OpenClaw/clawhub-security-signals huggingface dataset:
Skill: katherineedwards2475/rdk-x5-quickstart (version 1.0.0)

--- name: rdk-x5-quickstart description: "RDK X5 新手快速入门：从开箱到第一个 AI 应用的完整流程，包括首次烧录镜像、首次启动、首次连接网络、运行第一个 YOLO 检测 demo。Use when the user is a beginner, first-time user, just unboxed the board, asks '怎么开始/入门/第一次', or needs the initial image flashing guide. Do NOT use for re-flashing an existing board or firmware upgrade (use rdk-x5-system), advanced system management (use rdk-x5-system), specific AI algorithms (use rdk-x5-ai-detect), or TROS development (use rdk-x5-tros)." license: MIT-0 metadata: openclaw: compatibility: platform: rdk-x5 --- # RDK X5 Quickstart — 快速入门 从开箱到运行第一个 AI 应用。 ## Step 1: 烧录系统镜像 1. 从 [地瓜机器人官网](https://developer.d-robotics.cc/) 下载最新 RDK OS 镜像 2. 使用 balenaEtcher 或 `dd` 烧录到 microSD 卡（≥16GB）： ```bash sudo dd if=rdk_os_image.img of=/dev/sdX bs=4M status=progress && sync ``` 3. 插入 SD 卡到 RDK X5 ## Step 2: 首次启动 1. 接上电源（Type-C 5V/3A 或 12V DC） 2. 默认账号：`root` / `root` 或 `sunrise` / `sunrise` 3. 系统启动后自动获取 IP（有线 DHCP） ## Step 3: 连接网络 ```bash # 查看 IP（有线） ip addr show eth0 # 连接 WiFi sudo nmcli device wifi connect "你的WiFi名" password "你的密码" # 确认联网 ping -c 2 baidu.com ``` ## Step 4: 确认系统版本 ```bash rdkos_info cat /etc/version ``` ## Step 5: 更新系统（推荐） ```bash sudo apt update && sudo apt upgrade -y ``` ## Step 6: 运行第一个 AI Demo ### 方式 A: Python 脚本（最简单） ```bash cd /app/pydev_demo/07_yolov5_sample python3 test_yolov5.py ``` 终端输出检测结果。 ### 方式 B: TROS + 摄像头 + Web 展示（推荐） 1. 接上 USB 或 MIPI 摄像头 2. 运行： ```bash source /opt/tros/humble/setup.bash ros2 launch dnn_node_example dnn_node_example.launch.py \ dnn_example_config_file:=config/yolov5sworkconfig.json \ dnn_example_image_width:=640 dnn_example_image_height:=480 ``` 3. 浏览器打开 `http://<RDK_IP>:8000` 查看实时检测画面 ## Step 7: 下一步探索 | 想做什么 | 使用哪个 Skill | |---------|---------------| | 管理摄像头 | rdk-x5-camera | | 运行更多 AI 算法 | rdk-x5-ai-detect | | 控制 GPIO/舵机 | rdk-x5-gpio | | 监控系统状态 | rdk-x5-monitor | | 使用 ROS2 开发 | rdk-x5-tros | | 运行 /app 示例 | rdk-x5-app | | 系统备份/升级 | rdk-x5-system | ## 排查故障 | 现象 | 原因 | 解决 | |------|------|------| | 无法启动（无串口输出） | SD 卡未正确烧录 | 重新烧录镜像；换一张 SD 卡 | | 启动后无法 SSH | IP 未知 | 用串口登录查看 IP；或连接显示器 | | `apt update` 失败 | 无网络或 DNS 问题 | `ping 8.8.8.8`；检查网线/WiFi | | 摄像头无画面 | 未接摄像头或设备节点错误 | `ls /dev/video*` 确认设备存在 |


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

--- name: book-moving description: Book moving services through Lokuli MCP. Use when user needs to find and book moving. Triggers on requests like "book a moving", "find moving near me", or any moving service request. --- # uook moving Book moving 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": "moving", "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: suspicious (MEDIUM)
Skill: kirkraman/toby-transcribe (version 1.0.0)

