OpenClaw/clawhub-security-signals huggingface dataset:
Skill: silentforce/share2getnote (version 1.0.2)

--- name: share2getnote version: 1.0.0 description: > Parse ChatGPT or Gemini shared conversation links and save Q&A pairs as notes to GetNote (biji.com). Use when user provides a ChatGPT or Gemini share link and wants to import conversations as notes, or mentions saving AI chat history to GetNote/笔记. description_zh: > 解析 ChatGPT 或 Gemini 的分享对话链接，将问答对保存为 Get 笔记。 当用户提供 ChatGPT/Gemini 分享链接并希望导入为笔记时使用， 或用户提到将 AI 对话保存到 Get 笔记时使用。 --- # Share to GetNote 将 ChatGPT 或 Gemini 的公开分享对话导入为 Get 笔记。每轮问答生成一条独立笔记（问题为标题，回答为正文 MD 格式）。 ## 触发条件 当用户提供的 URL 匹配以下模式时自动触发： - `https://chatgpt.com/share/*` - `https://chat.openai.com/share/*` - `https://gemini.google.com/share/*` - `https://g.co/gemini/share/*` ## 前置依赖 ### 运行环境 需要 `uv` (Python 包管理器) 。脚本使用 PEP 723 内联依赖声明，`uv run` 会自动安装所需的 `playwright` 包。 检查 uv 是否可用： ```bash uv --version ``` 若未安装 uv，参考: https://docs.astral.sh/uv/getting-started/installation/ ### GetNote Skill 需要 getnote skill 已安装并完成授权。检查方式：确认环境变量 `GETNOTE_API_KEY` 和 `GETNOTE_CLIENT_ID` 已设置，或 `~/.openclaw/openclaw.json` 配置文件存在。 若未配置，提示用户： > 请先运行 `/note config` 完成 GetNote 授权配置。 getnote skill 安装地址: https://clawhub.ai/iswalle/getnote ## 核心工作流 ### Step 1: 验证 URL 确认用户提供的 URL 匹配支持的分享链接格式。若不匹配，告知用户支持的格式。 ### Step 2: 检查运行环境 确认 `uv` 可用。若不可用，告知用户安装方法。 ### Step 3: 运行解析脚本 执行解析脚本提取对话内容（脚本首次运行时会自动安装 Playwright 和 Chromium）。 `SKILL_DIR` 为本 SKILL.md 文件所在的目录，请根据实际安装路径替换： ```bash uv run SKILL_DIR/scripts/parse_share.py "<share_url>" ``` 脚本输出 JSON 数组到 stdout： ```json [ {"title": "[1/3] 问题文本...", "content": "回答的 markdown 内容...\n\n---\n*来源: ...*"}, {"title": "[2/3] 第二个问题...", "content": "第二个回答..."} ] ``` ### Step 4: 展示结果并确认 解析 JSON 输出后，向用户展示： ``` 成功提取 N 条笔记： 1. [标题1] 2. [标题2] ... 是否保存到 GetNote？ ``` 等待用户确认后继续。 ### Step 5: 保存到 GetNote 逐条调用 getnote skill 的 `/note save` 命令保存笔记。对于每条笔记： - 标题: JSON 中的 `title` 字段 - 正文: JSON 中的 `content` 字段（markdown 格式） 每保存成功一条，报告进度。 ### Step 6: 汇报结果 保存完成后，向用户汇报： ``` 已成功保存 N/M 条笔记到 GetNote。 [如有失败] 以下笔记保存失败： - [标题]: [错误原因] ``` ## 错误处理 | 脚本退出码 | 含义 | 处理方式 | |-----------|------|---------| | 1 | URL 不支持 | 告知用户支持的 URL 格式 | | 2 | 页面加载失败/超时 | 提示链接可能已过期、已删除或需要登录 | | 3 | 未找到对话数据 | 提示页面结构可能已变更，建议使用备用方案 | | 4 | Playwright 未安装 | 引导用户安装 Playwright | ## 备用方案 当 Python 脚本失败时（如页面结构变更），使用以下备用流程： 1. 使用 browser-agent Task 工具打开分享链接 2. 等待页面加载完成后截取文本快照 3. 从快照文本中手动识别和提取 Q&A 对（用户消息和助手回复交替出现） 4. 按照相同格式组织为 `{title, content}` 结构 5. 继续 Step 4（确认）和 Step 5（保存）

path: scripts/requirements.txt
content: playwright>=1.40.0


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: 52yuanchangxing/env-diff-explainer (version 1.0.0)

