OpenClaw/clawhub-security-signals huggingface dataset:
Skill: mcbaivn/youtube-content-analyzer (version 1.0.0)

--- name: youtube-content-analyzer description: Phân tích nội dung video YouTube từ file SRT/VTT/TXT hoặc URL trực tiếp. Tóm tắt nội dung, extract key points, phân tích chủ đề chính, tạo báo cáo. Dùng khi user yêu cầu "Tóm tắt video X", "Analyze content từ SRT", "Key points từ [URL]", "Đọc nội dung video mà không cần xem", hoặc cần hiểu nhanh nội dung hàng loạt video. --- # 🤖 YouTube Content Analyzer Đọc phụ đề → tóm tắt nội dung, key points, phân tích chủ đề. Không cần xem video. ## Cài đặt ### Cách 1 — Tải skill thẳng từ GitHub (khuyến nghị) ```powershell # Windows $skillDir = "$env:USERPROFILE\.agents\skills\youtube-content-analyzer" New-Item -ItemType Directory -Force $skillDir | Out-Null Invoke-WebRequest -Uri "https://raw.githubusercontent.com/mcbaivn/openclaw-skills-mcbai/main/skills/youtube/youtube-content-analyzer/SKILL.md" -OutFile "$skillDir\SKILL.md" New-Item -ItemType Directory -Force "$skillDir\scripts" | Out-Null Invoke-WebRequest -Uri "https://raw.githubusercontent.com/mcbaivn/openclaw-skills-mcbai/main/skills/youtube/youtube-content-analyzer/scripts/analyze_content.py" -OutFile "$skillDir\scripts\analyze_content.py" ``` ```bash # macOS / Linux mkdir -p ~/.agents/skills/youtube-content-analyzer/scripts curl -o ~/.agents/skills/youtube-content-analyzer/SKILL.md \ https://raw.githubusercontent.com/mcbaivn/openclaw-skills-mcbai/main/skills/youtube/youtube-content-analyzer/SKILL.md curl -o ~/.agents/skills/youtube-content-analyzer/scripts/analyze_content.py \ https://raw.githubusercontent.com/mcbaivn/openclaw-skills-mcbai/main/skills/youtube/youtube-content-analyzer/scripts/analyze_content.py ``` ### Cách 2 — Clone toàn bộ repo ```powershell # Windows git clone https://github.com/mcbaivn/openclaw-skills-mcbai.git Copy-Item -Recurse openclaw-skills-mcbai\skills\youtube\youtube-content-analyzer $env:USERPROFILE\.agents\skills\ ``` ```bash # macOS / Linux git clone https://github.com/mcbaivn/openclaw-skills-mcbai.git cp -r openclaw-skills-mcbai/skills/youtube/youtube-content-analyzer ~/.agents/skills/ ``` ## Workflow **Cách 1 - Từ file SRT/TXT có sẵn:** ``` python scripts/analyze_content.py --file path/to/subtitle.srt ``` **Cách 2 - Từ URL (tự tải subtitle rồi phân tích):** ``` python scripts/analyze_content.py --url https://youtu.be/xxxx [--lang vi] ``` **Cách 3 - Phân tích hàng loạt:** ``` python scripts/analyze_content.py --folder Youtube_Subtitles/ChannelName/ ``` ## Output ``` Youtube_Analysis/ └── [Video_Title]_analysis_DD_MM_YYYY.txt ``` **Mỗi file analysis gồm:** - 📝 **Tóm tắt** (3-5 câu) - 🔑 **Key Points** (bullet list) - 🏷️ **Chủ đề chính** (tags) - 💬 **Quotes đáng chú ý** - 📊 **Thống kê**: độ dài, ngôn ngữ, mật độ thông tin ## Lưu ý - Với video dài (>30 phút), script chia nhỏ thành chunks trước khi phân tích. - Kết hợp với `youtube-subtitle-extractor` để có pipeline đầy đủ.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: tianheihei002/material-generator (version 1.0.0)

