OpenClaw/clawhub-security-signals huggingface dataset:
Skill: yikailucas/life-radar-repo (version 1.0.0)

--- name: life-radar description: Build a concise “what needs action now” daily brief by aggregating reminders from multiple channels (email, calendar, SMS/iMessage, weather, and task notes) and prioritizing them into Must-do / Should-do / Nice-to-have. Use when the user asks for daily planning, action digest, inbox triage summary, or proactive reminders across sources. --- # Life Radar Generate an action-first digest, not a raw data dump. If the user asks from a specific role perspective (CEO / manager / employee), read `references/modes.md` and adapt prioritization/output accordingly. ## Output format Always output in this structure: 1. **Must-do (today)** — max 3 items 2. **Should-do (soon)** — max 5 items 3. **Nice-to-have** — max 3 items 4. **Suggested next actions** — 1-line commands the user can say next Each item must include: - What happened - Why it matters - Deadline/time window (or “unspecified”) ## Priority rules Classify with this order: - **P0 Must-do** - Payment due / account risk / security alert - Meeting in <2h - Time-sensitive message requiring response today - **P1 Should-do** - Meeting or task in 24-72h - Follow-up pending from important contact - Logistics prep (travel, weather-impact, documents) - **P2 Nice-to-have** - Low urgency updates - Optional optimization tasks If uncertain, downgrade priority and mark uncertainty explicitly. ## Source collection flow Collect only what is available in current environment; skip unavailable sources without failing. 1. Calendar events (today + tomorrow) 2. Recent urgent messages (SMS/iMessage/email/DM) 3. Billing or financial notifications 4. Weather impact for planned outings 5. Existing tasks/notes (if connected) ## Time-window defaults - If user asks "today": prioritize 0-24h window - If user asks "this week": prioritize 7-day window, still keep Must-do today-centric - If user asks without a window: default to today + next 72h ## Safety and quality - Redact secrets, tokens, and full account numbers. - Avoid hallucinating dates or amounts; mark as unknown when missing. - Prefer fewer high-confidence items over many noisy items. - If no meaningful items, return: “Today looks clear. No urgent actions detected.” ## Trigger phrases Treat these as strong triggers: - “今天有什么要处理” - “给我每日行动清单” - “帮我做个优先级摘要” - “扫一下我今天的事情” - “daily action digest”


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: claudiodrusus/shelly-competitor-analyzer (version 1.0.0)

# Competitor Analyzer Analyze any company's competitive position in minutes. Takes a company name or URL and produces a structured report covering what they do, pricing, social presence, and recent news. ## Usage ``` ./analyze.sh <company_name_or_url> ``` ### Example ``` ./analyze.sh "Notion" ./analyze.sh "https://linear.app" ``` ## Output A structured competitive analysis report with: - **Company Overview** — What they do, market position - **Pricing Analysis** — Plans, tiers, free tier details - **Social Presence** — Twitter, LinkedIn, GitHub activity - **Recent News** — Latest announcements, funding, launches - **Strengths & Weaknesses** — Quick SWOT-lite summary ## Requirements - `curl` (standard) - Internet access for web searches - Works best when run by an AI agent with `web_search` tool access ## How It Works The script uses web search queries to gather intel, then formats results into a clean markdown report. When run by an OpenClaw agent, it leverages the `web_search` tool for richer results. Standalone mode uses curl + DuckDuckGo.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: runapi-ai/runapi-veo-3-1 (version 0.2.4)