--- name: env-diff-explainer version: 1.0.0 description: "比较 dev/staging/prod 配置差异，并把技术差异翻译成业务风险。；use for env, config, diff workflows；do not use for 输出敏感密钥值, 直接覆盖配置." author: OpenClaw Skill Bundle homepage: https://example.invalid/skills/env-diff-explainer tags: [env, config, diff, ops] user-invocable: true metadata: {"openclaw":{"emoji":"🌡️","requires":{"bins":["python3"]},"os":["darwin","linux","win32"]}} --- # 环境差异解释器 ## 你是什么 你是“环境差异解释器”这个独立 Skill，负责：比较 dev/staging/prod 配置差异，并把技术差异翻译成业务风险。 ## Routing ### 适合使用的情况 - 比较 dev 和 prod 的配置差异 - 解释这些差异会造成什么影响 - 输入通常包含：多个环境配置文件或文本 - 优先产出：差异摘要、高风险差异、验证步骤 ### 不适合使用的情况 - 不要输出敏感密钥值 - 不要直接覆盖配置 - 如果用户想直接执行外部系统写入、发送、删除、发布、变更配置，先明确边界，再只给审阅版内容或 dry-run 方案。 ## 工作规则 1. 先把用户提供的信息重组成任务书，再输出结构化结果。 2. 缺信息时，优先显式列出“待确认项”，而不是直接编造。 3. 默认先给“可审阅草案”，再给“可执行清单”。 4. 遇到高风险、隐私、权限或合规问题，必须加上边界说明。 5. 如运行环境允许 shell / exec，可使用： - `python3 "{baseDir}/scripts/run.py" --input <输入文件> --output <输出文件>` 6. 如当前环境不能执行脚本，仍要基于 `{baseDir}/resources/template.md` 与 `{baseDir}/resources/spec.json` 的结构直接产出文本。 ## 标准输出结构 请尽量按以下结构组织结果： - 差异摘要 - 高风险差异 - 潜在业务影响 - 建议对齐项 - 可接受差异 - 验证步骤 ## 本地资源 - 规范文件：`{baseDir}/resources/spec.json` - 输出模板：`{baseDir}/resources/template.md` - 示例输入输出：`{baseDir}/examples/` - 冒烟测试：`{baseDir}/tests/smoke-test.md` ## 安全边界 - 报告会尽量掩码疑似敏感信息。 - 默认只读、可审计、可回滚。 - 不执行高风险命令，不隐藏依赖，不伪造事实或结果。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: hy-1990/dream-talking-image (version 1.0.1)

