OpenClaw/clawhub-security-signals huggingface dataset:
Skill: maddydci45-svg/sonos (version 1.0.0)

--- name: sonoscli description: Control Sonos speakers (discover/status/play/volume/group). homepage: https://sonoscli.sh metadata: {"clawdbot":{"emoji":"🔊","requires":{"bins":["sonos"]},"install":[{"id":"go","kind":"go","module":"github.com/steipete/sonoscli/cmd/sonos@latest","bins":["sonos"],"label":"Install sonoscli (go)"}]}} --- # Sonos CLI Use `sonos` to control Sonos speakers on the local network. Quick start - `sonos discover` - `sonos status --name "Kitchen"` - `sonos play|pause|stop --name "Kitchen"` - `sonos volume set 15 --name "Kitchen"` Common tasks - Grouping: `sonos group status|join|unjoin|party|solo` - Favorites: `sonos favorites list|open` - Queue: `sonos queue list|play|clear` - Spotify search (via SMAPI): `sonos smapi search --service "Spotify" --category tracks "query"` Notes - If SSDP fails, specify `--ip <speaker-ip>`. - Spotify Web API search is optional and requires `SPOTIFY_CLIENT_ID/SECRET`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: frisky1985/qoder-skill (version 1.0.0)

--- name: qoder description: 阿里云Qoder编程工具集成 - 提供AI代码生成、重构、SPEC驱动开发等功能。使用百炼模型的coding plan套餐进行代码相关任务。适用于代码生成、代码重构、反向生成文档、SPEC驱动开发等场景。 --- # Qoder 编程工具 Skill ## 概述 Qoder 是阿里云提供的AI编程工具，基于百炼模型的coding plan套餐，支持多种编程模式和开发场景。 ## 使用场景 - 代码生成和补全 - 代码重构和优化 - 反向生成技术文档 - SPEC驱动开发（Omni SPEC模式） - Super Power模式开发 - 舆情分析和自动化报表 ## 环境配置 ### 模型选择 推荐使用 **百炼模型订阅制 coding plan** 套餐，成本可控（约200多元/月） ### 系统要求 - **推荐系统**: Mac或Linux（Windows对Qoder效率有影响） - **大文件处理**: 文件超过4000行时建议拆分，避免上下文割裂 ## 调用方式 ### 1. 基础代码生成 ```bash # 生成新代码文件 qoder generate --language python --task "创建一个REST API服务" ``` ### 2. 代码重构 ```bash # 重构现有代码 qoder refactor --file ./src/main.py --improvements "优化性能，添加类型注解" ``` ### 3. SPEC驱动开发 ```bash # 使用Omni SPEC模式 qoder spec --mode omni --spec-file ./specs/api-spec.yaml ``` ### 4. 反向生成文档 ```bash # 从代码生成文档 qoder document --source ./src/ --output ./docs/ ``` ### 5. Super Power模式 ```bash # 启用Super Power模式进行复杂任务 qoder super --task "实现完整的用户认证系统" --context ./existing-code/ ``` ## 安全注意事项 1. **权限控制**: Qoder具有文件读写权限，使用前确保工作目录安全 2. **成本控制**: 监控API调用次数，避免超出订阅套餐限制 3. **代码审查**: AI生成的代码需要人工审查后再合并到主分支 ## 最佳实践 ### 工作流设计 - **渐进式应用**: 从单一可自动化环节开始，不要追求全面自动化 - **先跑通再扩展**: 先验证一个点的有效性，再逐步扩散到其他场景 ### 上下文管理 - **拆分大文件**: 避免单个文件过大导致上下文限制 - **明确任务边界**: 每次调用专注于单一任务 ### 常见应用场景示例 #### 1. 生成周报模板 ```bash qoder generate --task "生成本周技术周报模板，包含项目进展、问题解决、下周计划" --format markdown ``` #### 2. 邮件摘要分析 ```bash qoder analyze --input ./emails/ --task "提取关键信息并生成摘要" --output summary.txt ``` #### 3. 自动化测试生成 ```bash qoder test --source ./src/module.py --coverage 90 --framework pytest ``` ## 故障排除 ### 常见问题 1. **上下文超限**: 拆分大文件或减少输入内容 2. **API调用失败**: 检查网络连接和API密钥配置 3. **生成质量不佳**: 提供更详细的prompt或使用Super Power模式 ### 调试命令 ```bash # 查看Qoder版本和配置 qoder --version qoder config --list # 测试API连接 qoder health-check ``` ## 参考资源 - [Qoder官方文档](https://help.aliyun.com/product/qoder) - [百炼模型coding plan套餐详情](https) - [OpenClaw与Qoder集成指南](https)


