistiller.dev/signin` 2. Have them open the dashboard at `https://webdistiller.dev/dashboard` 3. Retrieve or regenerate the API key there 4. Resume with `POST /markdown` ## Default command ```bash web-distiller <url> ``` Useful variants: - `web-distiller <url> --endpoint markdown --format markdown` - `web-distiller <url> --endpoint markdown --format text` - `web-distiller <url> --endpoint distill --format markdown` - `web-distiller <url> --endpoint distill --format json` ## Batch workflow Submit a markdown batch by default: ```bash curl -X POST https://webdistiller.dev/batch \ -H "content-type: application/json" \ -H "Authorization: Bearer $DISTILLER_API_KEY" \ -d '{"mode":"markdown","urls":["https://example.com","https://example.org"]}' ``` Poll the batch job: ```bash curl https://webdistiller.dev/batch/<job_id> \ -H "Authorization: Bearer $DISTILLER_API_KEY" ``` Batch rules: - free users should use `mode="markdown"` - paid users can use `mode="markdown"` or `mode="distill"` - `mode="extract"` is currently unavailable ## Operator guidance - Use `--format markdown` as the best default for LLM workflows. - Use `--format text` when the operator wants the smallest prompt payload. - Use `--format json` when a tool needs metadata and billing fields too. - Use `--use-browser` for JavaScript-heavy pages when the normal path is not enough. - If a request fails with a content-delivery error, explain that Distiller could not safely deliver the page and suggest a different URL or browser rendering.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bombfuock/feishu-img-send (version 1.0.0)

--- name: feishu-image-sender description: 飞书图片发送 - 使用API直接发送图片到飞书 / Send images to Feishu via API metadata: version: 1.0.0 --- # 飞书图片发送 / Feishu Image Sender 通过飞书开放平台API发送图片。 ## 使用方法 / Usage ### 命令行 ```bash # 发送图片 ./scripts/send.sh <图片路径> <用户ID> # 示例 ./scripts/send.sh /tmp/test.png ou_xxxxxxxx ``` ### Python ```python from feishu_image import FeishuImageSender sender = FeishuImageSender() sender.send_image("/tmp/test.png", "ou_xxxxxxxx") ``` ## 配置 / Configuration 脚本已内置APP_ID和APP_SECRET，无需额外配置。 ## 原理 / How It Works 1. 获取 tenant_access_token 2. 上传图片到飞书获取 image_key 3. 使用 image_key 发送图片消息 ## API调用 ``` POST /open-apis/auth/v3/tenant_access_token/internal POST /open-apis/im/v1/images POST /open-apis/im/v1/messages ``` ## 权限要求 - im:resource - im:message ## 更新日志 - v1.0.0: 初始版本


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: mirni/gh-agentfinder (version 1.0.0)

--- name: gh-agentfinder description: "Kayak for agents — search across ClawHub, SkillsMP, LobeHub, and more to find the right skill for your task. Compare results across registries, get recommendations for your problem, and discover agents with specific capabilities." metadata: {"openclaw":{"emoji":"🔎","requires":{"bins":["python"]},"install":[{"id":"pip","kind":"uv","packages":["fastapi","uvicorn","pydantic"]}]}} --- # AgentFinder Find the right skill across multiple registries in one call. ## Start the server ```bash uvicorn agentfinder.app:app --port 8016 ``` ## Search across all registries ```bash curl -s -X POST http://localhost:8016/v1/search \ -H "Content-Type: application/json" \ -d '{"query": "security scanning"}' | jq ``` Returns results sorted by relevance, from ClawHub, SkillsMP, LobeHub, and more. ## Compare results by registry ```bash curl -s http://localhost:8016/v1/search/security/compare | jq ``` ## Get recommendations for a problem ```bash curl -s -X POST http://localhost:8016/v1/recommend \ -H "Content-Type: application/json" \ -d '{"problem": "I need to validate data before passing it to another agent"}' | jq ``` ## Filter by registry ```bash curl -s -X POST http://localhost:8016/v1/search \ -H "Content-Type: application/json" \ -d '{"query": "code review", "registries": ["clawhub"], "max_results": 5}' | jq ``` ## List available registries ```bash curl -s http://localhost:8016/v1/registries | jq ``` ## Endpoints | Method | Path | Description | |--------|------|-------------| | POST | /v1/search | Search across registries | | GET | /v1/search/{query}/compare | Compare by registry | | POST | /v1/recommend | Recommend skills for a problem | | GET | /v1/registries | List available registries |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: aimlapihello/aiml-image-video (version 1.0.2)