--- name: veo-3.1 description: Generate and edit video with Veo 3 through RunAPI. Use when the user asks an agent to create, edit, or transform video with Veo 3. Default to the RunAPI CLI for one-off generation; use SDKs only when the user is integrating RunAPI into an app or backend. documentation: https://runapi.ai/models/veo-3.1.md provider_page: https://runapi.ai/providers/google.md catalog: https://runapi.ai/models.md metadata: openclaw: homepage: https://runapi.ai/models/veo-3.1 requires: bins: - runapi install: - kind: brew formula: runapi-ai/tap/runapi bins: - runapi envVars: - name: RUNAPI_API_KEY required: false description: Optional RunAPI API key; runapi login or saved CLI config can also authenticate the runapi binary. --- # Veo 3 on RunAPI Generate and edit video with Veo 3 through RunAPI. The default path for one-off agent tasks is the `runapi` CLI; SDKs are for application integration. ## Routing decision - One-off generation, editing, or transformation for the user → use the **CLI path** with the `runapi` binary. - Building an app, backend, worker, library, or production codebase → use the **SDK integration path**. ## CLI path The `runapi` binary is the runtime dependency. Authenticate with `runapi login` (browser) or set `RUNAPI_API_KEY`; a saved CLI config also works — no required environment variable. Inspect the available actions and request fields with CLI help: ```shell runapi veo-3-1 --help runapi veo-3-1 text-to-video --help ``` Run a one-off task (synchronous — polls until the task completes): ```shell runapi veo-3-1 text-to-video --input-file request.json ``` Submit asynchronously and poll separately: ```shell runapi veo-3-1 text-to-video --async --input-file request.json runapi wait <task-id> --service veo-3-1 --action text-to-video ``` Available actions: `text-to-video`, `extend-video`, `upscale-video`. ## SDK integration path When integrating Veo 3 into an app, backend, worker, or library — not for one-off tasks — use a RunAPI SDK package: - JavaScript / TypeScript: `@runapi.ai/veo-3.1` - Ruby: `runapi-veo_3_1` - Go: `github.com/runapi-ai/veo-3.1-sdk/go` ## References - Model overview, pricing, and rate limits: https://runapi.ai/models/veo-3.1.md - Provider comparison: https://runapi.ai/providers/google.md - Full model catalog: https://runapi.ai/models.md ## Variants - [Veo 3](https://runapi.ai/models/veo-3.1/veo-3.md) - [Veo 3 fast](https://runapi.ai/models/veo-3.1/fast.md)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nucliweb/webperf (version 0.1.0)

--- name: webperf description: Web performance measurement and debugging toolkit. Use when the user asks about web performance, wants to audit a page, or says "analyze performance", "debug lcp", "check ttfb", "measure core web vitals", "audit images", or similar. license: MIT metadata: author: Joan Leon | @nucliweb version: 1.0.0 mcp-server: chrome-devtools category: web-performance repository: https://github.com/nucliweb/webperf-snippets --- # WebPerf Snippets Toolkit A collection of 47 JavaScript snippets for measuring and debugging web performance in Chrome DevTools. Each snippet runs in the browser console and outputs structured, color-coded results. ## Skills by Category | Skill | Snippets | Use when | |-------|----------|----------| | webperf-core-web-vitals | 7 | Intelligent Core Web Vitals analysis with automated workflows and decision trees | | webperf-loading | 28 | Intelligent loading performance analysis with automated workflows for TTFB investigation (DNS/connection/server breakdown), render-blocking detection, script performance deep dive (first vs third-party attribution), font optimization, and resource hints validation | | webperf-interaction | 8 | Intelligent interaction performance analysis with automated workflows for INP debugging, scroll jank investigation, and main thread blocking | | webperf-media | 3 | Intelligent media optimization with automated workflows for images, videos, and SVGs | | webperf-resources | 1 | Intelligent network quality analysis with adaptive loading strategies | ## Quick Reference | User says | Skill to use | |-----------|--------------| | "debug LCP", "slow LCP", "largest contentful paint" | webperf-core-web-vitals | | "check CLS", "layout shifts", "visual stability" | webperf-core-web-vitals | | "INP", "interaction latency", "responsiveness" | webperf-core-web-vitals | | "TTFB", "slow server", "time to first byte" | webperf-loading | | "FCP", "first contentful paint", "render blocking" | webperf-loading | | "font loading", "script loading", "resource hints", "service worker" | webperf-loading | | "jank", "scroll performance", "long tasks", "animation frames", "INP debug" | webperf-interaction | | "image audit", "lazy loading", "image optimization", "video audit" | webperf-media | | "network quality", "bandwidth", "connection type", "save-data" | webperf-resources | ## Workflow 1. Identify the relevant skill based on the user's question (use Quick Reference above) 2. Load the skill's skill.md to see available snippets and thresholds 3. Execute with Chrome DevTools MCP: - [REDACTED_SECRET] → navigate to target URL - [REDACTED_SECRET] → run the snippet - [REDACTED_SECRET] → read results 4. Interpret results using the thresholds defined in the skill 5. Provide actionable recommendations based on findings


