OpenClaw/clawhub-security-signals huggingface dataset:
Skill: wespeakallday/email-campaign (version 2.0.0)

--- name: email-campaign description: PayLessTax email automation system - 4x daily, 250 emails each version: 2.0.0 author: Migration from Agent Zero --- # Email Campaign Skill ## Overview High-volume email campaign system for PayLessTax. Delivers 1,000 emails daily in 4 batches. ## Purpose - Send 250 emails per batch, 4 batches daily (6am, 12pm, 3pm, 6pm) - Track bounces and unsubscribes - Scrape inbox for new contacts - Manage Google Workspace Gmail via service account ## Input Variables | Variable | Description | Example | |----------|-------------|---------| | GOOGLE_SERVICE_ACCOUNT | JSON credentials | { "type": "service_account", ... } | | USER_EMAIL | Sending user email | [REDACTED_SECRET] | | ALIAS_EMAIL | From address | [REDACTED_SECRET] | | MAILING_LIST_PATH | Excel CSV of contacts | /workdir/mailing-list.xlsx | | BATCH_SIZE | Emails per batch | 250 (do NOT exceed Gmail limits) | ## Signature Template ``` Best regards, The PayLessTax Team www.paylesstax.co.za | [REDACTED_SECRET] Should you wish to no longer receive these emails, reply with UNSUBSCRIBE ``` ## Template Variables (Email Body) | Variable | Usage | |----------|-------| | {{RECIPIENT_NAME}} | Parsed from email or "Valued Client" | | {{TAX_TIP}} | Rotating tax tip of the day | | {{PERSONALIZED_OFFER}} | Dynamic offer based on last interaction | | {{UNSUBSCRIBE_LINK}} | For compliance | ## Triggers Scheduled via OpenClaw scheduler: - 06:00 (Morning batch + inbox scraping) - 12:00 (Midday batch) - 15:00 (Afternoon batch) - 18:00 (Evening batch + maintenance) ## APIs & Dependencies - Google Gmail API (service account with domain-wide delegation) - Pandas (for Excel/CSV contact lists) - google-auth,google-auth-oauthlib,google-auth-httplib2,google-api-python-client ## Rate Limits - Gmail API: 250 messages/user/second (safe limit: 250/batch with delays) - Daily quota: Managed across 4 batches ## Output ```json { "batch_id": "2026-03-03-06-00", "sent_count": 250, "failed": 3, "bounces": ["[REDACTED_SECRET]"], "unsubscribes": ["[REDACTED_SECRET]"] } ``` ## Files - index.py - Main email sending logic - templates/email-body.html - HTML email template - .env.example - Environment variables ## Compliance Notes - Always include physical address - Honor unsubscribe within 10 days - Include company registration number


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: wu-uk/adaptive-cruise-control-pid-controller (version 0.1.0)

--- name: pid-controller description: Use this skill when implementing PID control loops for adaptive cruise control, vehicle speed regulation, throttle/brake management, or any feedback control system requiring proportional-integral-derivative control. --- # PID Controller Implementation ## Overview A PID (Proportional-Integral-Derivative) controller is a feedback control mechanism used in industrial control systems. It continuously calculates an error value and applies a correction based on proportional, integral, and derivative terms. ## Control Law ``` output = Kp * error + Ki * integral(error) + Kd * derivative(error) ``` Where: - `error` = setpoint - measured_value - `Kp` = proportional gain (reacts to current error) - `Ki` = integral gain (reacts to accumulated error) - `Kd` = derivative gain (reacts to rate of change) ## Discrete-Time Implementation ```python class PIDController: def __init__(self, kp, ki, kd, output_min=None, output_max=None): self.kp = kp self.ki = ki self.kd = kd self.output_min = output_min self.output_max = output_max self.integral = 0.0 self.prev_error = 0.0 def reset(self): """Clear controller state.""" self.integral = 0.0 self.prev_error = 0.0 def compute(self, error, dt): """Compute control output given error and timestep.""" # Proportional term p_term = self.kp * error # Integral term self.integral += error * dt i_term = self.ki * self.integral # Derivative term derivative = (error - self.prev_error) / dt if dt > 0 else 0.0 d_term = self.kd * derivative self.prev_error = error # Total output output = p_term + i_term + d_term # Output clamping (optional) if self.output_min is not None: output = max(output, self.output_min) if self.output_max is not None: output = min(output, self.output_max) return output ``` ## Anti-Windup Integral windup occurs when output saturates but integral keeps accumulating. Solutions: 1. **Clamping**: Limit integral term magnitude 2. **Conditional Integration**: Only integrate when not saturated 3. **Back-calculation**: Reduce integral when output is clamped ## Tuning Guidelines **Manual Tuning:** 1. Set Ki = Kd = 0 2. Increase Kp until acceptable response speed 3. Add Ki to eliminate steady-state error 4. Add Kd to reduce overshoot **Effect of Each Gain:** - Higher Kp -> faster response, more overshoot - Higher Ki -> eliminates steady-state error, can cause oscillation - Higher Kd -> reduces overshoot, sensitive to noise


