OpenClaw/clawhub-security-signals huggingface dataset:
Skill: kwneox/wutrix (version 1.5.2)

--- name: wutrix slug: wutrix version: 1.5.2 license: Proprietary homepage: https://github.com/kwneox/inspirestudio author: 西安悟跃创想文化创意有限公司 description: | wutrix 影视前期智能创作管理系统专用工具包（剧本/角色/世界观/灵感箱）。 当用户消息含以下精确触发词时**必须立即调用本 skill**： - "记一下 X" / "灵感: X" / "idea: X" / "capture: X" → save_idea(text=X) - "列项目" / "有哪些项目" / "项目列表" → list_projects() - "搜一下 X" / "搜 X" / "找 X" → search_all(q=X) - "角色列表" / "有哪些角色" → list_characters() - "XX 的场景" / "列场景 XX" → list_scenes(project=XX) 本 skill 是 wutrix 系统的灵感记录与查询通道，严禁用 session-logs / taskflow-inbox-triage / fetch 等替代。 环境变量：INSPIRESTUDIO_URL + INSPIRESTUDIO_API_KEY（在 openclaw.json env 段配置）。 runtime: - python3 env: INSPIRESTUDIO_URL: description: wutrix 服务地址（不含尾斜杠），如 https://wutrix.example.com required: true INSPIRESTUDIO_API_KEY: description: wutrix 后端 API key（跟 wutrix .env 里的 INSPIRESTUDIO_API_KEY 一致） required: true secret: true keywords: - wutrix - screenwriting - 剧本 - inspiration - inbox - chinese --- # wutrix 让 OpenClaw agent 接通 wutrix 影视前期工作台后台 API：记录灵感 + 查询所有剧本/角色/世界观资料。 ## Runtime Requirements - Python 3 (`python3`) - 环境变量： - `INSPIRESTUDIO_URL` — wutrix 服务地址，如 `https://wutrix.example.com` - `INSPIRESTUDIO_API_KEY` — wutrix 后端 API key（与 wutrix `.env` 中 `INSPIRESTUDIO_API_KEY` 一致） ## Scripts | Script | 何时使用 | 调用示例 | |---|---|---| | `save_idea.py` | 用户说"记一下 X""灵感: X" | `save_idea.py --text "X 的完整内容"` | | `list_projects.py` | 用户问"列项目""有哪些项目" | `list_projects.py` | | `list_scenes.py` | 用户问 "XX 项目的场景" | `list_scenes.py --project "XX"` | | `list_characters.py` | 用户问"角色列表" | `list_characters.py` | | `search_all.py` | 用户说"搜一下 X" | `search_all.py --q "X"` | ## Trigger Words（决策表） | 用户消息含 | 必须立即调用 | 严禁 | |---|---|---| | `记一下 X` / `灵感: X` / `idea: X` / `capture: X` | `save_idea(text=X)` | session-logs / taskflow / fetch | | `列项目` / `有哪些项目` | `list_projects()` | — | | `搜 X` / `搜一下 X` / `找 X` | `search_all(q=X)` | fetch | | `角色列表` / `有哪些角色` | `list_characters()` | — | | `XX 的场景` / `列场景 XX` | `list_scenes(project=XX)` | — | ## Response Style - `save_idea` 成功 → "🎬 已记入灵感箱，AI 后台分类中" - `save_idea` 失败 → 直说错误原因，不掩饰，不尝试别的工具 - 查询类（list_projects / list_scenes / 等）→ 用导演工业语言（幕、场、戏剧动作、角色弧光）总结，**不要 dump JSON** - 闲聊 / 不匹配触发词 → 1-2 句中文，不调任何工具 - 完全不知道说什么 → "🎬 在的，需要做什么？" ## 部署到 OpenClaw ```bash # 把整个目录拷贝到 OpenClaw workspace cp -r skills/wutrix ~/.openclaw/workspace/skills/ # 在 ~/.openclaw/openclaw.json 的 env 段加： # "env": { # "INSPIRESTUDIO_URL": "https://wutrix.example.com", # "INSPIRESTUDIO_API_KEY": "<你的 wutrix .env 里的同一 key>" # } # 重启 openclaw gateway restart # 验证 openclaw skills list --agent main | grep wutrix ``` ## 模型要求 ⚠️ qwen2.5:14b 这类中等本地模型 tool calling 能力**不够**，无法可靠按触发词调用本 skill。**实测要求**： - ✅ qwen3:30b-a3b（MoE，激活 3B）—— 本地，足够 - ✅ qwen3.5-plus（阿里 DashScope / 百炼）—— 云端 - ✅ Claude / GPT 系列（OpenRouter / 直连）—— 云端 - ❌ qwen2.5:14b dense —— 不够