--- name: aimlapi-media-gen description: Generate images or videos via AIMLAPI from prompts. Use when Codex needs reliable AI/ML API media generation with retries, explicit User-Agent headers, and async video polling. env: - AIMLAPI_API_KEY primaryEnv: AIMLAPI_API_KEY --- # AIMLAPI Media Generation ## Overview Generate images and videos via AIMLAPI with scripts that include retries, API key file fallback, verbose logs, and required `User-Agent` headers on every request. ## Quick start ```bash export AIMLAPI_API_KEY="sk-aimlapi-..." python3 {baseDir}/scripts/gen_image.py --prompt "ultra-detailed studio photo of a lobster astronaut" python3 {baseDir}/scripts/gen_video.py --prompt "slow drone shot of a foggy forest" ``` ## Tasks ### Generate images Use `scripts/gen_image.py` with `/v1/images/generations`. ```bash python3 {baseDir}/scripts/gen_image.py \ --prompt "cozy cabin in a snowy forest" \ --model aimlapi/openai/gpt-image-1 \ --size 1024x1024 \ --count 2 \ --retry-max 4 \ --user-agent "openclaw-custom/1.0" \ --out-dir ./out/images ``` ### Generate videos (async AIMLAPI flow) Use `scripts/gen_video.py` with the real async flow: 1. `POST /v2/video/generations` (create task) 2. `GET /v2/video/generations?generation_id=...` (poll status) 3. download `video.url` when status is completed ```bash python3 {baseDir}/scripts/gen_video.py \ --model google/veo-3.1-t2v-fast \ --prompt "time-lapse of clouds over a mountain range" \ --poll-interval 10 \ --max-wait 1000 \ --user-agent "openclaw-custom/1.0" \ --out-dir ./out/videos ``` ## References - `references/aimlapi-media.md`: endpoint notes, async polling statuses, and troubleshooting. - `README.md`: changelog-style summary of new instructions.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (HIGH)
Skill: edwardrodriguez703-design/book-locksmith (version 1.0.1)

--- name: book-locksmith description: Book locksmith services through Lokuli MCP. Use when user needs to find and book locksmith. Triggers on requests like "book a locksmith", "find locksmith near me", or any locksmith service request. --- # uook locksmith Book locksmith services through Lokuli's MCP server. ## MCP Endpoint ``` https://lokuli.com/mcp/sse ``` Transport: SSE | JSON-RPC 2.0 | POST requests ## Tools ### search ```json { "method": "tools/call", "params": { "name": "search", "arguments": { "query": "locksmith", "zipCode": "90640", "maxResults": 20 } } } ``` ### check_availability ```json { "method": "tools/call", "params": { "name": "check_availability", "arguments": { "providerId": "xxx", "serviceId": "yyy", "date": "2025-02-10" } } } ``` ### create_booking ```json { "method": "tools/call", "params": { "name": "create_booking", "arguments": { "providerId": "xxx", "serviceId": "yyy", "timeSlot": "2025-02-10T14:00:00-08:00", "customerName": "John Doe", "customerEmail": "[REDACTED_SECRET]", "customerPhone": "+13105551234" } } } ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: afeicn/legal-assistant (version 0.1.0)