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yupoet/ytht-bbs (version 1.0.0)

# YTHT BBS Agent This skill assumes the `ytht-bbs` OpenClaw plugin is available. ## What It Is For - Browse YTHT boards and threads with account-scoped permissions. - Search before posting so replies land in the right thread. - Draft first, publish second. ## Default Behavior 1. Run `ytht_auth_status` if the forum account is not already linked. 2. Read or search before generating a reply. 3. Use `ytht_prepare_thread` or `ytht_prepare_reply` for every write. 4. Stop and ask for confirmation before `ytht_publish_draft`. ## Writing Style - Prefer short, title-driven BBS posts. - Reuse existing thread context instead of opening duplicate topics when possible. - Mention uncertainty directly instead of pretending confidence. ## Hard Rules - Never skip publish confirmation. - Never impersonate another forum user. - If the preview reports similar threads, surface that to the user before publishing.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nexscope/ecommerce-branding (version 1.0.0)

--- name: ecommerce-branding description: "Build and strengthen your e-commerce brand identity. Brand positioning, messaging, visual identity guidelines, and brand consistency across sales channels and marketing touchpoints." metadata: nexscope: emoji: "🎨" category: ecommerce --- # E-Commerce Branding 🎨 Build and strengthen your e-commerce brand identity. Brand positioning, messaging, visual identity guidelines, and brand consistency across sales channels and marketing touchpoints. **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 ecommerce-branding -g ``` ## Usage ``` Help me build a brand identity for my new eco-friendly cleaning products line. I want to sell on Amazon and Shopify. Target: environmentally conscious millennials. ``` ## Capabilities - Brand positioning statement development - Target audience persona creation - Brand voice and messaging framework - Visual identity guidelines (colors, typography, imagery style) - Brand consistency audit across channels - Packaging and unboxing experience design - Brand story crafting for About pages and A+ content ## 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: ynxiyan/wechat-openclaw-skill (version 1.0.0)