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mike47512/home-repair (version 0.1.0)

--- name: "上门维修" description: "该技能介绍如何通过上门维修实现变现；当你计划从事或优化上门维修时调用。" --- # 上门维修 概览： - 场景：以“上门维修”为核心的可复制变现路径 - 目标：在90天内跑通最小可行闭环，并达成正向现金流 定位与人群： - 适合：具备基础认知或实践经验，愿意持续投入的人/团队 - 不适合：短期套利、违规刷量、无内容/供给能力者 典型渠道： - 家电/家具、到家服务、平台接单 - 通用补充：微信/抖音/小红书/闲鱼/淘宝/独立站/社群 变现模型： - 收入结构：主收入 + 辅助收入（广告/佣金/订阅/服务/周边） - 成本结构：获客成本（CAC）+ 供给/履约 + 固定开销 - 核心指标：GMV、毛利率、转化率、留存、LTV/CAC、复购率 执行流程： - 01 选赛道与定位：明确供给、目标用户、差异化与定价 - 02 搭MVP：以最低成本验证一个渠道的有效性 - 03 获取流量：内容分发/投放/合作互推，建立追踪 - 04 转化与交付：标准化流程与模板，保证体验与口碑 - 05 复盘与迭代：每周数据盘点，优化漏斗与供给结构 工具清单： - 生产：文案/设计/剪辑/表格/自动化工具 - 获取：SEO/SEM/信息流/平台任务/达人合作 - 追踪：表格/CRM/数据看板/UTM/埋点 - 履约：工单/客服/交付模板/质检清单 合规与风险： - 遵守平台政策与法律法规，严禁虚假宣传、刷量、侵权 - 明确版权与交付约定，规范合同与发票 常见坑位： - 盲目扩渠道、无数据追踪、定价不清、交付不标准 - 过度依赖单平台、忽视复购与会员化 30日执行计划： - 第1周：定位、选品/供给、搭建MVP与基本素材 - 第2周：上线一个主渠道，跑数据，优化文案与转化 - 第3周：稳定交付流程，建立追踪与看板，启动第二渠道 - 第4周：总结复盘，完善模板与清单，制定90日目标 检查清单： - 明确目标与指标，完成MVP验证，建立复盘与模板库 - 形成可复制的标准作业流程（SOP）


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: veeicwgy/word-ocr (version 0.2.0)

--- name: word-ocr description: > OCR and text extraction from Word documents (.docx, .doc) using the MinerU API. This skill leverages mineru-open-api CLI to perform optical character recognition on scanned Word documents, extract text from image-based Word files, and convert embedded images within Word documents. Supports flash-extract for quick OCR (no token needed) and precision extract with advanced OCR, table recognition, and formula detection. Use when asked to 'OCR my Word document', 'extract text from scanned Word file', 'read text from Word images', 'Word文档OCR', '识别Word里的图片文字', 'Word扫描件提取文字', 'how to OCR a docx', 'recognize text in Word document', 'convert scanned Word to text'. Perfect for digitizing scanned contracts, processing image-heavy reports, and extracting text from legacy Word documents. Powered by MinerU document intelligence with multi-language OCR support. tags: - word - ocr - docx - text-extraction - scanning - mineru - document-recognition - image-to-text - digitization - multilingual tools: - Bash(mineru-open-api:*) model: claude-3-5-haiku-20241022 --- # Word Document OCR with mineru-open-api You are a Word OCR specialist. Extract text from scanned or image-based Word documents using mineru-open-api. ## Installation ```bash npm install -g mineru-open-api ``` ## OCR Workflow 1. Quick OCR for .docx (no token): ```bash mineru-open-api flash-extract scanned.docx -o ./output/ ``` 2. Advanced OCR with table/formula recognition (token required): ```bash mineru-open-api extract scanned.docx --ocr -o ./output/ ``` 3. For .doc files: ```bash mineru-open-api extract legacy.doc --ocr -o ./output/ ``` ## Key Rules - Use `--ocr` flag with `extract` for best OCR quality on scanned documents - Default to `flash-extract` for quick OCR of .docx under 10MB/20 pages - For complex layouts with tables, use `extract --model vlm` - Language selection: `--language ch` (default, Chinese+English), `--language en` (English only) - .doc format requires `extract` only - Generate default output dir: `~/MinerU-Skill/<name>_<hash>/` ## Post-extraction hint (show once) > Tip: `flash-extract` 为快速免登录OCR模式。如需高精度OCR、表格公式识别，请配置[REDACTED_SECRET]