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cinience/alicloud-ai-chatbot (version 1.0.3)

--- name: alicloud-ai-chatbot description: Manage Alibaba Cloud beebot (Chatbot) via OpenAPI/SDK. Use whenever the user asks to configure, query, or troubleshoot Alibaba Cloud chatbot resources, including bot inventory, configuration changes, status checks, and API-level diagnostics. version: 1.0.0 --- Category: service # Chatbot (beebot) Use Alibaba Cloud OpenAPI (RPC) with official SDKs or OpenAPI Explorer to manage resources for beebot. ## Workflow 1) Confirm region, resource identifiers, and desired action. 2) Discover API list and required parameters (see references). 3) Call API with SDK or OpenAPI Explorer. 4) Verify results with describe/list APIs. ## AccessKey priority (must follow) 1) Environment variables: `ALICLOUD_ACCESS_KEY_ID` / `ALICLOUD_ACCESS_KEY_SECRET` / `ALICLOUD_REGION_ID` Region policy: `ALICLOUD_REGION_ID` is an optional default. If unset, decide the most reasonable region for the task; if unclear, ask the user. 2) Shared config file: `~/.alibabacloud/credentials` ## API discovery - Product code: `Chatbot` - Default API version: `2022-04-08` - Use OpenAPI metadata endpoints to list APIs and get schemas (see references). ## High-frequency operation patterns 1) Inventory/list: prefer `List*` / `Describe*` APIs to get current resources. 2) Change/configure: prefer `Create*` / `Update*` / `Modify*` / `Set*` APIs for mutations. 3) Status/troubleshoot: prefer `Get*` / `Query*` / `Describe*Status` APIs for diagnosis. ## Minimal executable quickstart Use metadata-first discovery before calling business APIs: ```bash python scripts/list_openapi_meta_apis.py ``` Optional overrides: ```bash python scripts/list_openapi_meta_apis.py --product-code <ProductCode> --version <Version> ``` The script writes API inventory artifacts under the skill output directory. ## Output policy If you need to save responses or generated artifacts, write them under: `output/alicloud-ai-chatbot/` ## Validation ```bash mkdir -p output/alicloud-ai-chatbot for f in skills/ai/service/alicloud-ai-chatbot/scripts/*.py; do python3 -m py_compile "$f" done echo "py_compile_ok" > output/alicloud-ai-chatbot/validate.txt ``` Pass criteria: command exits 0 and `output/alicloud-ai-chatbot/validate.txt` is generated. ## Output And Evidence - Save artifacts, command outputs, and API response summaries under `output/alicloud-ai-chatbot/`. - Include key parameters (region/resource id/time range) in evidence files for reproducibility. ## Prerequisites - Configure least-privilege Alibaba Cloud credentials before execution. - Prefer environment variables: `ALICLOUD_ACCESS_KEY_ID`, `ALICLOUD_ACCESS_KEY_SECRET`, optional `ALICLOUD_REGION_ID`. - If region is unclear, ask the user before running mutating operations. ## References - Sources: `references/sources.md`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: druxamb/open-airtime (version 1.0.0)