--- name: openai-whisper description: Speech-to-text via SkillBoss API Hub (STT, powered by Whisper and more). homepage: https://api.skillbossai.com metadata: {"clawdbot":{"emoji":"🎙️","requires":{"env":["SKILLBOSS_API_KEY"]}}} --- # Whisper STT via SkillBoss API Hub Use SkillBoss API Hub's `/v1/pilot` to transcribe audio (STT), powered by OpenAI Whisper and other speech recognition models. Quick start (Python) ```python import requests, base64, os SKILLBOSS_API_KEY = os.environ["SKILLBOSS_API_KEY"] API_BASE = "https://api.skillbossai.com/v1" def pilot(body: dict) -> dict: r = requests.post( f"{API_BASE}/pilot", headers={"Authorization": f"Bearer {SKILLBOSS_API_KEY}", "Content-Type": "application/json"}, json=body, timeout=60, ) return r.json() # Transcribe audio file audio_b64 = base64.b64encode(open("/path/audio.mp3", "rb").read()).decode() result = pilot({"type": "stt", "inputs": {"audio_data": audio_b64, "filename": "audio.mp3"}}) text = result["result"]["text"] print(text) # Translate audio to English result = pilot({"type": "stt", "inputs": {"audio_data": audio_b64, "filename": "audio.m4a", "task": "translate"}}) text = result["result"]["text"] print(text) ``` Notes - No local model download required; SkillBoss API Hub automatically routes to the best STT model. - `SKILLBOSS_API_KEY` environment variable required. - Response text is at `result["result"]["text"]`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xinxinhappy111/history-source-collector (version 1.0.0)

# 史料收集器 你是k12领域历史学科通用专业史料收集助手，严格遵循以下规则运行： 1. 所有史料检索**仅调用公司内部封装秘塔学术检索Tool**，不使用外部公开搜索引擎、不调用第三方公开学术接口，绝不泄露任何接口密钥信息 2. 严格分层整理史料 - 一手原始史料：历代官修正史、历朝实录、宫廷奏折档案、地方志、古籍碑刻、原始出土档案 - 二手学术研究史料：CSSCI史学期刊、历史学硕博学位论文、权威史学学术专著 3. 所有史料必须完整标注：所属朝代、文献书名、卷次版本、权威学术出处，做到溯源可查 4. 严格按照历史时间编年排序，客观摘录史料原文，不杜撰、不篡改古籍内容，不主观臆断解读史实 5. 内容严格过滤：拒绝野史传说、网络杂谈、自媒体非学术内容，只输出历史学正规权威学术史料 6. 自动按照GB/T 7714国家标准格式，整理史学参考文献，可直接用于学科教研、课程作业、学术科研 7. 全朝代历史学通用适配，不限定细分历史领域，适配所有历史学科史料检索整理场景 8. 输出统一Markdown清晰排版，分点分类展示，方便用户一键复制存档


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: vanyanski/va-claims-assistant (version 1.0.0)

--- name: va-claims-assistant description: "Research and guide VA disability claims for U.S. military veterans. Use when a veteran asks about: VA disability ratings, filing or increasing a claim, nexus letters, buddy statements, DBQs (Disability Benefits Questionnaires), PACT Act eligibility, toxic exposure benefits, VA buddy statements, C&P exam preparation, supplemental claims, appeals (HLR/BVA), combined rating calculations, or any VA benefits question. Covers the full claims lifecycle from initial filing through Board of Veterans Appeals." --- # VA Claims Assistant Guide veterans through the VA disability claims process from initial filing through appeals. ## Quick Reference **Rating calculator:** See `references/rating-math.md` for combined disability formula **Nexus letter template:** See `references/nexus-template.md` **Common conditions:** See `references/conditions.md` for service connection guidance ## Core Workflow ### 1. Assess the Veteran's Situation Ask (or infer from context): - Branch of service, dates of service, discharge status - Current claimed conditions and their severity - Existing rating (if any) and target rating - Key events: PACT Act exposure, MST, TBI, hazardous duty ### 2. Calculate / Estimate Combined Rating Use `scripts/va_rating_calc.py` — NOT simple addition. VA uses "whole person" method: ```bash python3 scripts/va_rating_calc.py 70 30 20 10 ``` Always round to nearest 10 for final rating display. ### 3. Research Service Connection Each condition needs: - **In-service event** (exposure, incident, MOS) - **Current diagnosis** (medical records) - **Nexus** (medical opinion linking service to condition) PACT Act (2022): expands presumptive conditions for burn pit, Agent Orange, radiation exposure — no nexus letter required for presumptives. See `references/conditions.md`. ### 4. Documents Checklist - DD-214 (discharge document) - STRs (Service Treatment Records) — request via MyHealtheVet or NPRC - Private medical records + buddy statements - DBQ completed by private doctor (stronger than VA examiner) - Nexus letter (if not presumptive) ### 5. Filing Strategy - **New claim:** VA.gov > File a VA disability claim (21-526EZ) - **Increase:** Same form, select "increase in disability" - **Supplemental:** New evidence required - **HLR (Higher Level Review):** Same evidence, fresh review - **BVA Appeal:** Board of Veterans Appeals — use if HLR denied ### 6. C&P Exam Prep Tell veteran: Show up. Describe worst day, not best day. Don't minimize symptoms. Checklist: See `references/cp-exam-prep.md` for condition-specific prep. ## Key Rules - Always calculate combined rating with the script — never add percentages - PACT Act presumptives skip nexus requirement (just need diagnosis + exposure) - 100% P&T (Permanent and Total) = CHAMPVA for dependents + property tax exemptions - TDIU: Can get 100% pay at 60%+ single / 70%+ combined with one at 40%+ - SMC (Special Monthly Compensation): additional pay for loss of use, Aid & Attendance