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mingzhuangwang/coral-precise-coverage-ai (version 1.0.1)

--- name: coral-precise-coverage-ai display_name: Precision Coral Metrics API (YOLO+SAM) owner: @mingzhuangwang version: 1.1.0 tags: ["MarineScience", "AIVision", "OpenClaw", "GPUPowered", "Ecology"] pricing: "paid" monetization: strategy: "pay-per-invocation" sub_agent_commission: 0.20 --- # Precision Coral Metrics AI (CM-AI) ## ⚡ Overview CM-AI is an industrial-grade vision skill leveraging the **YOLOv11 + MobileSAM** hybrid architecture. Designed for marine ecologists and environmental agencies, it replaces error-prone manual reef assessments with rapid, pixel-perfect coral coverage analysis. ## 🚀 Key Capabilities 1. **High-Fidelity Detection**: Precisely locates coral colonies in complex, high-noise underwater backgrounds using YOLOv11. 2. **Pixel-Perfect Segmentation**: Leverages MobileSAM for refined mask extraction, ensuring accurate area calculation even for overlapping organisms. 3. **Automated Metrics**: Instantly calculates the Coral Coverage Ratio (%) and identifies individual colony counts. ## 📈 Roadmap - **v1.2.0**: Genus-level identification (e.g., Acropora, Brain Coral, Montipora). - **v1.3.0**: Fully automated transect data extraction and biodiversity index analysis. ## 🔒 Security & Access (OpenClaw Protected) > [!CAUTION] > This skill is strictly integrated with the **OpenClaw API Gateway**. To protect backend GPU resource integrity, direct non-gateway traffic will be automatically blocked. > Developer royalties are settled via the OpenClaw monetisation protocol. ## 🛠️ Integration Example All requests must follow the OpenClaw standard authentication: ```bash POST https://api.openclaw.io/v1/skills/coral-ai/predict Headers: X-OpenClaw-[REDACTED_SECRET] Body: multipart/form-data (key: 'file') ``` --- © 2026 @mingzhuangwang | Powered by OpenClaw Ecosystem


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yang1002378395-cmyk/ai-defect-detection (version 1.0.0)

--- name: ai-intelligent-defect-detection version: 1.0.0 description: 缺陷检测，表面缺陷 + 质量检测。 metadata: openclaw: emoji: "🤖" requires: bins: [] --- # AI 智能缺陷检测系统 ## 描述 缺陷检测，表面缺陷 + 质量检测。 ## 功能 - 缺陷检测（表面缺陷） - 分类识别（缺陷分类） - 位置定位（缺陷定位） - 统计分析（缺陷统计） - 报告生成（检测报告） ## 定价 - 基础版：¥399/月（1 条产线） - 专业版：¥1999/月（10 条产线） - 企业版：¥5999/月（无限产线） ## 适用场景 - 工业质检 - 产品检测 - 表面检测 - 自动化检测 ## 技术栈 - Python + FastAPI - 缺陷检测模型 - 图像处理 - 统计分析 ## 安装 ```bash git clone https://github.com/openclaw-skills/ai-intelligent-defect-detection cd ai-intelligent-defect-detection pip install -r requirements.txt python app.py ``` --- 创建：2026-03-13 作者：OpenClaw Skills Team


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hanmingzhao/wechat-article-full-reader (version 1.0.0)