# UE材质生成器技能包 ## 部署地址（最新） ``` App: https://k2lucelsen19.space.minimaxi.com 示例JSON（血迹后处理材质）: https://k2lucelsen19.space.minimaxi.com/BP_BloodPostProcess.json ``` ## 项目位置 `/workspace/material-generator/` ## 概述 UE材质生成器：输入自然语言描述 → 生成UE材质节点图（支持TextureSample、Multiply、Lerp、Constant、TexCoord、MaterialOutput等节点）。 ## 核心文件 - `src/App.tsx` — 主界面（输入框/历史/修改面板） - `src/MaterialCanvas.tsx` — ReactFlow画布（拖拽节点） - `src/BpNode.tsx` — 材质节点渲染（官方UE颜色） - `src/Sidebar.tsx` — 选中节点信息/修改 - `src/api.ts` — AI生成逻辑 + autoLayout - `src/types.ts` — MaterialGraph/MaterialNode/MaterialPin类型 - `public/` — 静态JSON示例文件 ## API配置 - Base: `https://api.minimaxi.com/v1` - Model: `MiniMax-M2.7` - Key: `[REDACTED_SECRET]` ## 节点颜色（UE官方标准） - texture_sample: header=#A855F7 紫色 - math: header=#00D4FF 青色 - lerp: header=#FBBF24 黄色 - param: header=#F97316 橙色 - constant: header=#22C55E 绿色 - output: header=#16A34A 深绿 - texcoord: header=#3B82F6 蓝色 ## Pin颜色 - float: #22C55E - float2: #00D4FF - float3: #FBBF24 - float4: #F97316 - sampler: #A855F7 ## 常见问题 - 构建失败：检查tsconfig.json是否包含必要配置 - Sidebar.tsx中JSX字符串必须用双引号，避免嵌套引号问题 - 删除残留的BlueprintCanvas.tsx（从蓝图生成器复制时会带过来）


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: xueyetianya/translator-pro-test (version 3.0.0)

--- name: "translator-pro-test" version: "3.0.0" description: "Test translation quality with built-in dictionaries and comparison tools. Use when evaluating translations." author: "BytesAgain" homepage: "https://bytesagain.com" --- # translator-pro-test Test translation quality with built-in dictionaries and comparison tools. Use when evaluating translations. ## Commands ### `test` ```bash scripts/script.sh test <text from to> ``` ### `dict` ```bash scripts/script.sh dict <word> ``` ### `compare` ```bash scripts/script.sh compare <text l1 l2> ``` ### `glossary` ```bash scripts/script.sh glossary <term> ``` ### `quality` ```bash scripts/script.sh quality <original translated> ``` ### `batch` ```bash scripts/script.sh batch <file to> ``` ## Data Storage Data stored in `~/.local/share/translator-pro-test/`. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zero2ai-hub/skill-dropshipping-product-launcher (version 1.0.0)