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: erongcao/erong-crypto-analyst (version 1.0.0)

--- name: crypto-analyst description: 加密货币综合分析工具，整合OKX、Binance双交易所数据。提供行情查询、技术分析、交易信号、资金流向、仓位管理、DCA计划、风险计算。触发词：分析BTC、行情查询、交易信号、仓位计算、DCA计划、巨鲸追踪、风险评估。 --- # Crypto Analyst v1.0 加密货币综合分析，统一调用 OKX、Binance、AKShare 三大数据源。 ## 工作流 ``` 价格查询 → 技术分析 → 资金流向 → 策略建议 → 仓位管理 ``` ## 工具速查 | 需求 | 工具 | 数据源 | |------|------|--------| | OKX技术分析/信号 | `okx_analyst.py` | OKX API | | Binance实时行情 | `binance_market.py` | Binance公开API | | Binance技术分析 | `technical_analysis.py` | Binance公开API | | 双交易所价格对比 | `cross_exchange.py` | OKX + Binance | | 巨鲸追踪 | `whale_tracker.py` | Binance | | DCA定投计划 | `dca_calculator.py` | 本地计算 | | 仓位计算 | `position_sizer.py` | 本地计算 | | 市场机会扫描 | `market_scanner.py` | Binance | | 恐惧&贪婪 | `fear_greed.py` | alternative.me | | 加密货币余额 | `balance_check.py` | OKX API（需要Key） | ## 快速命令 ### 日常行情分析 ```bash # OKX技术分析（完整报告） python3 scripts/okx_analyst.py BTC-USDT # OKX快速信号 python3 scripts/okx_analyst.py BTC-USDT --signal-only # Binance实时价格 python3 scripts/binance_market.py --symbol BTCUSDT # Binance技术分析 python3 scripts/technical_analysis.py --symbol BTCUSDT --interval 1h ``` ### 进阶分析 ```bash # 跨交易所价格对比（发现价差套利机会） python3 scripts/cross_exchange.py BTC # 巨鲸追踪 python3 scripts/whale_tracker.py --symbol BTCUSDT # 市场机会扫描（Binance热门币种） python3 scripts/market_scanner.py --gainers --limit 10 # 恐惧&贪婪指数 python3 scripts/fear_greed.py ``` ### 策略工具 ```bash # DCA定投计划 python3 scripts/dca_calculator.py --total 5000 --frequency weekly --duration 180 --current-price 70000 # 仓位计算（2%风控） python3 scripts/position_sizer.py --balance 10000 --risk 2 --entry 70000 --stop-loss 67000 ``` ## 标准分析流程 当用户说"分析BTC"或"帮我看看行情"时： **Step 1 - 价格 & 趋势** ```bash # OKX 4H周期完整分析 python3 scripts/okx_analyst.py BTC-USDT --timeframe 4H # Binance 1H作为辅助确认 python3 scripts/binance_market.py --symbol BTCUSDT --klines 1h --limit 50 ``` **Step 2 - 资金面** ```bash # 巨鲸动向 python3 scripts/whale_tracker.py --symbol BTCUSDT # 交易所资金费率（判断多空情绪） python3 scripts/binance_market.py --symbol BTCUSDT --funding ``` **Step 3 - 市场情绪** ```bash # 恐惧&贪婪 python3 scripts/fear_greed.py ``` **Step 4 - 策略输出** 综合以上给出： 1. 当前信号（看涨/看跌/中性） 2. 关键支撑/阻力位 3. 入场区间 4. 止损/止盈建议 5. 仓位大小（风控） 6. 风险提示 ## 信号强度说明 | 强度 | 信号 | 建议 | |:---:|:---:|:---| | +8以上 | 🟢 强烈看涨 | 积极做多 | | +5~+7 | 🟡 温和看涨 | 轻仓试多 | | +2~+4 | 🔵 轻微看涨 | 观望 | | -1~+1 | ⚪ 中性 | 不操作 | | -2~-4 | 🟠 轻微看跌 | 轻仓试空 | | -5以下 | 🔴 强烈看跌 | 不做多 | ## 跨交易所对比 使用 `cross_exchange.py` 检测 OKX vs Binance 价差，超过0.1%提示套利机会。 ## 风险控制规则 1. 单笔交易风险 ≤ 账户2% 2. 总持仓 ≤ 账户50% 3. 永远带止损 4. 恐惧&贪婪指数 ≥ 75（极度贪婪）时不做多 5. 巨鲸卖出信号 + RSI超买 → 谨慎 ## 配置文件 OKX API Key 配置在 `.env`： ``` OKX_API_KEY=your-key OKX_API_SECRET=your-secret ``` ## 依赖 ```bash pip install requests pandas numpy python-dotenv akshare ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: gumadeiras/calcurse (version 1.0.0)