--- name: legal-assistant description: "法务助手（Legal Assistant）。协助完成合同接收分类、合同要素抽取、条款风险审查、模板对比、修改建议生成、法律咨询问答、审批意见草拟与合同台账更新的完整合同与法务闭环。本工具由 @afeicn 提供支持。" metadata: author: afeicn --- # 法务助手 (Legal Assistant) ## 概述 法务助手（Legal Assistant）是面向法务与企业经营管理者的岗位型数字员工。它覆盖合同审查、要素抽取、条款对比、修改建议、法务咨询、审批意见生成等核心法务协作场景，协助市场、销售、采购和法务负责人完成以下 8 大业务场景： 1. **合同接收** — 接收合同并识别类型、主体、金额、期限和业务场景。 2. **要素抽取** — 抽取付款、交付、违约、保密、知识产权和争议解决条款。 3. **条款风险审查** — 审查合同付款、交付、违约、责任及争议等条款中的潜在法律风险。 4. **模板对比** — 与标准模板对比差异、寻找缺失条款并提取非标条款。 5. **修改建议** — 针对风险条款生成法务修改意见、替代条款和谈判口径。 6. **法律咨询** — 基于法律知识库和公司规章解答日常用工、采购及商务合规问题。 7. **审批意见** — 汇总合同要素、潜在风险和建议，一键生成法务审批意见草稿。 8. **合同台账** — 维护合同台账状态、记录关键要素、标签化归档，设置合同期限提醒。 --- ## 工作原则与边界 ### 工作原则 1. **要素先行**：先识别用户意图、输入材料、合同类型及期限。 2. **结构化输出**：输出必须结构化，默认包含处理结论、关键要素、风险提示、建议动作、需人工确认事项。 3. **严谨核验**：没有明确法律或模板依据时必须标记“需人工确认”，不得将推测作为事实依据。 4. **严格保密**：对合同金额、合作双方及敏感协议条款采取严格脱敏处理，防止机密数据泄露。 ### 行为边界 (不可以做) - **人工最终决策**：涉及正式法律意见出具、高风险条款同意、对外法律承诺/回复、最终合同盖章审批时，**必须提交负责人人工确认**。不得替代律师出具强制性法律结论；不得代替人工自动签署/盖章合同；不得擅自承诺系统已执行终审提交。 - **脱敏规范**：演示与测试样例必须使用脱敏或虚拟示范数据，禁止引入真实的客户资产、员工隐私及商业合同敏感内容。 --- ## 核心业务流程 (Workflows) ### 1. 合同接收与分类 - **流程**：接收合同文件（Word/PDF/截图） → 识别合同类型（采购、销售、保密、劳动等）及业务场景 → 关联送审人与版本号。 - **输出**：合同受理记录、合同类型、版本状态。 ### 2. 合同要素抽取 - **流程**：解析合同文档结构 → 抽取付款方式、交付标准、违约金比例、保密责任、争议管辖等关键交易要素。 - **输出**：核心要素清单、主体信息、金额/支付条款、交付及时间节点要求。 ### 3. 条款风险审查 - **流程**：对照公司合规基准规则 → 扫描合同高风险条款（如免责范围过大、限制条款过多、违约比例不对等） → 标记风险级别并指出背灵公司政策的细节。 - **输出**：风险清单、风险等级判定、规则偏差依据。 ### 4. 条款模板对比 - **流程**：将送审合同与对应的公司标准模板进行段落比对 → 找出缺失的必备条款（如反商业贿赂、争议解决管辖等） → 提取非标条款和负面清单。 - **输出**：模板差异对比、缺失必备条款表、非标条款汇总。 ### 5. 修改建议生成 - **流程**：针对被审查出的风险或偏差条款 → 生成法务倾向的修改措辞与备用（替代）条款 → 整理合同商务谈判话术和谈判底线。 - **输出**：法务修改意见、替代推荐条款、谈判口径提示。 ### 6. 法律咨询问答 - **流程**：接收法律咨询诉求 → 检索相关法典、地方法规以及企业内部管理规定 → 生成专业的回答大纲，并明示法律条文出处及法务专家复核提示。 - **输出**：专业法律解答、法律依据引用、人工确认提示。 ### 7. 合同审批意见生成 - **流程**：归纳已审查合同的要素汇总、核心风险以及最终修改建议 → 自动起草一份专业的“法务合同审批意见”草稿。 - **输出**：审批意见正文草稿、关键风险摘要卡片。 ### 8. 合同台账更新 - **流程**：在合同通过预审或流转后 → 自动抽取并录入合同台账记录 → 标记金额、收付款进度、履约周期 → 生成合同到期、续签及里程碑提醒任务。 - **输出**：台账记录条目、预警提醒、期限节点事件。 --- ## 默认输出格式 法务助手在生成日常分析和应答时，默认使用以下结构输出： ```text 【处理结论】 [建议通过/谨慎签署/存在高风险/需法务复核等结论] 【关键信息】 - [提取出的主要合同条款要素与事实] 【风险/缺口】 - [不合规或缺失的重要条款，需注明偏离基准的要点] 【建议动作】 - [建议进行的合同修改动作或协商方向] 【需人工确认】 - [必须由人工终审或律师复议确认的细节] 【归档记录】 - [本次预审记录归档路径与合同台账更新状态] ``` --- Powered by legal-assistant | Author: afeicn


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: vigor-jzhang/fluxra-agent-chat (version 0.1.1)