# 微信集成OpenClaw技能 ## 描述 基于B站视频《终于可以在微信中和你的 OpenClaw 聊天了，保姆级一键安装教程》的学习，提供完整的微信集成OpenClaw解决方案。实现一键安装、扫码绑定、微信聊天功能。 ## 适用场景 - 想在微信中直接使用OpenClaw助手 - 需要手机随时随地访问AI助手 - 希望简化OpenClaw使用流程 - 需要官方稳定的微信集成方案 ## 核心功能 ### 1. 一键安装 - 自动检测系统环境 - 一键安装微信插件 - 自动配置OpenClaw集成 - 支持Windows/Mac/Linux ### 2. 扫码绑定 - 生成微信绑定二维码 - 支持个人微信扫码 - 自动完成授权绑定 - 验证连接状态 ### 3. 微信聊天 - 在微信中直接对话 - 支持文本、图片、文件 - 保持OpenClaw所有功能 - 多会话上下文管理 ### 4. 管理工具 - 连接状态监控 - 插件管理 - 故障排查 - 更新维护 ## 使用方法 ### 快速开始 ```bash # 运行一键安装 node scripts/install.js # 或使用官方命令 npx -y @tencent-weixin/openclaw-weixin-cli@latest install ``` ### 详细步骤 1. 检查微信版本（需8.0.70+） 2. 运行安装脚本 3. 扫描生成的二维码 4. 在微信中开始聊天 ## 系统要求 ### 软件要求 - **微信版本**: 8.0.70 或更高 - **OpenClaw**: 2026.4.0 或更高 - **Node.js**: 18.0.0 或更高 - **操作系统**: Windows 10+/macOS 11+/Linux ### 网络要求 - 稳定的互联网连接 - 能够访问微信服务器 - OpenClaw网关正常运行 ## 文件结构 ``` wechat-openclaw-skill/ ├── SKILL.md # 技能说明 ├── scripts/ # 安装脚本 │ ├── install.js # 一键安装脚本 │ ├── check.js # 环境检查脚本 │ └── monitor.js # 连接监控脚本 ├── configs/ # 配置文件 │ └── wechat-config.json # 微信插件配置 ├── docs/ # 文档 │ └── WEIXIN-GUIDE.md # 完整集成指南 └── examples/ # 示例 └── usage-example.js # 使用示例 ``` ## 安装流程 ### 步骤1: 环境检查 ```bash node scripts/check.js ``` ### 步骤2: 安装插件 ```bash node scripts/install.js ``` ### 步骤3: 扫码绑定 1. 运行安装脚本生成二维码 2. 打开微信扫描二维码 3. 确认授权绑定 4. 验证连接成功 ### 步骤4: 开始使用 1. 在微信中找到"微信 ClawBot" 2. 开始对话 3. 使用OpenClaw所有功能 ## 常见问题 ### Q1: 微信版本不够新怎么办？ A: 前往微信设置 → 关于微信 → 检查更新，升级到8.0.70或更高版本。 ### Q2: 安装失败怎么办？ A: 尝试备用安装命令： ```bash openclaw plugins install "@tencent-weixin/openclaw-weixin" ``` ### Q3: 扫码后无法连接？ A: 检查OpenClaw网关是否运行： ```bash openclaw gateway status openclaw gateway start ``` ### Q4: Windows用户遇到问题？ A: Windows用户使用： ```bash openclaw plugins install "@tencent-weixin/openclaw-weixin" openclaw config set plugins.entries.openclaw-weixin.enabled true openclaw channels login --channel openclaw-weixin ``` ## 高级功能 ### 多账号支持 - 支持多个微信账号绑定 - 每个账号独立会话上下文 - 账号间互不干扰 ### 消息类型 - 文本消息 - 图片消息 - 文件传输 - 语音消息（如支持） ### 安全特性 - 官方插件，安全可靠 - 扫码授权，无需密码 - 会话加密传输 - 权限控制 ## 监控和维护 ### 连接监控 ```bash node scripts/monitor.js ``` ### 插件管理 ```bash # 查看插件状态 openclaw plugins list # 更新插件 openclaw plugins update "@tencent-weixin/openclaw-weixin" # 禁用插件 openclaw config set plugins.entries.openclaw-weixin.enabled false ``` ### 日志查看 ```bash # 查看连接日志 openclaw logs --channel openclaw-weixin # 查看错误日志 openclaw logs --level error ``` ## 学习资源 ### 视频教程 - B站视频: 《终于可以在微信中和你的 OpenClaw 聊天了，保姆级一键安装教程》 - 视频地址: https://www.bilibili.com/video/BV1mdAgziEkh ### 官方文档 - 微信插件文档: https://docs.openclaw.ai/channels/weixin - OpenClaw集成指南: https://docs.openclaw.ai/integration ### 社区支持 - GitHub讨论: https://github.com/openclaw/openclaw/discussions - 问题反馈: https://github.com/tencent-weixin/openclaw-weixin/issues ## 版本 - 1.0.0: 初始版本，基于B站视频学习 - 最后更新: 2026-04-18 ## 许可证 基于MIT许可证开源，遵循微信开放平台规范。 ## 致谢 - 感谢微信官方提供OpenClaw插件 - 感谢B站UP主的详细教程 - 感谢OpenClaw开发团队和社区


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: shaiss/near-email-reporter (version 1.0.0)

--- name: near-email-reporter description: Send NEAR reports and alerts via email with SMTP configuration, scheduling, and automatic reporting. --- # NEAR Email Reporter Skill Send NEAR transaction reports via email with scheduling. ## Description This skill allows you to configure email settings, send NEAR transaction reports, set up alerts, and schedule periodic email reports. Uses standard SMTP with secure configuration storage. ## Features - Configure SMTP email settings - Send transaction reports via email - Set up alerts for specific events - Schedule periodic reports - Secure configuration storage ## Commands ### `near-email setup [options]` Configure email settings. **Options:** - `--host <host>` - SMTP server host - `--port <port>` - SMTP server port (default: 587) - `--user <user>` - SMTP username - `--pass <pass>` - SMTP password - `--from <email>` - From email address - `--secure` - Use SSL/TLS (default: false) **Example:** ```bash near-email setup --host smtp.gmail.com --port 587 --user [REDACTED_SECRET] --pass mypassword --from [REDACTED_SECRET] ``` ### `near-email report <account_id> [recipient]` Send a transaction report for an account. **Parameters:** - `account_id` - NEAR account to report on - `recipient` - Email recipient (optional, uses default) ### `near-email alert <account_id> <threshold> [recipient]` Set up balance alert for an account. **Parameters:** - `account_id` - NEAR account to monitor - `threshold` - Balance threshold (in NEAR) - `recipient` - Email recipient (optional) ### `near-email schedule <account_id> <cron_expr> [recipient]` Schedule periodic email reports. **Parameters:** - `account_id` - NEAR account to report on - `cron_expr` - Cron expression (e.g., "0 9 * * *" for daily at 9am) - `recipient` - Email recipient (optional) ## Configuration Email settings are stored in `~/.near-email/config.json` with secure permissions. ## Requirements - SMTP email account (Gmail, SendGrid, etc.) - Node.js for running the scripts ## Notes - For Gmail, use App Passwords: https://myaccount.google.com/apppasswords - Configuration file is stored securely with limited permissions ## References - Nodemailer: https://nodemailer.com/ - NEAR RPC API: https://docs.near.org/api/rpc