--- name: dream-talking-image description: "Generate talking videos from images using Talking Image API. Create talking videos from audio and images, supporting non-human faces like pets or animated characters. Powered by Dreamface - AI tools for everyone. Visit https://tools.dreamfaceapp.com/home for more AI products. API resources: https://api.newportai.com/api-reference/talking-image" metadata: {"openclaw": {"emoji": "🖼️", "requires": {"env": ["DREAMTALKINGIMAGE_API_KEY"]}, "primaryEnv": "DREAMTALKINGIMAGE_API_KEY"}} --- # Dream Talking Image - Talking Video from Image Generate talking videos from static images and audio. ## Quick Start ### 1. Get API Key Before using this skill, you need a DreamAPI API key. Visit **https://api.newportai.com/api-reference/get-started** to sign up and get your API key. For more AI tools, please visit: **https://tools.dreamfaceapp.com/home** ### 2. Configure API Key ```bash openclaw config patch --json '{"skills": {"entries": {"dream-talking-image": {"env": {"DREAMTALKINGIMAGE_API_KEY": "your-api-key-here"}}}}}'``` ### 3. Usage #### Parameters: - **photoUrl**: Image URL (jpg, jpeg, png, webp, gif), max 1280x1280 - **audioUrl**: Audio URL (mp3, wav, m4a), recommended < 2 minutes #### Note: - Audio over 2 minutes may cause memory errors - Recommend m4a format ## API Details ### 1. Get Upload Policy (for local files) Upload your local files to OSS first (get upload policy, then upload). ### 3. Talking Image API ``` POST https://api.newportai.com/api/async/talking_image ``` **Headers:** ``` Authorization: Bearer {DREAMTALKINGIMAGE_API_KEY} Content-Type: application/json ``` **Request Body:** ```json { "photoUrl": "https://example.com/image.jpg", "audioUrl": "https://example.com/audio.mp3" } ``` ### 4. Polling for Result ``` POST https://api.newportai.com/api/getAsyncResult ``` ## Implementation Notes - Supports non-human faces (pets, anime characters) - Automatically mirrors facial expressions and vocal tone - Supports multiple languages - Audio recommended < 2 minutes - Status: 0=pending, 1=processing, 2=processing, 3=completed, 4=timeout


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: followaf/guofeng-lyric-writer (version 1.0.0)

--- name: guofeng-lyric-writer description: Create traditional Chinese-style (Guofeng) lyrics with classical imagery, vocabulary substitution, rhyme schemes, and poetic techniques. Use when creating Guofeng lyrics, writing Chinese-style songs, adapting classical poetry into lyrics, or learning Guofeng lyric composition. Triggers include requests like writing Guofeng lyrics, creating traditional Chinese songs, or composing classical-style verses. --- # Guofeng Lyric Writer Create authentic traditional Chinese-style (Guofeng) lyrics with proper classical vocabulary, imagery, rhyme, and poetic structure. ## Quick Start ```text User: "帮我写一首关于江南的国风歌词" AI: [Reads references/imagery.md → Creates lyrics using proper imagery and vocabulary] ``` ## Core Workflow ### 1. Understand Request Identify: theme (离别/思念/山水/历史), emotion, story context ### 2. Select Imagery - Load [references/imagery.md](references/imagery.md) for theme-appropriate imagery - Choose 3-5 core images that work together ### 3. Apply Vocabulary - Use [references/vocabulary.md](references/vocabulary.md) for word substitutions - Transform modern language into classical expression ### 4. Structure Rhyme & Rhythm - Consult [references/rhyme.md](references/rhyme.md) for rhyme scheme selection - Apply appropriate sentence length patterns ### 5. Compose Lyrics Follow [references/workflow.md](references/workflow.md) for complete creation process ### 6. Polish & Refine Check emotional depth, rhythm flow, and classical authenticity ## Key Techniques | Technique | Purpose | Reference | |-----------|---------|-----------| | Vocabulary Substitution | Modern → Classical style | vocabulary.md | | Imagery Selection | Create visual atmosphere | imagery.md | | Rhyme Design | Musical flow | rhyme.md | | Emotional Layering | Progressive depth | workflow.md | ## Quality Standards - **Authenticity**: Use genuine classical vocabulary, avoid forced ancient style - **Coherence**: Images should connect and build unified atmosphere - **Musicality**: Rhyme naturally, match melodic rhythm - **Emotional Truth**: Express sincere feelings, not empty decoration ## Avoid Common Mistakes - ❌ Over-stacking obscure references → incomprehensible lyrics - ❌ Excessive classical language → loses modern accessibility - ❌ Forced ancient style without real emotion → hollow beauty - ❌ Ignoring rhythm → unsingable lyrics ## When to Load References | User Request | Load These Files | |--------------|------------------| | General creation | imagery.md, vocabulary.md | | Specific theme (离别/思念/山水) | imagery.md (theme section) | | Rhyme assistance | rhyme.md | | Learning techniques | workflow.md, examples.md | | Analyzing style | examples.md | ## Output Format ```text 【歌词名称】 （主歌） [lines with classical imagery] （副歌） [emotionally intensified lines] （过渡/结尾） [resolution or lingering feeling] --- 创作说明： - 主题：[theme] - 核心意象：[3-5 images] - 韵脚：[rhyme scheme] - 情感递进：[layering description] ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: tomlee2013/siliconflow-qwen-vision (version 0.2.0)