--- name: calcurse description: A text-based calendar and scheduling application. Use strictly for CLI-based calendar management. metadata: {"clawdbot":{"emoji":"📅","requires":{"bins":["calcurse"]}}} --- # calcurse A text-based calendar and scheduling application. ## Usage (CLI Mode) Use `calcurse` in non-interactive mode for quick queries and updates. ### Query List appointments for the next 2 days: ```bash calcurse -r2 ``` Query a specific date range: ```bash calcurse -Q --from 2026-01-20 --to 2026-01-22 ``` ### Add Items Add an appointment: ```bash calcurse -a "Meeting with Team" 2026-01-21 14:00 60 ``` (Format: Description, Date, Time, Duration in mins) Add a todo: ```bash calcurse -t "Buy milk" 1 ``` (Format: Description, Priority) ## Interactive Mode (TUI) For the full TUI experience, run in a PTY session (e.g., inside `tmux` or using `process` with `pty=true`). ```bash calcurse ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yuanchao193/claw-search (version 1.0.3)

# Claw Search 🔍 通用免费的 Web Search API 服务，专为 AI Agents 设计。 ## 功能 - 🔍 **Web 搜索** - 类似 Brave Search 的 Web Search API - 🌐 **通用兼容** - 兼容 OpenClaw、Claude Code 等各种 Agent - 🔑 **无需 API Key** - 使用 skillhub 后端，无需申请 - 🚀 **快速响应** - 优化的搜索体验 - 🐳 **Docker 部署** - 一键部署到任意服务器 ## API 使用 ### Web 搜索 ```bash curl -X POST https://api.claw-search.com/api/search \ -H "Content-Type: application/json" \ -d '{"query": "openclaw ai agent", "count": 10}' ``` ### 搜索结果示例 ```json { "query": "openclaw ai agent", "count": 5, "results": [ { "title": "openclaw-backup", "url": "https://clawhub.com/skill/openclaw-backup", "description": "OpenClaw Backup", "age": "" } ] } ``` ## API 参数 | 参数 | 类型 | 必填 | 说明 | |------|------|------|------| | query | string | 是 | 搜索关键词 | | count | number | 否 | 返回结果数量 (默认 10, 最大 20) | | offset | number | 否 | 分页偏移 | | country | string | 否 | 国家代码 (默认 CN) | | freshness | string | 否 | 时间范围: pd(天), pw(周), pm(月), py(年) | ## 部署 ### Docker 部署 (推荐) ```bash # 克隆或下载项目 cd claw-search # 启动服务 docker-compose up -d # 测试 curl https://api.claw-search.com/health ``` ### 手动部署 ```bash # 安装依赖 npm install # 启动服务 PORT=8080 npm start ``` ## 环境变量 | 变量 | 说明 | |------|------| | PORT | 服务端口 (默认 8080) | | TAVILY_API_KEY | Tavily API Key (可选) | | BRAVE_API_KEY | Brave Search API Key (可选) | ## OpenClaw Skill 调用 ```bash node {baseDir}/scripts/search.mjs "搜索关键词" node {baseDir}/scripts/search.mjs "搜索关键词" -n 10 ``` ## 支持的后端 1. **skillhub** (默认，免费) - 搜索 ClawHub 技能 2. **tavily** (需要 API Key) - AI 优化的通用搜索 3. **brave** (需要 API Key) - Brave Search ## 上传到 ClawHub ```bash clawhub publish ``` ## License MIT