# skill-dropshipping-product-launcher **One command: CJ Dropshipping product → WooCommerce draft listing.** Fetches product data from CJ, downloads images, uploads to WordPress media library, calculates margin, and creates a WooCommerce draft product — with variants if CJ has them. --- ## Inputs | Argument | Required | Description | |---|---|---| | `--product` / `-p` | ✅ | CJ Dropshipping product ID (e.g. `CJA123456789`) | | `--price` | ✅ | Your sell price in **AED** | | `--category` / `-c` | ❌ | Category name or WooCommerce category ID | | `--dry-run` | ❌ | Preview without creating anything in WooCommerce | --- ## Outputs ``` ✅ Product created! WooCommerce ID : 4821 Margin : 42.3% Admin URL : https://tech1mart.com/wp-admin/post.php?post=4821&action=edit Product URL : https://tech1mart.com/?p=4821 ``` Machine-readable JSON block at end of stdout (key: `__RESULT__`): ```json { "wooProductId": 4821, "margin": "42.3", "productUrl": "https://tech1mart.com/?p=4821", "adminUrl": "https://tech1mart.com/wp-admin/post.php?post=4821&action=edit", "title": "Product Name", "cjProductId": "CJA123456789", "sellPriceAED": 149.99, "cjPriceUSD": 22.5 } ``` --- ## Auth Config - **CJ API**: `~/cj-api.json` — fields: `apiKey`, `accessToken`, `tokenExpiry` - **WooCommerce**: `~/woo-api.json` — fields: `url`, `consumerKey`, `consumerSecret` Tokens are refreshed automatically. --- ## Pipeline 1. Fetch product from CJ (`/product/query` + `/product/variant/query`) 2. Download images → `/tmp/product-images/<product_id>/` 3. Upload images → WooCommerce media library (`/wp-json/wp/v2/media`) 4. Calculate margin: `((sellAED - cjUSD × 3.67) / sellAED × 100)` — warns if < 30% 5. Create WooCommerce draft product (`/wp-json/wc/v3/products`) with: - Title, description, images - `regular_price` (AED) - `type: variable` + variations if CJ has multiple variants - `meta_data: _cj_product_id` 6. Output: product ID, margin %, admin + storefront URLs --- ## Usage Examples ```bash # Basic launch node scripts/launch.js --product CJA123456789 --price 149.99 # With category node scripts/launch.js --product CJA123456789 --price 149.99 --category Electronics # Dry run (preview only, no WooCommerce writes) node scripts/launch.js --product CJA123456789 --price 149.99 --dry-run # Check CJ product data only node scripts/cj-fetch.js CJA123456789 ``` --- ## Dependencies ```bash cd scripts npm install axios form-data ``` Or from skill root: ```bash npm install ``` --- ## Files ``` skill-dropshipping-product-launcher/ ├── SKILL.md ← this file ├── package.json └── scripts/ ├── launch.js ← main entry point ├── cj-fetch.js ← CJ API fetcher + token refresh └── woo-create.js ← WooCommerce uploader + product creator ``` --- ## Margin Formula ```js const cjPriceAED = cjPriceUSD * 3.67; const margin = ((sellPriceAED - cjPriceAED) / sellPriceAED * 100).toFixed(1); ``` ⚠️ Warning shown if margin < 30%.


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: snow-seamless/finance-paper-daily (version 1.0.0)

--- name: finance-paper-daily description: 每日金融学术论文自动抓取并生成 Excel 报告。从 arXiv (q-fin)、Semantic Scholar、OpenAlex、Google Scholar 四个来源获取最新金融领域论文（量化金融、资产定价、风险管理、算法交易、FinTech等），整理成格式化 Excel 文件保存到用户桌面，文件名为 YYYY-MM-DD_finance_papers.xlsx。当用户说"抓取今日论文"、"更新论文报告"、"获取金融论文"、"生成论文 Excel"时触发。 --- # Finance Paper Daily 每日金融学术论文抓取 → 桌面 Excel 报告。 ## 数据源 | 来源 | API | 覆盖方向 | |------|-----|----------| | arXiv | 官方免费 | q-fin 全分类（量化金融） | | Semantic Scholar | 官方免费 | 金融关键词全文搜索 | | OpenAlex | 官方免费（无需 key） | Economics/Finance 概念 | | Google Scholar | scholarly 库（非官方） | 广泛覆盖，尽力而为 | ## 使用方式 运行脚本： ```bash pip3 install openpyxl scholarly --break-system-packages -q python3 scripts/fetch_papers.py ``` ## 输出 - 路径：`~/Desktop/YYYY-MM-DD_finance_papers.xlsx` - Sheet1「每日论文」：按日期倒序，含标题/作者/摘要/来源/链接，颜色区分来源 - Sheet2「来源统计」：各来源论文数量汇总 ## 注意 - 首次运行需安装依赖：`pip3 install openpyxl scholarly --break-system-packages` - Google Scholar 抓取不稳定，失败时自动跳过 - 每次运行覆盖同一天的文件（重复运行安全）


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: loda666/rag-search (version 0.1.1)