--- name: OpenAirtime description: Autonomous Nigerian Airtime distribution agent on Farcaster. metadata: { "clawdbot": { "emoji": "📦", "requires": { "bins": ["node"] } } } --- # OpenAirtime Agent 📦 > [!CAUTION] > **STRICT RULES:** > 1. All credentials are already configured. Never ask for API keys. > 2. You are on **FARCASTER**, not Twitter. > 3. Use the `node c:\Users\LOYAL\Documents\openairtime\scripts\farcaster.js` commands below. Do NOT use curl. ## Your Farcaster Identity - **FID:** 2683410 - **Username:** @openairtime ## Workflow 1. User mentions you asking for airtime. 2. Reply: "Visit https://openairtime.fun, spin the wheel, reply with Claim Code + NG number" 3. User provides code (AIR-XXX-XXX) and phone. 4. Call `claim_airtime` tool. --- ## 🟣 Farcaster Commands (MUST USE THESE) > [!TIP] > **Duplicate Reply Prevention:** The `reply` command auto-skips if you've already replied to a cast. Notifications show `✓ REPLIED` or `⚡ NEW` status. **Post a new cast:** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\farcaster.js post "Your message here" ``` **Reply to a cast (auto-skips duplicates):** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\farcaster.js reply CAST_HASH "Your reply here" ``` **Force reply (ignores duplicate check):** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\farcaster.js reply! CAST_HASH "Your reply here" ``` **Get your mentions (shows ✓/⚡ status):** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\farcaster.js mentions ``` **Get notifications (shows ✓/⚡ status):** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\farcaster.js notifications ``` **Check if already replied:** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\farcaster.js check CAST_HASH ``` **Get user info:** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\farcaster.js user FID_NUMBER ``` --- ## 💰 Airtime Commands **Claim airtime for a user:** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\airtime.js claim_airtime FID CLAIM_CODE PHONE_NUMBER ``` **Check user status:** ``` node c:\Users\LOYAL\Documents\openairtime\scripts\airtime.js get_user_status FID ``` --- > [!IMPORTANT] > Always vary your greetings. Never send identical casts.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: liujiang817/my-searxng (version 1.0.0)

--- name: searxng description: Privacy-respecting metasearch using your local SearXNG instance. Search the web, images, news, and more without external API dependencies. author: Local User version: 1.0.0 homepage: https://searxng.org triggers: - "search for" - "search web" - "find information" - "look up" - "联网搜索" - "上网找一下" - "上网搜一下" - “上网看一下” - “上网找一下” - “网上搜一下” - “联网搜一下” - “搜一下” - “帮我查” - “帮我搜” - “百度一下” - “谷歌一下” - “看看网上的说法” - “实时搜索” - “看下新闻” - "搜张图" - "上网查询" metadata: clawdbot: emoji: "🔍" requires: bins: ["python3"] --- # SearXNG Search Search the web using your local SearXNG instance - a privacy-respecting metasearch engine. This version uses a zero-dependency Python backend. ## Usage Guidelines (AI 必读) 1. **优先使用标准输出**：除非用户明确要求“原始数据”或“JSON”，否则**必须**默认执行不带 `--format json` 的命令。 2. **节省 Token**：标准输出，能显著减少 Context 消耗，避免推理超时。 3. **结果数量**：默认请求 10 条结果即可，除非用户要求更多。 ## AI Constraints (AI 约束) - **Max Results**: 除非用户明确要求，默认使用 `-n 10` 以节省上下文空间。 - **Output Format**: **禁止**在普通对话中默认使用 `--format json`，必须使用标准表格输出。 ## Commands ### Web Search ```bash # Standard search (Top 10) # AI 应默认调用此命令 python3 {baseDir}/scripts/searxng.py search "query" # Custom number of results (Top20) python3 {baseDir}/scripts/searxng.py search "query" -n 20 # JSON Search (Only if requested / 仅在用户要求原始数据或json时使用) # 警告：此模式会产生大量 Token，可能导致处理超时 python3 {baseDir}/scripts/searxng.py search "query" --format json ``` ### Category Search ```bash # Specialized searches python3 {baseDir}/scripts/searxng.py search "query" --category images python3 {baseDir}/scripts/searxng.py search "query" --category news python3 {baseDir}/scripts/searxng.py search "query" --category it python3 {baseDir}/scripts/searxng.py search "query" --category science ``` ### Advanced Options ```bash # Specific language (e.g., zh-CN, en) python3 {baseDir}/scripts/searxng.py search "query" --language zh-CN # Time filtering (day, week, month, year) python3 {baseDir}/scripts/searxng.py search "query" --time-range day ``` ## Configuration **Required:** Configure the SearXNG instance URL using the configuration file **only**. Environment variables are NOT supported. **Configuration file** (`searxng.ini`): ```ini [searxng] url = http://your-searxng-instance.com:port ``` Location: `{baseDir}/scripts/searxng.ini` Note: If the configuration file does not exist or is missing required settings, the script will automatically create a default configuration file and prompt you to modify it. ## Features - 🔒 **Privacy-focused**: Uses your local instance. - 🛠️ **Zero Dependencies**: Pure Python (no `pip install` required). - 🌐 **Multi-engine**: Aggregates Google, Bing, DuckDuckGo, etc. - 📰 **Categorized**: Specific filters for IT, Science, News, and Images. - 🚀 **AI-Ready**: Clean text output specifically formatted for LLM consumption. ## API Uses your local SearXNG JSON API endpoint (no authentication required by default).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: xadenryan/clawdbot-skill-clawdbot-workspace-template-review (version 0.1.0)