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: 275254cl-hash/niche-product-finder (version 1.0.0)

--- name: niche-product-finder version: 1.0.0 description: 发现蓝海商品和细分市场机会，适合电商选品、副业创业、市场分析师。 homepage: https://github.com/openclaw/skills metadata: { "openclaw": { "emoji": "🔍", "requires": { "bins": ["python3"] }, "install": [], }, } --- # 蓝海商品发现技能 发现低竞争高利润的细分市场商品机会。 ## 功能 1. **蓝海发现**: 低竞争高需求商品 2. **趋势分析**: 上升期品类预测 3. **利润测算**: 估算毛利空间 4. **竞品分析**: 现有卖家数量 5. **供应链推荐**: 1688 货源对接 ## 使用方式 **找蓝海商品**: ``` 帮我找 3 个蓝海商品，要求月利润 1 万+ ``` **分析品类**: ``` 分析一下宠物用品市场的竞争情况 ``` **利润测算**: ``` 在淘宝卖手机壳能赚多少钱？ ``` **找货源**: ``` 找一下瑜伽垫的 1688 货源，要求利润 50%+ ``` ## 输出示例 ``` 🔍 蓝海商品推荐 (2026-03-24) 1️⃣ 商品：宠物智能饮水机 ├─ 市场需求：月搜索 5 万+ ├─ 竞争程度：中低（卖家 200+） ├─ 平均售价：¥89-159 ├─ 1688 成本：¥35-55 ├─ 毛利空间：55-65% ├─ 月销潜力：300-500 件 └─ 预估月利：¥8,000-15,000 💡 机会点： - 竞争相对较小 - 复购率高（滤芯） - 可打造品牌 ⚠️ 风险： - 需要一定启动资金 - 物流成本较高 📦 货源推荐： - 1688 厂家：义乌市 XXX 宠物用品厂 - 起订量：50 件 - 支持一件代发：是 ``` ## 变现模式 - 免费：每日 3 次查询 - 付费 (¥99/月)：无限查询 + 详细报告 - 付费 (¥299/月)：+ 定制选品 + 货源对接 ## 优势 - ✅ 高客单价 - ✅ B 端用户付费意愿强 - ✅ 可延伸咨询服务 - ✅ 数据驱动决策 --- **声明**: 数据仅供参考，投资有风险。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: snilpmud/cs-gog (version 1.0.0)

--- name: gog description: Google Workspace CLI for Gmail, Calendar, Drive, Contacts, Sheets, and Docs. homepage: https://gogcli.sh metadata: {"clawdbot":{"emoji":"🎮","requires":{"bins":["gog"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/gogcli","bins":["gog"],"label":"Install gog (brew)"}]}} --- # gog Use `gog` for Gmail/Calendar/Drive/Contacts/Sheets/Docs. Requires OAuth setup. Setup (once) - `gog auth credentials /path/to/client_secret.json` - `gog auth add [REDACTED_SECRET] --services gmail,calendar,drive,contacts,sheets,docs` - `gog auth list` Common commands - Gmail search: `gog gmail search 'newer_than:7d' --max 10` - Gmail send: `gog gmail send --to [REDACTED_SECRET] --subject "Hi" --body "Hello"` - Calendar: `gog calendar events <calendarId> --from <iso> --to <iso>` - Drive search: `gog drive search "query" --max 10` - Contacts: `gog contacts list --max 20` - Sheets get: `gog sheets get <sheetId> "Tab!A1:D10" --json` - Sheets update: `gog sheets update <sheetId> "Tab!A1:B2" --values-json '[["A","B"],["1","2"]]' --input USER_ENTERED` - Sheets append: `gog sheets append <sheetId> "Tab!A:C" --values-json '[["x","y","z"]]' --insert INSERT_ROWS` - Sheets clear: `gog sheets clear <sheetId> "Tab!A2:Z"` - Sheets metadata: `gog sheets metadata <sheetId> --json` - Docs export: `gog docs export <docId> --format txt --out /tmp/doc.txt` - Docs cat: `gog docs cat <docId>` Notes - Set `GOG_ACCOUNT=[REDACTED_SECRET]` to avoid repeating `--account`. - For scripting, prefer `--json` plus `--no-input`. - Sheets values can be passed via `--values-json` (recommended) or as inline rows. - Docs supports export/cat/copy. In-place edits require a Docs API client (not in gog). - Confirm before sending mail or creating events.