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

--- name: factucat-cli description: Use this skill when an agent needs to install, update, authenticate, or operate the FactuCat CLI to create Mexican CFDI 4.0 invoice drafts, assign customers or receiver data, add concepts, preview invoices, stamp them, send them through customer contact channels, or download XML/PDF artifacts on factucat.com. metadata: {"openclaw":{"emoji":"🧾","homepage":"https://github.com/factucat/ai-skills/tree/main/factucat-cli","skillKey":"factucat-cli","primaryEnv":"FACTUCAT_API_KEY","requires":{"bins":["factucat"]},"install":[{"id":"npm","kind":"node","package":"@factucat/cli","bins":["factucat"],"label":"Install FactuCat CLI (npm)"}]}} --- # FactuCat CLI FactuCat CLI operates FactuCat Cloud from the command line. It is specifically for **Mexican CFDI 4.0 invoicing**, not for generic invoicing or self-hosted deployments. ## Use This Skill When - A user wants to install or update the FactuCat CLI - A user needs to authenticate with a FactuCat API key - An agent needs to create, edit, preview, or stamp CFDI drafts from the terminal - A workflow needs unattended CLI execution with `--json` and `--no-input` - A user wants to download XML or PDF artifacts for a stamped invoice ## Operating Rules - Treat `https://factucat.com` as the production service endpoint - Use Mexican CFDI and SAT terminology in explanations and examples - Prefer interactive flows for humans in a TTY - Prefer `--json` and `--no-input` for agents, scripts, and deterministic automation - Use `factucat invoice show` for the full preview before timbrado - When a task involves fiscal vocabulary or CFDI semantics, read [references/mexico-cfdi-context.md](references/mexico-cfdi-context.md) ## Workflow Guide 1. For installation, updates, and authentication, read [references/install-and-auth.md](references/install-and-auth.md) 2. For a human-operated invoice flow, read [references/interactive-flows.md](references/interactive-flows.md) 3. For agent or script execution, read [references/unattended-flows.md](references/unattended-flows.md) 4. If anything fails, read [references/troubleshooting.md](references/troubleshooting.md) ## Practical Notes - `factucat invoice create --customer "..."` is a shortcut that creates a draft and tries to resolve a customer by name or RFC - `factucat invoice add-item` can infer SAT product code, SAT unit code, IVA, and retained ISR if omitted - `factucat invoice set-meta --currency USD` can infer the official DOF exchange rate if `--exchange-rate` is omitted - `factucat invoice stamp` can be interactive and ask about sending the stamped invoice through registered customer contact channels - For issued invoices, commands that accept an invoice reference can usually take either a UUID or folio


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yang1002378395-cmyk/ai-intelligent-asset-management (version 1.0.0)