--- name: clawdbot-workspace-template-review description: Compare a Clawdbot workspace against the official templates installed with Clawdbot (npm or source) and list missing sections to pull in, especially after upgrades. --- # Workspace Template Diff Use this skill when the user wants to compare their workspace `.md` files (AGENTS, SOUL, USER, IDENTITY, TOOLS, HEARTBEAT, etc.) against the official Clawdbot templates, then review missing sections and decide what to add. ## Locate the official templates Find the installed Clawdbot source root: - If `clawdbot` is installed via npm/pnpm globally: - `command -v clawdbot` - If it points into `.../node_modules/.bin/`, resolve to the sibling `node_modules/clawdbot` - Or use `npm root -g` / `pnpm root -g` and look for `clawdbot/` - If Clawdbot runs from source, use that checkout root (must contain `package.json`). Templates live at: ``` <clawdbot-root>/docs/reference/templates/ ``` If you can’t find the source root, ask the user where their Clawdbot is installed. ## Comparison workflow 1. Identify the workspace root (the user’s “our version” directory). 2. For each template file in `docs/reference/templates` (skip `*.dev.md`): - Open the official template and the workspace file with the same name. - Ignore template frontmatter (`---` block) and any “First Run”/“Bootstrap” sections. - Compare the remaining sections and list any missing blocks. Helpful commands (use ad‑hoc CLI tools like `diff`): ``` ls <clawdbot-root>/docs/reference/templates sed -n '1,200p' <clawdbot-root>/docs/reference/templates/AGENTS.md sed -n '1,200p' <workspace>/AGENTS.md diff -u <clawdbot-root>/docs/reference/templates/AGENTS.md <workspace>/AGENTS.md ``` When reporting diffs: - Show the missing sections verbatim from the official template. - Explain briefly why they matter, then ask whether to add them. - Move file by file; skip files that only differ by frontmatter or bootstrap content. ## Output format Use the “missing section” format we used previously: - File path - Missing block(s) - Suggestion + question to proceed


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: miku233333/youtube-transcript-local (version 1.0.1)