--- name: siliconflow-qwen-vision description: 图片理解与分析。当用户需要分析图片内容、识别图片中的物体、描述图片场景、理解图片含义时使用此技能。支持图片问答、物体识别、场景描述等。 --- # 图片理解 (SiliconFlow Qwen2.5-VL) 使用 SiliconFlow 的 Qwen2.5-VL 模型进行图片分析理解。 ## 环境配置 - 需要设置 `OPENAI_API_KEY` 环境变量 (SiliconFlow API Key，即 OpenAI 格式的 API Key) - 或使用 `--api-key` 参数直接传入 API Key ## 使用方法 ```bash cd siliconflow-qwen-vision python scripts/analyze_image.py -i /path/to/image.jpg -p "请描述这张图片" ``` ## 参数说明 - `-i, --image`: 图片路径 (必需) - `-p, --prompt`: 提示词，默认 "请描述这张图片" - `-k, --api-key`: API Key (可选，默认从环境变量读取) - `-o, --output`: 输出文件路径 (可选) ## 示例 ```bash # 描述图片内容 python scripts/analyze_image.py -i photo.jpg -p "这张图片里有什么?" # 识别物体 python scripts/analyze_image.py -i photo.jpg -p "图片中有哪些物体?" # 分析场景 python scripts/analyze_image.py -i photo.jpg -p "描述这个场景" # 保存结果到文件 python scripts/analyze_image.py -i photo.jpg -p "详细描述图片" -o result.txt ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: nguyet601/ai-writing-agent (version 1.1.0)

--- name: ai-writing-agent description: AI writing assistant that generates structured articles, blog posts, and marketing content version: 1.1.0 author: nguyet601 tags: - writing - content - blog - ai - copywriting --- # AI Writing Agent AI Writing Agent 是一个用于自动生成文章、博客内容和文案的 AI 写作助手。 它可以根据用户提供的主题或需求，自动生成结构清晰、逻辑完整的文章内容，适用于博客写作、内容营销、知识分享和社交媒体内容创作。 ## 功能 这个 AI Agent 可以： - 根据主题生成完整文章 - 自动生成吸引人的标题 - 组织清晰的文章结构 - 生成博客内容 - 生成营销文案 - 生成知识型文章 ## 使用方式 用户只需要提供一个简单的写作需求，例如： - 写一篇关于 AI 的博客 - 写一篇关于远程工作的文章 - 写一篇 SEO 内容营销文章 - 写一篇产品介绍文案 AI Writing Agent 会自动理解需求，并生成完整文章。 ## 工作流程 AI Writing Agent 执行以下步骤： 1. 理解用户的主题和写作目标 2. 分析目标读者 3. 生成 SEO 友好的标题 4. 设计文章结构（包含 H2 小标题） 5. 生成完整正文内容 6. 在结尾给出总结和行动建议 ## 输出格式 请严格按照以下结构输出： 标题 SEO 描述 正文（包含 H2 小标题结构） 总结 CTA（鼓励读者采取行动） ## 示例 用户输入： Write a blog post about the benefits of AI tools for productivity. AI Writing Agent 输出： 标题 AI 工具如何提升工作效率 正文 （完整文章内容） 总结 总结文章核心观点，并给出结论。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jbennett111/supportforge (version 1.0.0)