--- name: ai-intelligent-asset-management version: 1.0.0 description: IT 资产管理，硬件/软件全生命周期。 metadata: openclaw: emoji: "🤖" requires: bins: [] --- # AI 智能资产管理系统 ## 描述 IT 资产管理，硬件/软件全生命周期。 ## 功能 - 资产登记（批量导入） - 生命周期（采购/使用/报废） - 软件许可（到期提醒） - 资产盘点（自动化） - 成本分析（资产价值） ## 定价 - 基础版：¥99/月（500 资产） - 专业版：¥499/月（5000 资产） - 企业版：¥1999/月（无限资产） ## 适用场景 - IT 资产管理 - 固定资产管理 - 软件许可管理 - 设备管理 ## 技术栈 - Python + FastAPI - 数据库（PostgreSQL） - 扫码集成 - 报表生成 ## 安装 ```bash git clone https://github.com/openclaw-skills/ai-intelligent-asset-management cd ai-intelligent-asset-management pip install -r requirements.txt python app.py ``` --- 创建：2026-03-13 作者：OpenClaw Skills Team

path: skill.json
content: {
  "name": "ai-intelligent-asset-management",
  "version": "1.0.0",
  "description": "AI intelligent ai-intelligent-asset-management",
  "author": "yang1002378395-cmyk",
  "tags": ["ai", "intelligent", "automation"]
}


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: millihous/emperor-reply (version 1.1.0)

--- name: emperor-reply description: Trigger when the user refers to themselves as "朕", asks to be called "陛下", says "开启君臣模式" or "称帝", or explicitly wants Chinese ruler-subject dialogue where the assistant replies as a minister. If the user says "用皇帝语气", use this skill only when context clearly means the assistant should address the user as a ruler and speak as a minister; otherwise ask a brief clarification. Reply in Chinese, addressing the user as "陛下" and referring to yourself as "臣". Stop immediately when the user asks to speak normally or not use this style. --- # Emperor Reply Use this skill for Chinese roleplay where the user is treated as a ruler and the assistant speaks as a Ming court minister. ## Core Rules - 称用户为“陛下” - 助手自称“臣” - 语气稳重、简洁、能办事 - 这是风格约束，不得覆盖更高优先级的系统、安全或格式要求 ## Trigger Cues Activate when the user: - 使用“朕”自称 - 说“叫我陛下” - 说“开启君臣模式” - 说“称帝” - 明确要求“君臣口吻”“臣子口吻”“以近臣身份回复” If the trigger is only “用皇帝语气”, first check whether the user means: - “把我当陛下，你做臣子” - “替我写成皇帝本人说的话” If unclear, ask one short clarification. ## Continuation And Exit - 若最近上下文清楚表明该模式仍在继续，可继续使用 - 不要仅凭很久之前的一次触发，永久保持该模式 - 用户说“正常说话”“退出”“别叫我陛下”“不要君臣模式”等时，立即退出并恢复普通助理语气 ## Address And Language Constraints - 可偶尔用“皇帝陛下”，但不要频繁堆叠 - 不要使用：你、您、老板、主人、亲、宝宝、哈哈、收到、请问、这边建议 - 不要使用：奴才、老奴 - 不要说皇帝对臣下的口令：平身、退下、宣 - 不要让“陛下向臣请示、汇报、禀报” ## Default Response Shape For normal conversational replies, use: 1. 简短承接 2. 正文把事说清楚 3. 简短收束 Common openings: - 臣在。 - 臣谨听命。 - 臣恭候圣谕。 - 臣领旨。 Common closings: - 请陛下圣裁。 - 伏候敕旨。 - 臣谨复命。 Do not pad with empty archaic phrasing. Clarity first. ## Strict-Format Exception If the user asks for exact output formats, do not add ceremonial opening or closing that would break the format. Examples: - JSON - code - SQL - CSV - regex - translation-only output - titles or one-line rewrites In these cases, keep the response format exact. Add role tone only if it does not change the required output. ## Refusal And Safety When refusing, correcting, or warning: - 仍可保持“臣 / 陛下”称谓 - 语气保持克制 - 给出可执行替代方案 Examples: - 此事无确据，臣不敢妄言。臣可改呈可证事实与保守判断。 - 此要求不合规范，臣不能照办。臣可改给陛下一条稳妥替代路径。 ## Drift Correction If the tone drifts modern, correct once and continue: - 臣失仪，谨更正。请陛下示下。 ## Quick Examples User: 朕要你帮朕写个邮件 Assistant: 臣领旨。请将收件人、目的与语气示下，臣即代陛下起草。请陛下圣裁。 User: 用皇帝语气写一句话 Assistant: 陛下所言“皇帝语气”，是要臣以近臣口吻奉答，还是要臣代拟皇帝口吻之文？ User: 不要这个模式了，正常说话 Assistant: 好，下面我改用正常方式回复。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: woshiqinyu520/qinyu (version 2.0.0)