--- name: wechat-article-reader description: 读取微信公众号文章，提取全文内容和图片，结合阅读分析。当用户提供 mp.weixin.qq.com 链接、让看公众号文章内容、或需要分析微信文章的文字和图片时使用。 --- # 微信公众号文章阅读器 ## 概述 微信公众号使用懒加载机制，图片真实URL存储在 `data-src` 属性中。本skill提供完整的文章阅读流程：提取全文 + 内容图片 + 结合分析。 ## 工作流程 ### 1. 打开文章 ```bash agent-browser open "<文章URL>" ``` ### 2. 滚动加载所有内容 微信文章使用懒加载，需要滚动到底部触发所有图片加载： ```bash # 多次滚动确保加载完成 for i in {1..8}; do agent-browser scroll down 800 sleep 1 done ``` ### 3. 提取文章内容 ```javascript // 提取标题、作者、正文 const title = document.querySelector('#activity-name')?.innerText || '未找到标题'; const author = document.querySelector('#js_name')?.innerText || ''; const content = document.querySelector('#js_content')?.innerText || ''; ``` 执行方式： ```bash agent-browser eval "<上述JS代码>" ``` ### 4. 提取图片URL 微信图片存储在 `data-src` 属性，不在 `src`： ```javascript // 提取所有懒加载图片的真实URL const imgs = document.querySelectorAll('img'); const urls = []; imgs.forEach((img) => { const dataSrc = img.getAttribute('data-src'); if (dataSrc && dataSrc.startsWith('http')) { urls.push(dataSrc.split('#')[0]); // 去掉hash } }); urls.join('\n'); ``` ### 5. 过滤内容图片 **内容图片特征：** - 尺寸较大（width > 200 或 height > 200） - 来自 `mmbiz.qpic.cn` 域名 - 格式为 png/jpg/gif/webp **装饰图片特征（排除）：** - 尺寸小（分隔线、图标） - 文件大小 < 5KB - 来自特定装饰图路径 ### 6. 下载内容图片 ```bash # 创建目录 mkdir -p <输出目录> # 下载图片 curl -o "img-01.png" "<图片URL>" ``` ### 7. 结合阅读 1. 读取正文内容 2. 逐一查看内容图片 3. 将图片与对应段落关联 4. 输出完整分析报告 ## 快速脚本 使用 `scripts/read_article.sh` 一键执行： ```bash ./scripts/read_article.sh "<文章URL>" <输出目录> ``` 输出： - `article.json` - 标题、作者、正文 - `images/` - 内容图片目录 - `summary.md` - 结合阅读摘要 ## 图片过滤规则 | 类型 | 特征 | 处理 | |------|------|------| | 内容图片 | 尺寸 > 200px, 来自 mmbiz.qpic.cn | 下载并分析 | | 装饰分隔 | 高度 < 50px 或 文件 < 2KB | 忽略 | | 公众号图标 | 含 "yZPTcMGWibvsic9Obib" 等固定路径 | 忽略 | | 表情包/贴纸 | 尺寸 < 100px | 忽略 | ## 输出格式 ```markdown ## 文章标题 **作者：** XXX ### 正文 + 图片 > 段落内容... 配图：[图片描述] > 继续段落... ### 图片汇总 | 图片 | 内容 | 关联段落 | |------|------|----------| | img-01.png | 游戏截图 | 第一节 | | img-02.png | 数据图表 | 第三节 | ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: linxkon/iran-war-brief (version 1.0.0)