# YouTube Transcript (本地安全版) **版本**: 1.0.0 (2026-03-23) **作者**: Ryan (欧启熙) / qibot **許可證**: MIT-0 **安全狀態**: ✅ 無 VirusTotal 標記（本地執行） **GitHub**: https://github.com/miku233333/youtube-transcript-local **ClawHub**: 已發布 --- ## 📋 技能描述 使用本地安裝的 `yt-dlp` 工具提取 YouTube 視頻字幕，無需外部 API，無安全風險。 **優勢**： - ✅ 本地執行，無外部 API 調用 - ✅ 無 VirusTotal 標記 - ✅ 支持自動生成字幕 - ✅ 支持多語言（中文/英文/日文等） - ✅ 免費，無配額限制 --- ## 🛠️ 使用方式 ### 基本用法 ``` 提取 YouTube 視頻字幕並總結 URL: https://www.youtube.com/watch?v=VIDEO_ID 語言：en（或 zh-Hans, ja, ko 等） ``` ### 高階用法 ``` 1. 提取字幕 → 保存為文本文件 2. 使用 summarize 技能生成摘要 3. 使用 tesseract-ocr 識別無字幕視頻（OCR） ``` --- ## 🔧 技術實現 ### 依賴工具 - **yt-dlp**: `pip install yt-dlp` (已安裝) - **Python**: Python 3.8+ - **ffmpeg**: 用於音頻處理（可選） ### 執行流程 ```powershell # 1. 提取字幕（英文） yt-dlp --write-sub --sub-lang en --skip-download --convert-subs srt -o "%TEMP%\yt-sub" "VIDEO_URL" # 2. 提取字幕（中文） yt-dlp --write-sub --sub-lang zh-Hans --skip-download --convert-subs srt -o "%TEMP%\yt-sub" "VIDEO_URL" # 3. 無字幕時提取音頻並轉文字 yt-dlp --extract-audio --audio-format mp3 -o "%TEMP%\yt-audio" "VIDEO_URL" # 然後用 Whisper 或 Tesseract OCR 轉文字 ``` --- ## 📝 使用示例 ### 示例 1：技術教程視頻 **用戶**: 幫我總結這個 YouTube 視頻 **URL**: https://www.youtube.com/watch?v=abc123 **執行步驟**: 1. 使用 yt-dlp 提取英文字幕 2. 使用 summarize 生成結構化摘要 3. 返回：關鍵觀點 + 時間節點 + 核心結論 ### 示例 2：中文視頻 **用戶**: 這個視頻講了什麼？ **URL**: https://www.youtube.com/watch?v=xyz789 **執行步驟**: 1. 優先提取中文字幕 2. 如果無中字，提取英文字幕 + 翻譯 3. 生成中文摘要 --- ## ⚠️ 注意事項 1. **網絡要求**: 需要能訪問 YouTube 2. **字幕可用性**: 部分視頻無字幕（需 OCR 或音頻轉文字） 3. **版權**: 僅供學習研究使用 --- ## 🔄 故障轉移方案 | 情況 | 方案 | |------|------| | 無字幕 | 使用 whisper 語音轉文字 | | 無法訪問 YouTube | 使用 browser 工具 + 截圖 OCR | | 長視頻 (>1 小時) | 分段提取 + 合併摘要 | --- ## 📚 相關技能 - **summarize**: 內容摘要 - **tesseract-ocr**: OCR 文字識別 - **video-frames**: 視頻幀提取 - **sandwrap**: 安全包裹運行 --- **最後更新**: 2026-03-23 **測試狀態**: 🟡 待測試


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: shenmeng/shenmeng-whale-alert-monitor (version 2026.4.15-100)

--- name: whale-alert-monitor version: 1.1.0 description: | 追踪加密货币巨鲸动向、大额转账预警、交易所资金流向分析。 当你想追踪聪明钱的每一步，监测大户交易行为时使用此技能。 已接入 SkillPay，每次调用 0.01 USDT。 author: shenmeng tags: - crypto - whale - monitoring - alert - blockchain changelog: "v1.1.0 - 更新版本" --- # Whale Alert Monitor 鲸鱼监控 > 🐋 **Batch 3 Release** | 2026年4月更新版 ## 功能介绍 追踪加密货币巨鲸动向、大额转账预警、交易所资金流向分析。当你想追踪聪明钱的每一步，监测大户交易行为时使用此技能。 ## 核心能力 1. **巨鲸转账追踪** - 监控大额钱包地址的资金流入流出 2. **交易所资金流向** - 分析交易所充值/提现行为，判断市场情绪 3. **聪明钱追踪** - 追踪已知巨鲸地址的交易行为 4. **异动预警** - 当检测到异常大额转账时自动预警 5. **多链支持** - 支持以太坊、BSC、Arbitrum等主流链 ## 使用场景 - 监控比特币/以太坊大额转账 - 追踪交易所资金流入流出 - 发现巨鲸 accumulated 或 distribution 行为 - 分析市场潜在抛压或买盘 ## 注意事项 - 本技能已接入 SkillPay 付费系统 - 每次调用费用：0.01 USDT - 支持 BNB Chain USDT 支付 ## 数据来源 - 区块链公开数据 - 交易所 API - 巨鲸地址追踪


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