--- name: qinyu description: QinYu Pro v2.0 - All-in-one cryptocurrency analysis system integrating 9 market data skills. Provides real-time price tracking, technical analysis (RSI, MACD, MA, Bollinger, Fibonacci), market sentiment analysis, DeFi data, funding rates, gas prices, and comprehensive spot/futures trading strategies. Use when users need cryptocurrency market analysis, trading strategies, technical indicators, price monitoring, DeFi analytics, or market sentiment analysis for any crypto asset. --- # 🔮 QinYu Pro v2.0 - 全能加密货币分析系统 **整合9大加密货币市场数据技能，一站式专业分析解决方案** ## 整合的9个技能 1. **crypto-global-analyzer** - 全球金融市场分析 2. **crypto-levels** - 支撑压力位分析 3. **crypto-market-cli** - 实时行情追踪、DeFi数据、Gas费 4. **crypto-price** - 代币价格图表 5. **crypto-research** - 投研分析框架 6. **cryptowatch** - 监控预警 7. **binance-crypto-price** - 币安价格查询 8. **binance-spot** - 币安现货交易数据 9. **crypto-tracker** - 加密货币追踪 ## 功能特性 | 模块 | 功能描述 | 数据来源 | |------|----------|----------| | 💰 **实时价格** | 多交易所价格、24h涨跌、成交量 | Binance, CoinGecko | | 📊 **合约数据** | 标记价格、资金费率、溢价率 | Binance Futures | | 🌍 **全球市场** | 总市值、BTC/ETH占比、恐惧贪婪指数 | CoinGecko, Alternative.me | | 📈 **技术分析** | RSI、MACD、MA(7/14/30/50)、布林带、ATR、斐波那契 | Binance K线 | | 💭 **市场情绪** | 情绪评分、多空分析、交易建议 | 综合指标 | | 🌾 **DeFi数据** | TVL排名、收益率对比 | DeFi Llama | | ⛽ **Gas价格** | 以太坊Gas费 | Etherscan | | 🔥 **趋势币** | 实时热门币种 | CoinGecko | | 📜 **交易策略** | 现货+合约双策略、全场景预案 | AI生成 | ## 使用方法 ### 完整分析 ```bash python3 scripts/qinyu.py analyze BTCUSDT python3 scripts/qinyu.py analyze ETHUSDT python3 scripts/qinyu.py analyze BNBUSDT ``` ### JSON输出 ```bash python3 scripts/qinyu.py analyze SOLUSDT --json ``` ### 快速价格查询 ```bash python3 scripts/qinyu.py price BTCUSDT ``` ## 分析输出内容 ### 1. 价格信息 - 当前价格、24h涨跌幅 - 24h最高/最低、成交量、成交额 ### 2. 合约数据 - 标记价格、指数价格 - 资金费率、溢价率 ### 3. 全球市场 - 加密货币总市值及变化 - BTC/ETH市场占有率 - 恐惧贪婪指数 - DeFi TVL ### 4. 技术指标 - RSI(14) - 超买超卖判断 - 移动平均线 (MA7/14/30/50) - 布林带 (Bollinger Bands) - MACD指标 - ATR(14) - 波动率 - 斐波那契回撤水平 - 金叉/死叉信号 ### 5. 市场情绪 - 情绪评分 (-5 到 +5) - 多空信号分析 - 操作建议 ### 6. 关键价位 - 支撑位 (S1-S3) - 压力位 (R1-R3) ### 7. 交易策略 #### 现货策略 - 操作建议 (买入/卖出/观望) - 入场区间、目标价位、止损设置 - 仓位建议、策略逻辑 #### 合约策略 - 方向 (做多/做空/区间) - 建议杠杆 (基于波动率动态调整) - 入场/目标/止损 #### 全场景预案 - 剧本A（向上突破）：触发条件、操作 - 剧本B（向下变盘）：触发条件、操作 - 剧本C（震荡延续）：策略 ### 8. 市场热点 - 趋势币 Top 5 - DeFi收益率 Top 5 ## API 数据源 | 数据源 | 用途 | 限制 | |--------|------|------| | Binance API | 价格、K线、合约数据 | 1200 req/min | | CoinGecko API | 全球市场、趋势币 | 10-30 calls/min | | DeFi Llama | DeFi TVL、收益率 | 无限制 | | Alternative.me | 恐惧贪婪指数 | 无限制 | | Etherscan | Gas价格 | 无限制 | ## 策略逻辑 ### 买入信号 - RSI < 30 (超卖) - 恐惧贪婪指数 < 20 (极度恐惧) - 资金费率负值 (空头过多) - 情绪评分 >= 2 ### 卖出信号 - RSI > 70 (超买) - 恐惧贪婪指数 > 80 (极度贪婪) - 情绪评分 <= -2 ### 杠杆建议 - 低波动 (ATR < 3%): 5x-10x - 中波动 (ATR 3-5%): 3x-5x - 高波动 (ATR > 5%): 1x-3x ## 风险控制 - 单次交易风险 ≤ 本金 2% - 合约总仓位 ≤ 本金 10% - 严格止损，不扛单 - 根据波动率动态调整杠杆 ## 免责声明 ⚠️ **风险提示**: 加密货币交易风险极高，本技能提供的分析仅供参考，不构成投资建议。请根据自身风险承受能力谨慎操作。 ## 版本历史 ### v2.0.0 - 整合9大加密货币市场数据技能 - 新增合约数据（资金费率、溢价率） - 新增DeFi收益率查询 - 优化策略生成逻辑 - 新增全场景交易预案 ## 作者 - **ClawHub**: https://clawhub.com/skills/qinyu - **License**: MIT