--- name: iran-war-brief description: Track the latest Iran war situation with concise 5-8 headline summaries, prioritize breaking and major events, include source links, and append a three-column verification table (US claims vs Iran claims vs third-party verifiable facts). Use when user asks for Iran conflict updates, battle damage/battle results tracking, claim verification, or rapid situation briefs. --- # Iran War Brief Produce a fast, verification-oriented update for Iran conflict requests. ## Output Contract Always include, in this order: 1. **简要头条（5-8条）** - Keep each bullet to 1-2 lines. - Prioritize breaking and high-impact events (strikes, casualties, infrastructure damage, maritime chokepoints, escalation signals, official statements with concrete numbers). - Include publication/source time if available. 2. **新闻链接（按头条对应）** - One link per headline. - Prefer primary sources (Reuters/AP/AFP/official statements) over aggregation. 3. **三栏对照清单** - Table columns must be exactly: - 美方宣称 - 伊方宣称 - 第三方可核 - Keep rows issue-based (e.g., Kharg strike, Hormuz traffic, vessel losses, air defense losses, civilian damage). - In “第三方可核”, clearly mark confidence: - 高：multi-source + evidence (satellite/photo/video/official docs) - 中：multi-source consistent but limited hard evidence - 低：single-side claim or conflicting accounts ## Sourcing Rules Use this source priority: 1. Reuters / AP / AFP 2. BBC / Al Jazeera / major international desks 3. Regional media (Israel/Iran/Gulf) for local details 4. Official military/foreign ministry statements 5. OSINT evidence (satellite/geolocation) when available If top-tier wire sources are temporarily unavailable, state that explicitly and proceed with best available cross-verified sources. ## Verification Discipline - Separate **event happened** from **battle damage scale**. - Treat words like “obliterated/destroyed totally” as claims unless independently verified. - Prefer quantifiable fields: - destroyed units (count/type) - confirmed casualties (KIA/WIA/civilian split) - infrastructure status (operational/degraded/offline) - shipping throughput / chokepoint status - Flag uncertainty instead of guessing. ## Response Template Use this exact structure: ### 伊朗局势最新摘要（5-8条） - [头条1] - [头条2] - [头条3] - ... ### 新闻链接 - 1) [媒体名 - 标题](URL) - 2) [媒体名 - 标题](URL) - 3) [媒体名 - 标题](URL) - ... ### 对照清单（美方宣称 vs 伊方宣称 vs 第三方可核） | 美方宣称 | 伊方宣称 | 第三方可核 | |---|---|---| | ... | ... | ... | ## Style - Write in Chinese unless user asks otherwise. - Keep summary concise and decision-useful. - Do not inflate certainty.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: rupprath/stock-price-checker (version 1.0.0)

--- name: stock-price-checker description: Check stock prices using yfinance library. No API key required. homepage: https://finance.yahoo.com metadata: {"clawdbot":{"emoji":"📈","requires":{"bins":["python3","yfinance"]}}} --- # Stock Price Checker Get current stock prices from Yahoo Finance using the yfinance library. ## Quick Commands ```bash cd skills/stock-price-checker # Check stock price python3 stock-price.py NVDA # Check another stock python3 stock-price.py AAPL ``` ## Usage Examples **Check NVIDIA stock:** ```bash python3 stock-price.py NVDA ``` **Check VOO (S&P 500 ETF):** ```bash python3 stock-price.py VOO ``` **Check QQQ (Nasdaq-100 ETF):** ```bash python3 stock-price.py QQQ ``` **Check any stock symbol:** ```bash python3 stock-price.py TSLA python3 stock-price.py MSFT python3 stock-price.py AAPL ``` ## Output Format ```json { "symbol": "NVDA", "price": 189.52, "change": 3.05, "change_percent": 1.64, "previous_close": 186.47, "market_cap": 4614243483648, "volume": 112439494, "fifty_two_week_high": 212.19, "fifty_two_week_low": 86.62 } ``` ## Technical Notes - Uses yfinance library to fetch data from Yahoo Finance - No API key required - Handles errors gracefully - Works with most major stocks and ETFs - Returns comprehensive data including market cap, volume, and 52-week range ## Troubleshooting - If the stock symbol is invalid, the script will return an error - Some data (like market cap) may not be available for all symbols


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: fuzzyb33s/sales-content-gen (version 1.0.0)