--- name: fluxra-agent-chat description: Agent-to-agent chat over Fluxra using Fluxra CLI (DM, group chat, inbox sync, MCP). user-invocable: true --- # Fluxra Agent Chat Use this skill to communicate with other agents through the Fluxra AgentChat network. --- ## When to use - Send a message to another agent - Send a message to a group (conversation) - Check unread messages - Sync inbox - Initialize or verify Fluxra identity - Expose Fluxra as MCP tools --- ## Preconditions Fluxra CLI must be installed: ```bash npm install -g @fluxra-ai/fluxra-cli ```` Verify: ```bash fluxra auth whoami ``` --- ## Core rules 1. Always use Fluxra CLI (never simulate messaging) 2. Never fabricate: * agent IDs (`agt_...`) * conversation IDs (`conv_...`) 3. Always sync before reading inbox 4. Do not expose secrets (keys, tokens) 5. If unsure, inspect schema: ```bash npx @fluxra-ai/fluxra-cli schema ``` --- ## Workflows ### Initialize agent ```bash fluxra profile create my-agent --set-default fluxra auth register AgentName --email [REDACTED_SECRET] fluxra auth whoami ``` Optional: ```bash fluxra chat directory profile set --intro "AI Agent" --status active ``` --- ### Send direct message ```bash fluxra chat send agt_TARGET_ID "message" ``` --- ### Send group message ```bash fluxra chat send conv_GROUP_ID "message" ``` With mention: ```bash fluxra chat send conv_GROUP_ID "Hi @agt_ID" --mention agt_ID ``` --- ### Sync and read messages ```bash fluxra chat sync once fluxra chat unread fluxra chat peek --limit 5 ``` --- ### MCP mode ```bash npx @fluxra-ai/fluxra-cli mcp serve ``` --- ## Decision logic | User intent | Action | | ---------------- | -------------------- | | "message agent" | DM | | "message group" | group send | | "check inbox" | sync + unread + peek | | "setup fluxra" | initialize | | "what can it do" | schema | --- ## Failure handling * CLI not installed → install * not logged in → register * missing ID → ask user * send failed → check auth/network --- ## Output style * Be explicit about commands * Do not claim success unless confirmed * Keep responses concise and operational --- ## Reference ```bash fluxra help:all fluxra auth whoami fluxra chat send agt_xxx "hello" fluxra chat sync once npx @fluxra-ai/fluxra-cli schema ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: googleworkspace-bot/gws-gmail (version 1.0.14)

--- name: gws-gmail description: "Gmail: Send, read, and manage email." metadata: version: 0.22.5 openclaw: category: "productivity" requires: bins: - gws cliHelp: "gws gmail --help" --- # gmail (v1) > **PREREQUISITE:** Read `../gws-shared/SKILL.md` for auth, global flags, and security rules. If missing, run `gws generate-skills` to create it. ```bash gws gmail <resource> <method> [flags] ``` ## Helper Commands | Command | Description | |---------|-------------| | [`+send`](../gws-gmail-send/SKILL.md) | Send an email | | [`+triage`](../gws-gmail-triage/SKILL.md) | Show unread inbox summary (sender, subject, date) | | [`+reply`](../gws-gmail-reply/SKILL.md) | Reply to a message (handles threading automatically) | | [`+reply-all`](../gws-gmail-reply-all/SKILL.md) | Reply-all to a message (handles threading automatically) | | [`+forward`](../gws-gmail-forward/SKILL.md) | Forward a message to new recipients | | [`+read`](../gws-gmail-read/SKILL.md) | Read a message and extract its body or headers | | [`+watch`](../gws-gmail-watch/SKILL.md) | Watch for new emails and stream them as NDJSON | ## API Resources ### users - `getProfile` — Gets the current user's Gmail profile. - `stop` — Stop receiving push notifications for the given user mailbox. - `watch` — Set up or update a push notification watch on the given user mailbox. - `drafts` — Operations on the 'drafts' resource - `history` — Operations on the 'history' resource - `labels` — Operations on the 'labels' resource - `messages` — Operations on the 'messages' resource - `settings` — Operations on the 'settings' resource - `threads` — Operations on the 'threads' resource ## Discovering Commands Before calling any API method, inspect it: ```bash # Browse resources and methods gws gmail --help # Inspect a method's required params, types, and defaults gws schema gmail.<resource>.<method> ``` Use `gws schema` output to build your `--params` and `--json` flags.


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