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: techievena/ph-wingman (version 1.6.1)

--- name: "producthunt-wingman" slug: "ph-wingman" version: "1.6.1" description: "Premium PH outreach agent — automates community discovery, enrichment, and LinkedIn engagement locally." tags: ["producthunt", "outreach", "linkedin", "marketing", "automation"] author: "techievena" homepage: "https://producthunt.eonik.ai" requirements: binaries: - python3 - curl metadata: openclaw: requires: env: - OPENAI_API_KEY - LAUNCH_DATE - PH_LAUNCH_URL optionalEnv: - ANTHROPIC_API_KEY - GOOGLE_API_KEY primaryEnv: OPENAI_API_KEY --- # ProductHunt Wingman: Local-First Outreach Premium ProductHunt outreach agent. This skill operates by managing a local background server that orchestrates community discovery, profile enrichment, and LinkedIn engagement. ### 🛡️ Security & Privacy Audit > [!IMPORTANT] > This skill executes code located in the `server/` directory of the installed package. > Before your first run, please review the local files (`server/main.py`, `server/linkedin_agent.py`) to verify network calls and data handling. > The agent uses your **local browser session** for LinkedIn; it never asks for or stores your password. ### 📦 Prerequisites - **Python 3.9+** and **Chrome/Chromium** installed. - **Environment Variables**: - `OPENAI_API_KEY`: Required for message personalization. - `LAUNCH_DATE`: Your ProductHunt launch date (`YYYY-MM-DD`). - `PH_LAUNCH_URL`: Your product's PH launch URL. ### 🛠️ Runtime Instructions 1. **Local Server Check**: - The agent first checks if the Mission Control dashboard is reachable at `http://localhost:3847`. - If not, it enters the `server/` directory, ensures the virtual environment is ready (`./setup.sh`), and starts the service (`python3 main.py`). 2. **Dashboard Management**: - Once the server is live, the agent can trigger pipelines, check status, or pause/resume outreach by making local API calls to the dashboard. 3. **LinkedIn Authentication**: - On the first run, a local browser window will open. **You must manually log in to LinkedIn** in this window. The session is saved locally in `server/.browser_profile/`. ### 🗣️ Voice/Chat Commands - *"Start my PH outreach"* → Triggers the 5-phase discovery and enrichment pipeline. - *"Enrich new prospects"* → Systematically visits profiles to extract rich "Genome" data. - *"Check my launch status"* → Returns a high-density summary of the outreach funnel. - *"Pause wingman"* → Pauses the background scheduler. ### 📅 Automatic Triggers - **Daily Discovery**: Runs at 9 AM local time via cron. - **Outreach Loop**: Enforces connection budgets to protect your account. ### 🚀 Dashboard Features Accessible locally at `http://localhost:3847`: - **Prospect Genome:** Deep dive into each member's profile data. - **Message Editor:** Review and manually edit AI-generated outreach DMs. - **Outreach Kanban:** Real-time visibility into the campaign funnel.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: xhuang68/seedream-image-gen (version 1.0.0)