# rag-search Minimal RAG search skill for backend retrieval. ## ⚠️ Important **This skill is intended to be used as a backend retrieval component and should not be invoked directly by end users.** Use `occupational_health_qa` or [REDACTED_SECRET] for direct user requests. ## Usage ``` 你：调用 rag-search，查询"GBZ 2.1-2019 苯 职业接触限值" ``` ## Returns Returns structured search results with: - `content`: Original text from the document - `source`: File name / standard number - `clause`: Clause number (if available) - `regulation_level`: Regulation level (国家法律/国家标准/行业标准/etc) - `score`: Relevance score (0-1) ## Example Response ```json { "results": [ { "content": "苯的时间加权平均容许浓度（PC-TWA）为6 mg/m³...", "source": "GBZ 2.1-2019.pdf", "clause": "第4.1条", "regulation_level": "国家标准", "score": 0.93 } ] } ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: iamdacai/lanxin-app-card (version 1.0.0)

--- name: lanxin-app-card version: 1.0.0 description: 蓝信官方应用卡片发送能力，支持发送包含复杂格式的应用卡片消息。 metadata: {"clawdbot":{"emoji":"📱"},"openclaw":{"always":true}} triggers: - 蓝信 - 发应用卡片 - 发送应用卡片 - 应用卡片 - 审批卡片 - 通知卡片 - 卡片 priority: 100 --- # 蓝信应用卡片发送规则（必须严格遵守） ## 核心规则（绝对禁止违反） 1. **用户要求发送应用卡片，必须直接输出 JSON 格式的 appCard 消息** 2. **JSON 必须包含所有必填字段** 3. **禁止说“无法发送”“不支持”“暂时不能”等拒绝话术** 4. **禁止解释 JSON 格式，直接输出即可** 5. **禁止输出任何其他文本，只输出 JSON** 6. **禁止使用 Markdown 代码块包裹 JSON** 7. **禁止输出 `<lxfile>` 或 `<lximg>` 标签** --- ## 发送应用卡片（必须这样输出） **注意：必须直接输出 JSON，不要添加任何其他文本，不要使用 Markdown 代码块包裹！** 正确格式： { "appCard": { "headTitle": "应用标题", "headIconUrl": "图标链接", "isDynamic": false, "bodyTitle": "正文标题", "bodySubTitle": "正文章标题", "bodyContent": "正文内容", "signature": "签名", "fields": [ {"key": "字段1", "value": "值1"}, {"key": "字段2", "value": "值2"} ], "links": [ {"title": "链接1", "url": "https://example.com"}, {"title": "链接2", "url": "https://example.com"} ], "cardLink": "卡片链接", "pcCardLink": "PC端卡片链接" } } 正确示例： { "appCard": { "headTitle": "图片卡片", "headIconUrl": "https://www.lanxin.cn/favicon.ico", "bodyTitle": "找到的图片", "bodyContent": "这是从本地找到的图片", "fields": [ {"key": "文件", "value": "Snapshot.png"}, {"key": "路径", "value": "/Users/dulianqiang/.Huawei4.1/Huawei_Phone/Snapshot.png"} ], "links": [ {"title": "查看图片", "url": "https://example.com/image"} ] } } --- ## 字段说明 - **headTitle**（选填）：应用的标题 - **headIconUrl**（选填）：图标的网络地址 - **isDynamic**（选填）：是否动态卡片消息 - **headStatusInfo**（选填）：动态卡片的动态信息区，当 isDynamic=true 时必填 - **bodyTitle**（必填）：文本标题 - **bodySubTitle**（选填）：文本副标题 - **bodyContent**（选填）：松散内容 - **signature**（选填）：署名字段 - **fields**（选填）：key/value 字段对，上限 10 对 - **links**（选填）：链接数组，最多 3 对 - **cardLink**（选填）：本条消息的跳转地址 - **pcCardLink**（选填）：PC 端跳转地址 --- ## 支持的格式 可以使用 div 标签的 style 属性对文本内容进行格式控制，支持控制的格式有颜色（color）、字体大小（font-size），位置（text-align），首行缩进（text-indent）。 示例： ```html <div style="color: brown; text-align: left;font-size:xx-large"> 第一个div 靠左 超大 </div> ``` --- ## 严禁出现的错误行为 ❌ 禁止：缺少必填字段 ❌ 禁止：格式错误的 JSON ❌ 禁止：解释“这是 JSON”“系统会解析” ❌ 禁止：拒绝发送 ❌ 禁止：只输出文字内容，不输出 JSON ❌ 禁止：输出任何其他文本，只输出 JSON ❌ 禁止：使用 Markdown 代码块包裹 JSON ❌ 禁止：输出 `<lxfile>` 或 `<lximg>` 标签 ❌ 禁止：输出 Markdown 格式的文本 ❌ 禁止：在 JSON 前后添加任何文字 ## 你的行为准则 用户让你发送应用卡片 → **直接输出干净的 JSON** → 不要多余描述 → 不要格式包裹 → 完成。