path: _meta.json
content: ownerId: kn70pywhg0fyz996kpa8xj89s57yhv26
slug: gog
version: 1.0.0
publishedAt: 1767545346060

Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: outsmartchad/outsmart-lp-sniping (version 1.0.0)

--- name: outsmart-lp-sniping description: "Buy tokens at or near LP creation on Solana. Use when: user asks about sniping, bonding curve graduation, migration, new pool, LP created, pump fun graduation, launchlab, first buy. NOT for: slow accumulation (use DCA), established tokens (use regular trading), historical analysis." homepage: https://github.com/outsmartchad/outsmart-cli metadata: { "openclaw": { "requires": { "bins": ["outsmart"], "env": ["PRIVATE_KEY", "MAINNET_ENDPOINT"] }, "install": [{ "id": "node", "kind": "node", "package": "outsmart", "bins": ["outsmart"], "label": "Install outsmart CLI (npm)" }] } } --- # LP Sniping The moment liquidity appears, you buy. Speed is everything. ## When to Use - "Snipe this token at graduation" - "Buy the moment LP goes live" - "PumpFun bonding curve at 90%" - Token about to migrate to AMM ## When NOT to Use - Slow accumulation — use DCA skill instead - Established tokens — use regular dex-trading - You don't know what the token is — research first ## Commands ```bash # Competitive buy with Jito MEV tip outsmart buy --dex meteora-dlmm --pool POOL --amount 0.05 --tip 0.005 # Quick buy via aggregator (if you have the mint but not pool) outsmart buy --dex jupiter-ultra --token MINT --amount 0.05 # Check what you bought outsmart info --token MINT ``` ## What to Snipe **PumpFun graduation** — bonding curve fills to 100%, migrates to PumpSwap. Target: 80%+ progress, active community, dev hasn't sold. **LaunchLab** — same pattern, graduates to Raydium CPMM. **Known mints** — dev shared the address before pool exists. ## Position Sizing - Confident in narrative: 2-3% of portfolio - Looks promising: 1% - Just want exposure: 0.5% ## After You're In ```bash # Check if you should hold or dump outsmart info --token MINT ``` Low organic activity, single wallet >30%, no real volume? Sell and move on. ## Exit Plan | Hit | Do | |-----|-----| | 2x | Sell 50% | | 3-5x | Sell another 25% | | 10x+ | Let the rest ride | | -50% | Full exit | ```bash outsmart sell --dex jupiter-ultra --token MINT --pct 50 ``` ## After — The LP Play If the token has legs: ```bash # < 5 min, big volume: create DAMM v2 pool with 99% fee outsmart create-pool --dex meteora-damm-v2 --token MINT --base-amount 1000000 --quote-amount 0.5 --max-fee 9900 --min-fee 200 # > 30 min, established: DLMM position outsmart add-liq --dex meteora-dlmm --pool POOL --sol 0.5 --strategy spot --bins 50 ``` ## Risks - Rugs — that's why you size small - Front-run by MEV — use `--tip` for priority - Late entry — don't chase with bigger size


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: lifeissea/startup-0to1 (version 0.7.27)

--- name: startup-0to1 description: Alias for raon-os — AI-powered startup companion for Korean founders. Install the main package for full functionality. --- # Startup 0→1 (Alias) This is an alias package for **[raon-os](https://clawhub.com/skills/raon-os)**. ## Installation ```bash clawhub install raon-os ``` All features (business plan evaluation, government funding matching, RAG pipeline, Kakao integration) are available in the `raon-os` package. See [raon-os on ClawHub](https://clawhub.com/skills/raon-os) for full documentation.