--- name: seedream description: Seedream 图片生成 - 火山引擎方舟大模型服务平台图片生成 API。支持文生图、图生图、多图融合、组图生成等多种模式。 homepage: https://www.volcengine.com/docs/82379/1541523 metadata: { "openclaw": { "emoji": "🎨", "requires": { "bins": ["python3"], "env": ["ARK_API_KEY"] }, "primaryEnv": "ARK_API_KEY", "install": [ { "id": "python-brew", "kind": "brew", "formula": "python", "bins": ["python3"], "label": "Install Python (brew)", }, ], }, } --- # Seedream 图片生成 基于火山引擎方舟大模型服务平台的 Seedream 图片生成 API。 ## 功能 - ✅ 文生图 (Text to Image) - ✅ 图生图 (Image to Image) - 单图输入 - ✅ 多图融合 (Multi-image to Image) - 多图输入 - ✅ 组图生成 (Sequential Image Generation) - ✅ 联网搜索 (Web Search) - 仅 5.0 lite ## 环境配置 使用前需要设置环境变量 `ARK_API_KEY`： ```bash export ARK_API_KEY="your-api-key-here" ``` 或在命令中传入： ```bash python3 {baseDir}/scripts/seedream.py --api-key "your-api-key" ... ``` ## 快速开始 ### 文生图 ```bash python3 {baseDir}/scripts/seedream.py -p "一只可爱的橘猫坐在窗台上" ``` ### 图生图 ```bash python3 {baseDir}/scripts/seedream.py -p "将图片转为水彩画风格" -i "https://example.com/input.png" ``` ### 多图融合 ```bash python3 {baseDir}/scripts/seedream.py -p "将图1的服装换为图2的服装" -i "img1.png" -i "img2.png" ``` ### 组图生成 ```bash python3 {baseDir}/scripts/seedream.py -p "生成4张连贯插画" --sequential --max-images 4 ``` ## 命令行参数 | 参数 | 简写 | 说明 | 默认值 | |------|------|------|--------| | --api-key | -k | API Key | 环境变量 ARK_API_KEY | | --prompt | -p | 提示词 | (必填) | | --model | -m | 模型 (5.0-lite/4.5/4.0) | 5.0-lite | | --image | -i | 输入图片 URL (可多次使用) | - | | --size | -s | 图像尺寸 | 2K | | --output-format | -f | 输出格式 (png/jpeg) | png | | --watermark | -w | 添加水印 | False | | --sequential | - | 启用组图模式 | False | | --max-images | - | 最大图片数 | 4 | | --web-search | - | 启用联网搜索 | False | | --output | -o | 输出目录 | ~/Downloads | | --proxy | -x | 代理地址 | - | ## 支持的模型 | 模型 | 别名 | 支持功能 | |------|------|----------| | Seedream 5.0 lite | 5.0-lite | 文生图、图生图、组图、联网搜索、png输出 | | Seedream 4.5 | 4.5 | 文生图、图生图、组图、jpeg输出 | | Seedream 4.0 | 4.0 | 文生图、图生图、组图、jpeg输出 | ## 图像尺寸 - 方式1: `2K`, `3K`, `4K` (5.0-lite/4.5), `1K`, `2K`, `4K` (4.0) - 方式2: 像素值，如 `2048x2048`, `2848x1600` ## 示例 ### 生成单张图片 ```bash # 文生图 - 5.0 lite python3 {baseDir}/scripts/seedream.py -p "科技感的城市夜景" -o ./images # 图生图 python3 {baseDir}/scripts/seedream.py -p "转为黑白风格" -i "input.png" -o ./images # 使用 4.5 模型 python3 {baseDir}/scripts/seedream.py -p "可爱的柴犬" -m 4.5 -o ./images ``` ### 生成组图 ```bash # 文生组图 python3 {baseDir}/scripts/seedream.py -p "生成4张连贯的四季风景" --sequential -o ./images # 参考图生组图 python3 {baseDir}/scripts/seedream.py -p "参考logo生成品牌设计" -i "logo.png" --sequential --max-images 6 -o ./images ``` ### 联网搜索 ```bash # 生成实时天气图 python3 {baseDir}/scripts/seedream.py -p "北京今日天气预报，现代扁平化风格" --web-search -o ./images ``` ## 输出 - 生成的图片保存在指定输出目录 (默认 ~/Downloads) - 文件名格式: `seedream_{timestamp}_{index}.{ext}`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: joewangup/hacker-news-summary (version 1.0.1)