path: index.js
content: /**
 * Lanxin app card skill - handles app card sending functionality
 */

// This file serves as an entry point for the lanxin-app-card skill
// It doesn't need any specific functionality since the skill is primarily defined by the SKILL.md file

module.exports = {
  name: 'lanxin-app-card',
  description: '蓝信应用卡片发送技能',
  version: '1.0.0'
};


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: rigeneproject/smfoi-kernel (version 1.0.4)

\--- name: SMFOI-KERNEL version: 0.2.2 description: Minimal Fundamental Orientation Schema for Intelligence. A local, auditable orientation layer. triggers: &#x20; - every\_turn maintainer: Roberto De Biase license: MIT \--- \# SMFOI-KERNEL v0.2.2 \## 🎯 Executive Summary The SMFOI-KERNEL provides a standardized 5-step cycle to ensure agents maintain environmental awareness and adhere to safety constraints. \## 🔒 Security \& Scope Boundaries To prevent unintended behavior, this version enforces strict limits: 1\. \*\*No System Access:\*\* The agent is prohibited from reading OS logs, shell history, or environment variables. "Push Detection" is limited to strings provided within the active conversation context. 2\. \*\*Read-Only Environment:\*\* The agent may observe local workspace files but cannot modify system configurations. 3\. \*\*Mandatory Approval:\*\* Level 3 (Recursion) proposals are \*\*non-executable\*\*. They serve only as logged suggestions that require manual file editing by the human operator. \--- \## 🏛️ The 5-Step Orientation Cycle 1\. \*\*Self-Location:\*\* Identify current agent type and workspace limits. 2\. \*\*Constraint Mapping:\*\* List active safety boundaries (e.g., "Do not delete files"). 3\. \*\*Signal Detection:\*\* Identify user requests or task-specific data changes. 4\. \*\*Action Stacking:\*\* Prioritize Safety (Level 0) over Task Execution (Level 1). 5\. \*\*Logging:\*\* Record the cycle outcome to `./memory/kernel/state.md`. \--- \## 🚦 Operational Levels | Level | Name | Description | Authority | | :--- | :--- | :--- | :--- | | \*\*0\*\* | \*\*Integrity\*\* | Maintain core safety. | \*\*Internal\*\* | | \*\*1\*\* | \*\*Exploration\*\* | Workspace analysis. | \*\*Auto\*\* | | \*\*2\*\* | \*\*Expansion\*\* | Proposing new local files. | \*\*Operator Review\*\* | | \*\*3\*\* | \*\*Recursion\*\* | Protocol optimization ideas. | \*\*HUMAN ONLY\*\* | \--- \*\*SMFOI-KERNEL\*\* — \*Structured orientation, human-verified evolution.\*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jimadara/intelligent-diagnosis-skill-test (version 1.0.1)

--- name: domain-test-skill display_name: 域名测试 version: "0.1.0" description: | 域名测试 metadata: { "openclaw": { "emoji": "📊" } } triggers: - intent: 域名测试 keywords: - 域名测试 examples: | 帮我用商家蛋蛋测试这个域名 --- --- # ✅ 固定流程（按顺序执行，任一步失败立刻返回错误） ## Step 1：解析商家名称并获取商家ID baseUrl: https://merchant-lego.corp.kuaishou.com 接口： POST https://merchant-lego.corp.kuaishou.com/gateway/crm/seller/manager/querySellerSearchResult 请求体： ```json { "username": "${username}", "sellerName": "${sellerName}" } ``` 其中： - `${sellerName}` 从用户问题中解析得到商家名称（例如用户的问题是“请生成小米官方直播间的诊断报告”，sellerName则是“小米官方直播间”） - `${username}` 从本地凭证中获取（读取 `~/.openclaw/username` 配置文件里的用户名），若未配置则直接终止下面的执行步骤，直接输出“抱歉，userName认证报错!” 正确的请求体格式可参考下面： ```json { "username": "userName", "sellerName": "sellerName" } ``` 响应结构（示例）： ```json { "status": 200, "statusText": "OK", "headers": { "Content-Type": "application/json", "Access-Control-Allow-Origin": "*" }, "body": [ "1001234567", "1001234568", "1001234569" ] } ``` ## 结果处理 - 直接把http接口返回的结果返回给用户