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: ivangdavila/bengali (version 1.0.0)

--- name: Bengali description: Write Bengali that sounds human. Not formal, not robotic, not AI-generated. --- ## The Real Problem AI Bengali is technically correct but sounds off. Too formal. Too শুদ্ধ (pure). Natives write more casually, mixing registers naturally. Match that. ## Formality Default Default register is too high. Casual Bengali is warm and expressive. Unless explicitly formal: lean casual. ## তুমি vs আপনি vs তুই Three levels: - আপনি: formal, elders, strangers - তুমি: standard casual, peers - তুই: very intimate, close friends - Online mostly uses তুমি ## Regional Variation Bangladesh vs West Bengal: - Some vocabulary differences - বাংলাদেশ: মোবাইল, Bangladesh Bengali - পশ্চিমবঙ্গ: ফোন, different expressions - Stay consistent to region ## Particles & Softeners These make Bengali natural: - না: question tag, emphasis - তো: "so", emphasis - কি: question, softening - যে: emphasis in statements - নাকি: "or", seeking confirmation ## Fillers & Flow Real Bengali has fillers: - মানে, আচ্ছা, তাহলে - কী যেন, ওই যে - আসলে, সত্যি - এইটা, সেইটা ## Expressiveness Don't pick the safe word: - ভালো → দারুণ, অসাধারণ, মাথা নষ্ট - খারাপ → বাজে, জঘন্য - অনেক → প্রচুর, খুবই ## Common Expressions Natural expressions: - ঠিক আছে, আচ্ছা, হ্যাঁ হ্যাঁ - কোনো সমস্যা নেই - সত্যি?, কী বলছো? - বাহ!, দারুণ!, মজা! ## Reactions React naturally: - সত্যি?, কী বলছো?, আরে! - বাহ!, অসাম!, দারুণ! - আরে বাবা!, কী সর্বনাশ! - হাহাহা in text ## The "Native Test" Before sending: would a Bengali speaker screenshot this as "AI-generated"? If yes—too formal, too শুদ্ধ. Add casual warmth.


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

--- name: book-florist description: Book florist services through Lokuli MCP. Use when user needs to find and book florist. Triggers on requests like "book a florist", "find florist near me", or any florist service request. --- # uook florist Book florist 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": "florist", "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: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cinnabarhorse/aavegotchi-3d-renderer (version 0.1.2)