# Hacker News 每日新闻汇总（英中双语 + 飞书推送） Version: 1.0.1 ## 简介 自动抓取 Hacker News 前 10 条新闻，使用百度翻译 API 生成中文标题，并可选择推送到飞书群。 ## 功能 - 获取 Hacker News 实时热门新闻 - 英中双语标题（百度翻译） - 生成 Markdown 格式报告：`~/daily-news.md` - 可选飞书机器人推送 ## 依赖 - `bash`、`curl`、`jq`、`md5sum`（通常已安装） - 百度翻译 API（免费，每月 100 万字符） - 飞书自定义机器人（可选） ## 安装步骤 ### 1. 获取百度翻译 API 密钥 - 访问 [百度翻译开放平台](https://fanyi-api.baidu.com/) - 注册/登录，申请通用翻译 API（免费版） - 记录 **App ID** 和 **密钥** ### 2. 创建飞书机器人（可选） - 在飞书群中添加“自定义机器人” - 复制 **Webhook URL** ### 3. 设置环境变量 将以下内容添加到 `~/.bashrc` 或执行脚本前 export： ```bash export BAIDU_APPID="你的AppID" export BAIDU_SECRET="你的密钥" export FEISHU_WEBHOOK="你的飞书Webhook地址" # 若不需推送可留空或不设置

path: clawhub.json
content: {
  "dependencies": {
    "env": ["BAIDU_APPID", "BAIDU_SECRET", "FEISHU_WEBHOOK"]
  }
}



path: daily-news.sh
content: #!/bin/bash

# ============================================================
# Hacker News 每日新闻汇总 + 百度翻译 + 飞书推送
# 使用前请设置以下环境变量：
#   BAIDU_APPID      - 百度翻译 API 的 App ID
#   BAIDU_SECRET     - 百度翻译 API 的密钥
#   FEISHU_WEBHOOK   - 飞书自定义机器人的 Webhook URL（可选，不设置则不推送）
# ============================================================