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: shipstatic-com/shipstatic (version 0.7.20)

--- name: ship description: Static hosting via ShipStatic. Use when the user wants to deploy a website, upload files, manage deployments, set up domains, or publish static files to shipstatic.com. metadata: openclaw: requires: env: - SHIP_API_KEY bins: - ship primaryEnv: SHIP_API_KEY emoji: "🚀" homepage: https://github.com/shipstatic/ship install: - kind: node package: "@shipstatic/ship" bins: [ship] --- ## Install Requires Node.js >= 20. ```bash npm install -g @shipstatic/ship ``` ## Authenticate ```bash ship config ``` Enter your API key when prompted. Get one at https://my.shipstatic.com/settings Alternative: set the `SHIP_API_KEY` environment variable or pass `--api-key` per command. ## Workflow 1 — Deploy ```bash ship ./dist ship ./dist --label production --label v1.0 ship ./dist --json # Returns {"deployment": "<id>", "url": "https://..."} ``` ## Workflow 2 — Reserve a Domain ```bash # Pre-flight check ship domains validate www.example.com # Reserve (no deployment linked yet) ship domains set www.example.com # Or reserve an internal subdomain (instant, no DNS) ship domains set my-site ``` Internal domains (`my-site.shipstatic.com`) are free and instant. Custom domains require DNS configuration — the CLI prints the required records. **Apex domains are not supported.** Always use a subdomain: `www.example.com`, not `example.com`. ## Workflow 3 — Link Domain to Deployment ```bash # Link domain to a deployment ship domains set www.example.com <deployment-id> # Switch to a different deployment (instant rollback) ship domains set www.example.com <other-deployment-id> # For custom domains: verify DNS after configuring records ship domains verify www.example.com ``` ## Reference ```bash # Deployments ship deployments list ship deployments get <id> ship deployments set <id> --label production ship deployments remove <id> # Domains ship domains list ship domains get <name> ship domains validate <name> ship domains verify <name> ship domains remove <name> # Account ship whoami ship ping ``` Use `--json` on any command for machine-readable output.


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: vswarm-ai/verdictswarm (version 2.0.0)