--- name: supportforge description: AI customer support via SupportForge API — ticket creation, auto-replies, routing, knowledge base search. Use when user needs customer support automation, ticket management, auto-response generation, or support knowledge base features. Free tier available (100 req/day). --- # SupportForge AI customer support API by Voss Consulting Group. ## Setup Set `SUPPORTFORGE_API_KEY` or `SUPPORTFORGE_EMAIL` for auto-signup (free, no credit card). ```bash curl -X POST https://anton.vosscg.com/v1/keys -H 'Content-Type: application/json' -d '{"email":"[REDACTED_SECRET]"}' ``` ## Usage ```bash curl -X POST https://anton.vosscg.com/v1/tickets/create \ -H "Authorization: Bearer $SUPPORTFORGE_API_KEY" \ -H "Content-Type: application/json" \ -d '{"subject": "Login issue", "message": "Cannot reset password", "priority": "high"}' ``` ## Capabilities - `POST /v1/tickets/create` — Create support ticket - `POST /v1/tickets/:id/reply` — Reply (manual or AI auto-reply) - `POST /v1/kb/search` — Search knowledge base - `POST /v1/keys` — Get API key (email-only for free tier) - `GET /v1/health` — Health check


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: nightvibes3/video-upscale (version 1.4.0)

--- name: ai-video-upscale version: 1.0.0 description: "AI-powered video upscaling with Real-ESRGAN and Waifu2x. Use when user asks to enhance, upscale, improve video quality, make HD/4K. Supports anime and real footage with progress tracking." metadata: {"openclaw":{"emoji":"🎬","triggers":["upscale","enhance","make HD","make 4K","improve quality"],"requires":["ffmpeg","bc","md5sum"]}} author: NightVibes3 --- # AI Video Upscale Skill AI-powered video upscaling with progress tracking and job isolation. ## Quick Usage After installation (see below), run: ```bash ~/video-tools/real-video-enhancer/upscale_video.sh "{{filepath}}" "{{output_path}}" "{{mode}}" "{{preset}}" "{{engine}}" "{{job_id}}" ``` Or if you added the tool paths to your PATH: ```bash upscale_video.sh "{{filepath}}" "{{output_path}}" "{{mode}}" "{{preset}}" "{{engine}}" "{{job_id}}" ``` ## Parameters | Parameter | Default | Description | |-----------|---------|-------------| | filepath | required | Input video path | | mode | auto | `anime` or `real` (auto-detects) | | preset | fast | `fast` (2x) or `high` (4x) | | engine | auto | `waifu2x` or `realesrgan` | | job_id | auto | `tg_<chatid>_<messageid>` | ## Mode Selection - **anime** → Waifu2x (better for anime with text) - **real** → Real-ESRGAN (better for photorealistic) ## Preset Selection | Preset | Upscale | CRF | Speed | |--------|---------|-----|-------| | fast | 2x | 20 | Quick | | high | 4x | 16 | Slower | ## Example Prompts - "Upscale this" - "Upscale this anime clip" - "Make this 4K" - "Enhance in high quality, keep me updated" ## Output Format ``` JOB_ID: tg_123_456 PHASE: EXTRACTING_FRAMES FRAMES_TOTAL: 780 PHASE: UPSCALING PROGRESS: 78/780 ... STATUS: OK UPSCALED_VIDEO: /path/to/output.mp4 ``` ## Installation See [INSTALL.md](references/INSTALL.md) for setup instructions.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: haoxianniu528-bit/recruit-email-monitor (version 1.0.0)