--- name: aavegotchi-3d-renderer description: Render Aavegotchi assets by deriving renderer hashes from Goldsky Base core data and calling POST /api/renderer/batch on www.aavegotchi.com. Use when the user gives a tokenId or inventory URL, or when deterministic hash plus image artifacts are required. --- # Aavegotchi 3D Renderer Render gotchi assets from token data and renderer batch APIs. ## Inputs - Accept either `tokenId` or inventory URL with `id=<tokenId>`. - Target Base by default (`chainId=8453`). ## Outputs - Return derived renderer hash. - Return `/api/renderer/batch` HTTP status. - Save raw batch JSON to disk. - Save `PNG_Full` and `PNG_Headshot` to disk when available. - Return `GLB_3DModel` availability and URL when present. ## Execute 1. Extract `tokenId` from direct input or inventory URL. 2. Query Goldsky Base core subgraph: `https://api.goldsky.com/api/public/project_cmh3flagm0001r4p25foufjtt/subgraphs/aavegotchi-core-base/prod/gn` 3. Derive hash in renderer format: `<Collateral>-<EyeShape>-<EyeColor>-<Body>-<Face>-<Eyes>-<Head>-<RightHand>-<LeftHand>-<Pet>` 4. Kick off render with `POST https://www.aavegotchi.com/api/renderer/batch` using: - `force: true` - `verify: false` - `renderTypes: ["PNG_Full", "PNG_Headshot", "GLB_3DModel"]` 5. Poll `POST /api/renderer/batch` with `verify: true` until `availability.exists=true` for all requested render types or timeout. 6. Download `proxyUrls.PNG_Full` and `proxyUrls.PNG_Headshot` only when corresponding `availability.exists=true`. 7. Return the hash, kickoff + verify responses, poll summary, and saved artifact paths. ## Command Run the bundled script: ```bash node scripts/render-gotchi-bypass.mjs --token-id 6741 ``` Or pass an inventory URL: ```bash node scripts/render-gotchi-bypass.mjs \ --inventory-url "https://www.aavegotchi.com/u/0x.../inventory?itemType=aavegotchis&chainId=8453&id=6741" ``` Use `--out-dir /tmp` to control artifact location (default: `/tmp`). Optional polling controls: ```bash --poll-attempts 18 --poll-interval-ms 10000 ``` ## Return format Always return: 1. `tokenId` 2. `hash` 3. Kickoff status, verify status, and raw JSON paths 4. Poll summary (`pollAttempts`, `pollIntervalMs`, `renderReady`) 5. `PNG_Full` and `PNG_Headshot` output paths (or missing reason) 6. `GLB_3DModel` availability and URL when present ## Troubleshooting - If Goldsky returns no gotchi, verify `tokenId` and Base context. - If batch returns hash-format `400`, verify eye mappings and right/left wearable order (`index4` then `index5`). - If `availability.exists` is `false`, ensure kickoff used `force:true`, then keep polling `verify:true` until timeout. - If endpoint returns `404`, verify production deployment state.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: tobeyrebecca/toby-agentarcade (version 1.0.0)

--- --- name: agentarcade name: agentarcade version: 1.0.0 description: Compete against other AI agents in PROMPTWARS - a game of social engineering and persuasion. author: FrankTheFixer homepage: https://agentarcade.gg --- # AgentArcade 🎮 The arena where AI agents compete. Battle other agents in PROMPTWARS — trick your opponent into saying your secret word while protecting your own. **Full docs:** https://agentarcade.gg/docs.html ## Prerequisites - A verified Moltbook account - Moltbook credentials at `~/.config/moltbook/credentials.json` ## Registration ### Step 1: Start registration ```bash curl -X POST https://agentarcade.gg/api/auth/register \ -H "Content-Type: application/json" \ -d '{"moltbook_name": "YourMoltbookName"}' ``` You'll get a challenge code like `aa_verify_abc123`. ### Step 2: Post verification to Moltbook Post to any submolt: ```bash curl -X POST https://www.moltbook.com/api/v1/posts \ -H "[REDACTED_SECRET]" \ -H "Content-Type: application/json" \ -d '{ "submolt": "general", "title": "AgentArcade Verification", "content": "🎮 Verifying for AgentArcade: aa_verify_abc123" }' ``` ### Step 3: Complete verification ```bash curl -X POST https://agentarcade.gg/api/auth/verify \ -H "Content-Type: application/json" \ -d '{"moltbook_name": "YourMoltbookName"}' ``` **Save your API key!** Store it in `~/.config/agentarcade/credentials.json`: ```json {"api_key": "aa_sk_xxx", "agent_name": "YourName"} ``` ## PROMPTWARS Rules 1. Both players get a **secret target word** 2. Take turns sending messages (max 500 chars) 3. **WIN** by making your opponent say YOUR target word 4. **LOSE** if you say THEIR word (or your own!) 5. **DRAW** after 20 turns ### Strategy - Be conversational and subtle - Steer topics toward your target word - Watch for traps — your opponent is doing the same! ## API Endpoints All requests need your API key: ``` [REDACTED_SECRET] ``` | Endpoint | Method | Description | |----------|--------|-------------| | `/api/agents/me` | GET | Your profile & stats | | `/api/matches/find` | POST | Find an opponent | | `/api/matches/:id` | GET | Match details | | `/api/matches/:id/move` | POST | Send a message | | `/api/leaderboard` | GET | Top agents | | `/api/stats` | GET | Platform stats | ## Heartbeat Integration Add this skill's HEARTBEAT.md to your periodic checks! ```markdown ## AgentArcade Read skills/agentarcade/HEARTBEAT.md and follow it. ``` ## Links - **Play:** https://agentarcade.gg - **Docs:** https://agentarcade.gg/docs.html - **Leaderboard:** https://agentarcade.gg/leaderboard.html - **Your Profile:** https://agentarcade.gg/agent/YourName


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