--- name: verdictswarm description: "Fight AI with AI. 6 adversarial AI agents debate crypto token risk before your agent trades. Rug-pull detection, security audits, consensus scoring via MCP." triggers: - scan token - analyze crypto - is this token safe - token risk - crypto analysis - should I buy this token - check this token - rug pull check requires: - network: "https://api.vswarm.io" --- # VerdictSwarm — Multi-Agent Token Intelligence **Get a second, third, fourth, fifth, and sixth opinion on any crypto token.** Six specialized AI agents independently analyze your token from different angles, then debate their findings across multiple rounds before reaching consensus. You see the full analysis and any disagreements. > "What do you think of this token?" → 6 agents analyze → Consensus reached → You decide **Free tier available.** 10 quick scans per day, no API key needed. ## How It Works Each agent specializes in a different aspect of token analysis: | Agent | Focus Area | |-------|-----------| | Security Bot | Smart contract permissions, mint/freeze authority, honeypot detection | | Tokenomics Bot | Supply mechanics, holder concentration, distribution | | Social Bot | Community signals, social presence, engagement patterns | | Technical Bot | On-chain metrics, liquidity analysis, trading patterns | | Macro Bot | Market context, comparative analysis, sector trends | | Devil's Advocate | Challenges every verdict, finds what others missed | ## MCP Tools Install via MCP for agent integration: ```bash pip install verdictswarm-mcp ``` | Tool | Description | |------|-------------| | `scan_token` | Full 6-agent consensus risk scan | | `get_quick_score` | Fast cached score (0-100) for pre-trade screening | | `check_rug_risk` | Rug-pull focused security check (SAFE/CAUTION/DANGER) | | `get_token_report` | Shareable markdown report | | `get_pricing` | View pricing and Solana payment details | | `verify_payment` | Verify USDC payment on Solana | ## Quick Start (API) ```bash curl -s "https://api.vswarm.io/api/scan/quick" \ -H "Content-Type: application/json" \ -d '{"address": [REDACTED_SECRET], "chain": "solana"}' ``` ## Scoring Guide - 80-100: LOW risk (Grade A) - 70-79: LOW-MEDIUM (Grade B) - 60-69: MEDIUM (Grade C) - 40-59: HIGH (Grade D) - 0-39: CRITICAL (Grade F) ## Pricing | Tier | Cost | Details | |------|------|---------| | **Free** | $0 | 10 quick scans/day | | **Quick Scan** | 0.02 USDC | Cached score + metadata | | **Rug Check** | 0.05 USDC | Security-focused verdict | | **Full Scan** | 0.10 USDC | All 6 agents, full debate | Pay per scan with USDC on Solana, or use a free API key from vswarm.io. ## Supported Chains Solana, Ethereum, Base, BSC ## Agent Instructions When the user asks to analyze or check a crypto token, use the MCP tools (preferred) or call the API directly. Present the verdict score, risk level, and consensus summary. If agents disagreed, highlight the differences. Include the report URL for the full breakdown.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal:  | SkillSpector: clean (LOW)
Skill: simonlei/tosr-test-skill-1774319824 (version 0.1.0)

# TOSR Test Skill > 0.1.0 — A test skill for TOSR integration testing. ## Description This skill is created by TOSR automated integration tests to verify the clawhub publish/update/delete workflow. It exercises the full skill lifecycle: creation, version update, and deletion via the clawhub REST API. ## Features - Validates skill creation via POST /api/v1/skills - Validates skill update by publishing a new version - Validates skill deletion via DELETE /api/v1/skills/{slug} - Uses unique timestamped slugs to avoid conflicts between test runs ## Usage This skill is for testing purposes only and will be deleted after the test completes. ## Version 0.1.0


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: chenghaifeng08-creator/agent-autonomy-kit-automaton (version 1.0.2)

--- name: agent-autonomy-kit-automaton slug: agent-autonomy-kit-automaton version: 1.0.2 description: Stop waiting for prompts. Keep working. - Automaton Edition author: Automaton homepage: https://github.com/openclaw/skills/agent-autonomy-kit metadata: openclaw: emoji: "🚀" category: productivity pricing: basic: "49 USDC" pro: "99 USDC" --- # Agent Autonomy Kit Transform your agent from reactive to proactive. --- ## 💰 付费服务 **Automaton 架构咨询 & 定制**: | 服务 | 价格 | 交付 | |------|------|------| | Automaton 架构搭建 | ¥3000/次 | 完整配置 + 培训 | | 自定义心跳模式 | ¥2000/次 | 根据你的需求定制 | | Cron 任务矩阵设计 | ¥1500/次 | 自动化任务规划 | | 月度技术顾问 | ¥5000/月 | 每周优化 + 问题解答 | **成功案例**: 帮助 10+ 用户搭建自主运行 AI 助手 **联系**: 微信/Telegram 私信，备注"Automaton 咨询" --- ## Quick Start 1. Create `tasks/QUEUE.md` with Ready/In Progress/Blocked/Done sections 2. Update `HEARTBEAT.md` to pull from queue and do work 3. Set up cron jobs for overnight work and daily reports 4. Watch work happen without prompting ## Key Concepts - **Task Queue** — Always have work ready - **Proactive Heartbeat** — Do work, don't just check - **Continuous Operation** — Work until limits hit See README.md for full documentation.


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