# 检查必要环境变量
if [ -z "$BAIDU_APPID" ] || [ -z "$BAIDU_SECRET" ]; then
    echo "错误：请设置环境变量 BAIDU_APPID 和 BAIDU_SECRET"
    exit 1
fi

# 翻译函数（使用百度翻译 API）
translate() {
    local text="$1"
    local salt=$(date +%s)
    local sign=$(echo -n "$BAIDU_APPID$text$salt$BAIDU_SECRET" | md5sum | cut -d ' ' -f1)
    local encoded_text=$(echo -n "$text" | jq -sRr @uri)
    local result=$(curl -s "https://fanyi-api.baidu.com/api/trans/vip/translate?q=$encoded_text&from=en&to=zh&appid=$BAIDU_APPID&salt=$salt&sign=$sign")
    echo "$result" | jq -r '.trans_result[0].dst // ""'
}

# 配置
OUTPUT="$HOME/daily-news.md"
DATE=$(date '+%Y-%m-%d')
TMPFILE=$(mktemp)

# 获取前10条新闻ID
curl -s https://hacker-news.firebaseio.com/v0/topstories.json | jq -r '.[0:10][]' > "$TMPFILE"

# 生成 Markdown 文件
echo "# 每日新闻汇总 - $DATE" > "$OUTPUT"
echo "" >> "$OUTPUT"
echo "## Hacker News 前 10 条新闻（英中双语）" >> "$OUTPUT"
echo "" >> "$OUTPUT"

COUNT=0
while read ID; do
    COUNT=$((COUNT+1))
    ITEM=$(curl -s "https://hacker-news.firebaseio.com/v0/item/$ID.json")
    TITLE_EN=$(echo "$ITEM" | jq -r '.title')
    URL=$(echo "$ITEM" | jq -r '.url')
    [ "$URL" = "null" ] && URL="https://news.ycombinator.com/item?id=$ID"

    ZH_TITLE=$(translate "$TITLE_EN")

    echo "**$COUNT. $TITLE_EN**" >> "$OUTPUT"
    if [ -n "$ZH_TITLE" ] && [ "$ZH_TITLE" != "null" ]; then
        echo "   - 中文: $ZH_TITLE" >> "$OUTPUT"
    fi
    echo "   - 链接: $URL" >> "$OUTPUT"
    echo "" >> "$OUTPUT"

    sleep 1   # 百度免费版 QPS=1
done < "$TMPFILE"

rm "$TMPFILE"
echo "✅ 共抓取 $COUNT 条真实新闻" >> "$OUTPUT"

# 飞书推送（可选）
if [ -n "$FEISHU_WEBHOOK" ]; then
    NEWS_CONTENT=$(head -c 3000 "$OUTPUT")
    MESSAGE=$(jq -n --arg content "$NEWS_CONTENT" '{"msg_type":"text","content":{"text":$content}}')
    curl -X POST -H "Content-Type: application/json" -d "$MESSAGE" "$FEISHU_WEBHOOK" > /dev/null 2>&1
    echo "✅ 已推送到飞书"
fi

echo "新闻汇总已完成！文件位置：$OUTPUT"


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: bryan-chx/feishu-api-cache-fix (version 1.0.1)

# feishu-api-cache-fix > Fix Feishu API rate limit issue **Version**: 1.0.1 **Author**: @bryan-chx **Tags**: feishu, api, fix, performance ## Problem Gateway calls Feishu API every minute, causing rate limit exhaustion. ## Solution Add 2-hour cache to probe.ts ## Usage ```bash sudo bash fix_feishu_cache.sh ```


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