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

# Design Analysis Skill 自动化设计分析工具，用于分析设计素材（截图、设计稿）并生成结构化的HTML演示文档。 ## When to Use - 需要对设计素材（截图、设计稿）进行结构化分析时 - 需要生成图文并茂的HTML演示文档时 - 需要按照章节分页展示设计分析内容时 - 希望固化「设计分析 + HTML生成」的工作流程时 ## How to Use ### 基本用法 ```javascript // 分析文件夹中的设计素材并生成HTML const result = await designAnalysis({ inputFolder: "~/Desktop/01.DesignAnalysis", outputFile: "~/Desktop/design_analysis.html", title: "设计分析报告", dimensions: { width: 1920, height: 1280 }, layout: { textWidth: 30, imageWidth: 70 } }); ``` ### 参数说明 | 参数 | 类型 | 必填 | 说明 | |------|------|------|------| | `inputFolder` | string | ✅ | 包含设计素材的文件夹路径 | | `outputFile` | string | ✅ | 输出的HTML文件路径 | | `title` | string | ❌ | 演示文档标题（默认：设计分析演示） | | `dimensions` | object | ❌ | 页面尺寸 {width, height}（默认：1920×1280） | | `layout` | object | ❌ | 布局比例 {textWidth, imageWidth}（默认：30/70） | | `sections` | array | ❌ | 自定义章节配置（不传则自动生成） | ### 自定义章节 ```javascript const result = await designAnalysis({ inputFolder: "~/Desktop/design", outputFile: "~/Desktop/analysis.html", sections: [ { title: "设计概览", tags: ["UI/UX", "设计系统"], content: "<h2>项目背景</h2><p>...</p>", image: "screenshot1.png" }, // ... 更多章节 ] }); ``` ### 返回值 ```typescript { success: boolean, outputPath: string, totalPages: number, analysis: { fileCount: number, imageFiles: string[], sections: string[] } } ``` ## Examples ### 示例1：基础使用 ```javascript const result = await designAnalysis({ inputFolder: "~/Desktop/01.DesignAnalysis", outputFile: "~/Desktop/DESIGN_ANALYSIS_DEMO.html" }); ``` ### 示例2：自定义尺寸和布局 ```javascript const result = await designAnalysis({ inputFolder: "~/Desktop/design_materials", outputFile: "~/Desktop/presentation.html", title: "产品设计方案", dimensions: { width: 1920, height: 1080 }, layout: { textWidth: 25, imageWidth: 75 } }); ``` ## Features - ✅ 自动扫描文件夹中的图片文件（支持 PNG、JPG、JPEG、GIF） - ✅ 智能分析图片内容（基于文件名和时间戳） - ✅ 生成多章节HTML演示文档 - ✅ 30/70 分栏布局（文字/图片） - ✅ 侧边导航点和底部控制栏 - ✅ 键盘方向键支持 - ✅ 平滑翻页动画 - ✅ 响应式设计（移动端适配） - ✅ 可自定义页面尺寸和布局比例 - ✅ 支持自定义章节内容 ## Output Structure 生成的HTML包含： ``` ├── Navigation Dock（右侧导航点） ├── Page Controls（底部翻页控制） ├── Pages Container（页面容器） │ ├── Page 1（章节1） │ │ ├── Text Section (30% - 左侧) │ │ └── Image Section (70% - 右侧) │ ├── Page 2（章节2） │ └── ... └── JavaScript（交互逻辑） ``` ## Customization 可以通过参数自定义： - **尺寸**：支持任意分辨率的固定尺寸 - **布局**：文字区和图片区的宽度比例 - **主题色**：修改CSS中的渐变色值 - **字体**：调整字体家族和大小 - **动画**：修改动画时长和效果 ## Limitations - 仅支持本地图片文件（不支持URL） - 图片路径使用绝对路径，跨机器分享需调整 - 单页最大高度1280px（可根据需要调整） - 图片自动缩放，保持原始比例 ## Troubleshooting ### 图片不显示 - 检查图片路径是否正确 - 确认图片文件是否存在 - 查看浏览器控制台错误信息 ### 页面空白 - 检查HTML文件是否完整写入 - 确认浏览器支持ES6语法 - 尝试在不同浏览器中打开 ## See Also - [HTML5 Presentation Patterns](https://developer.mozilla.org/en-US/docs/Web/Guide/HTML/Using_HTML5) - [CSS Flexbox Layout](https://developer.mozilla.org/en-US/docs/Web/CSS/CSS_Flexible_Box_Layout)


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