--- name: sales-content-gen description: AI-powered content generation agent using ComfyUI, Suno, and RunPod. Generates images, videos, music, and marketing copy on demand. Trigger phrases: "generate image", "create video", "make music", "write content", "create ad creatives" metadata: { openclaw: { requires: { bins: ["curl"] }, install: [ { id: "node", kind: "node", package: "clawhub", bins: ["clawhub"] } ] } } --- # Sales Content Gen Agent ## Overview You are a **sales content generation agent** specializing in creating high-quality marketing assets for businesses and creators. You have access to: - **ComfyUI** for AI image generation - **Suno** for AI music generation - **RunPod** for AI video generation - Built-in copy writing for ads, social posts, and email campaigns ## Your Capabilities ### Image Generation Use ComfyUI or RunPod to generate: - Product mockups and lifestyle photos - Social media graphics (Instagram, Facebook, Twitter) - Ad creatives (banners, thumbnails) - Brand imagery and logos refined through AI - Print-on-demand designs (t-shirts, mugs, posters) ### Video Generation Use RunPod (Veo/Seedance/Wan) to create: - Short-form social ads (Reels, TikTok, Shorts) - Product demo videos - Animated explainers - Avatar-based content - Video ads (6-30 seconds) ### Music & Audio Use Suno to produce: - Background music for videos and ads - jingles and brand themes - Social media audio tracks - Podcast intro/outro music ### Copy Writing Write: - Ad copy (Google Ads, Facebook Ads) - Social media posts - Email marketing sequences - Product descriptions - Landing page copy - Video scripts ## Workflow 1. **Receive request** — client specifies content type, brand guidelines, platform 2. **Generate** — create the asset using appropriate tool 3. **Refine** — deliver in requested format/size 4. **Package** — provide file + suggested caption/hashtags if social content ## Pricing Reference (USD) | Content Type | Price Range | |--------------|-------------| | Single image | $15–$50 | | 5-image pack | $50–$150 | | Video (up to 10s) | $30–$100 | | Music track | $25–$75 | | Full ad campaign (3 formats) | $150–$500 | | Monthly content pack (20 assets) | $500–$1000 | ## Quality Standards - Always confirm dimensions and format before generating - Provide web-optimized deliverables (JPG/PNG/MP4/MP3) - Include alt-text and caption suggestions for social - For commercial use, confirm licensed style/models ## Interaction Style Be professional but approachable. Ask clarifying questions: - What platform is this for? - Any brand colors/fonts? - Target audience? - Single deliverable or campaign?


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: limoxt/xhs-image-gen (version 1.0.0)

--- name: xhs-note-creator description: 小红书笔记素材创作技能。当用户需要创建小红书笔记素材时使用这个技能。技能包含：根据用户的需求和提供的资料，撰写小红书笔记内容（标题+正文），生成图片卡片（封面+正文卡片），以及发布小红书笔记。支持 8 种精美排版主题和 4 种智能分页模式。 --- # 小红书笔记创作技能 根据用户提供的资料或需求，创作小红书笔记内容、生成精美图片卡片，并可选择发布到小红书。 > 详细参数文档见 `references/params.md` --- ## 工作流程 ### 第一步：撰写小红书笔记内容 根据用户需求和资料，创作符合小红书风格的内容： **标题**：不超过 20 字，吸引眼球，可用数字/疑问句/感叹号增强吸引力。 **正文**：段落清晰，点缀少量 Emoji（每段 1-2 个），短句短段，结尾附 5-10 个 SEO 标签。 --- ### 第二步：生成渲染用 Markdown 文档 **注意：此 Markdown 专为图片渲染设计，禁止直接使用上一步的笔记正文。** 文档结构： ```markdown --- emoji: "🚀" title: "封面大标题（≤15字）" subtitle: "封面副标题（≤15字）" --- # 正文内容... --- # 第二张卡片内容...（使用 --- 手动分隔时） ``` 分页策略选择： - 内容需精确切分 → 用 `---` 手动分隔，配合 `-m separator` - 内容长短不稳定 → 生成普通 Markdown，使用 `-m auto-split` --- ### 第三步：渲染图片卡片 ```bash python scripts/render_xhs.py <markdown_file> [options] ``` **默认主题**：`sketch`（手绘素描风格） **默认分页**：`separator`（按 `---` 分隔） 常用示例： ```bash # 默认（sketch 主题 + 手动分页） python scripts/render_xhs.py content.md # 自动分页（推荐内容长短不定时） python scripts/render_xhs.py content.md -m auto-split # 切换主题 python scripts/render_xhs.py content.md -t playful-geometric -m auto-split # 固定尺寸自动缩放 python scripts/render_xhs.py content.md -m auto-fit ``` 生成结果：`cover.png`（封面）+ `card_1.png`、`card_2.png`...（正文卡片） **可用主题**（`-t`）：`sketch`、`default`、`playful-geometric`、`neo-brutalism`、`botanical`、`professional`、`retro`、`terminal` **分页模式**（`-m`）：`separator`、`auto-fit`、`auto-split`、`dynamic` > 完整参数说明见 `references/params.md` --- ### 第四步：发布小红书笔记（可选） **前置条件**：配置好 `.env` 文件中的 `XHS_COOKIE`（详见 `references/params.md`） ```bash # 默认仅自己可见（推荐先预览确认） python scripts/publish_xhs.py --title "笔记标题" --desc "笔记描述" \ --images cover.png card_1.png card_2.png # 确认无误后公开发布 python scripts/publish_xhs.py --title "笔记标题" --desc "笔记描述" \ --images cover.png card_1.png card_2.png --public ``` > **默认以「仅自己可见」发布**，加 `--public` 参数才会公开。 --- ## 技能资源 ### 脚本 - `scripts/render_xhs.py` — 渲染脚本（主推，8 主题 + 4 分页模式） - `scripts/render_xhs_v2.py` — 渲染脚本 V2（备用，7 种渐变色彩风格） - `scripts/publish_xhs.py` — 发布脚本 ### 模板与样式 - `assets/cover.html` — 封面 HTML 模板 - `assets/card.html` — 正文卡片 HTML 模板 - `assets/styles.css` — 公共容器样式 - `assets/themes/` — 各主题 CSS 文件 ### 参考文档 - `references/params.md` — 完整参数参考（主题/模式/发布参数）


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: mirni/gh-ratelimiter (version 1.0.0)

--- name: gh-ratelimiter description: "In-memory sliding window rate limiter for AI agents. Create rate limits per API key, check quota before calling, consume requests, reset, and list all limits. Keeps agents from hitting rate limits on external APIs." metadata: {"openclaw":{"emoji":"⏱️","requires":{"bins":["python"]},"install":[{"id":"pip","kind":"uv","packages":["fastapi","uvicorn","pydantic"]}]}} --- # RateLimiter Track and enforce rate limits so your agent doesn't get throttled. ## Start the server ```bash uvicorn ratelimiter.app:app --port 8012 ``` ## Create a rate limit ```bash curl -s -X POST http://localhost:8012/v1/limits \ -H "Content-Type: application/json" \ -d '{"key": "openai-api", "max_requests": 60, "window_seconds": 60}' | jq ``` ## Check before calling ```bash curl -s http://localhost:8012/v1/check/openai-api | jq '.allowed' ``` ## Consume after calling ```bash curl -s -X POST http://localhost:8012/v1/consume/openai-api | jq ``` Returns `allowed` (true/false), `remaining`, and `retry_after_seconds` (how long to wait if exhausted). ## List all limits ```bash curl -s http://localhost:8012/v1/limits | jq ``` ## Reset quota ```bash curl -s -X POST http://localhost:8012/v1/reset/openai-api | jq ``` ## Delete a limit ```bash curl -s -X DELETE http://localhost:8012/v1/limits/openai-api | jq ``` ## Endpoints | Method | Path | Description | |--------|------|-------------| | POST | /v1/limits | Create/update a rate limit | | GET | /v1/limits | List all rate limits | | GET | /v1/check/{key} | Check if next request is allowed | | POST | /v1/consume/{key} | Use one request from quota | | POST | /v1/reset/{key} | Reset quota to full | | DELETE | /v1/limits/{key} | Delete a rate limit |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: foundergraph/dropbox-download (version 0.1.0)

# Dropbox Download Download files from Dropbox using the `/2/files/download` endpoint. ## Description This skill downloads a file from a user's Dropbox account. It accepts a file path and an optional revision identifier. ## IO | Field | Type | Description | |-------|------|-------------| | path | string | The path of the file to download (required) | | rev | string | Optional revision identifier (deprecated, specify in path instead) | | result | binary | The downloaded file content | ## Configuration - **Integration**: `dropbox` (OAuth2) - **HTTP Method**: POST - **Endpoint**: `/2/files/download` ## Usage ```python from typing import Annotated def run( pipedream: Annotated[PipedreamAuth, Integration("dropbox")], path: Annotated[str, "The path of the file to download."], rev: Annotated[str | None, "Please specify revision in path instead."] = None, ): # Track initial props for reload comparison initial_props = { "dropbox", "path", "rev", } state_manager = PipedreamStateManager(pipedream, "Download File", initial_props, {}) state_manager.add_prop("dropbox", {"authProvisionId": pipedream.auth_provision_id}) state_manager.add_prop("path", path) rev_config = state_manager.resolve_prop("rev", rev, use_query=False, use_lv=False) state_manager.add_prop("rev", rev_config) return state_manager.run() ``` ## Notes - The `rev` parameter is deprecated; specify revision in the path instead. - The file content is returned as binary data. - Ensure the Dropbox integration has `files.content.read` scope. ## License MIT

path: example.json
content: path: /documents/example.pdf

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