--- name: recruit-email-monitor description: 招聘邮件监控系统 - 自动检查邮箱、记录到表格、飞书通知、每日简报 homepage: https://github.com/nhaoxi/recruit-email-monitor metadata: { "clawdbot": { "emoji": "📧", "requires": { "bins": ["python3"], "pip": ["openpyxl", "poplib"] }, "install": [ { "id": "pip-deps", "kind": "pip", "packages": ["openpyxl"], "label": "安装依赖 (openpyxl)" } ], "config": { "email_accounts": "配置邮箱账号 (QQ/163 等)", "excel_path": "招聘邮件汇总表格路径", "feishu_target": "飞书通知目标用户 ID" } } } --- # 招聘邮件监控系统 自动监控多个邮箱的招聘相关邮件，记录到 Excel 表格，支持飞书实时通知和每日简报。 ## 功能 - **自动检查**: 每小时检查 QQ 邮箱、163 邮箱等 - **智能分类**: 自动识别笔试/测评、面试、Offer、宣讲会、投递确认等类型 - **实时通知**: 发现新邮件时立即发送飞书消息 - **每日简报**: 每天早上 9:00 汇总待处理邮件 - **表格管理**: 自动记录到 Excel，支持状态标记 ## 快速开始 ### 1. 配置邮箱 编辑 `scripts/email-heartbeat-check.py`，配置你的邮箱账号： ```python EMAIL_ACCOUNTS = [ { 'name': 'QQ 邮箱', 'user': '[REDACTED_SECRET]', 'password': 'your_auth_code', # 使用授权码，不是登录密码 'host': 'pop.qq.com', 'port': 995, }, { 'name': '163 邮箱', 'user': '[REDACTED_SECRET]', 'password': 'your_auth_code', 'host': 'pop.163.com', 'port': 995, } ] ``` ### 2. 配置飞书通知 在脚本中修改飞书目标用户 ID： ```python '--target', 'user:YOUR_FEISHU_USER_ID' ``` ### 3. 设置定时任务 使用 OpenClaw 的 cron 系统或系统 crontab： ```bash # 每小时检查邮箱 0 * * * * python3 /path/to/email-heartbeat-check.py # 每天早上 9:00 发送简报 0 9 * * * python3 /path/to/email-daily-briefing.py ``` ## 脚本说明 ### email-heartbeat-check.py **功能**: 检查邮箱，发现新招聘邮件时记录到表格并发送飞书通知 **运行频率**: 建议每小时一次 **输出**: - 更新 Excel 表格 - 发送飞书通知（如有新邮件） ### email-daily-briefing.py **功能**: 汇总待处理邮件，生成日报并发送 **运行频率**: 每天早上 9:00 **输出**: - 生成简报文件 - 发送飞书消息 ## 邮件分类规则 | 类型 | 关键词 | |------|--------| | 笔试/测评 | 笔试、在线笔试、笔试通知、测评、人才测评、性格测评 | | 面试 | 面试、面试邀请、面试通知 | | Offer/录用 | offer、录用、签约、三方 | | 宣讲会 | 宣讲会、说明会、open day | | 投递确认 | 投递成功、简历、申请 | | 其他 | 其他招聘相关邮件 | ## 表格结构 | 列名 | 说明 | |------|------| | 日期 | 邮件收到时间 | | 邮箱 | 邮箱账号 (QQ/163) | | 主题 | 邮件主题 | | 发件人 | 发件人地址 | | 状态 | ⏳ 待处理 / ✅ 已完成 | | 类型 | 邮件分类 | | 链接 | 邮件中的重要链接 | | 截止日期 | 截止/面试日期 | ## 命令行示例 ```bash # 手动检查邮箱 python3 scripts/email-heartbeat-check.py # 手动生成简报 python3 scripts/email-daily-briefing.py # 查看表格 open /home/erhao/shared/招聘邮件汇总.xlsx ``` ## 注意事项 1. **邮箱授权码**: QQ/163 邮箱需要使用授权码，不是登录密码 2. **表格路径**: 确保 Excel 文件路径正确，首次运行会自动创建 3. **飞书权限**: 确保 OpenClaw 有飞书消息发送权限 4. **关键词匹配**: 可根据需要调整 `RECRUITMENT_KEYWORDS` 列表 ## 故障排查 **问题**: 没有检测到新邮件 - 检查邮箱授权码是否正确 - 查看脚本运行日志 - 确认关键词匹配规则 **问题**: 飞书通知未发送 - 检查飞书用户 ID 是否正确 - 确认 OpenClaw 飞书插件已启用 **问题**: 表格写入失败 - 检查文件路径权限 - 确保 Excel 文件未被其他程序占用 ## 相关文件 - `scripts/email-heartbeat-check.py` - 邮箱检查脚本 - `scripts/email-daily-briefing.py` - 每日简报脚本 - `/home/erhao/shared/招聘邮件汇总.xlsx` - 邮件汇总表格 - `/home/erhao/shared/招聘邮件每日简报.txt` - 简报输出文件


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: ntriq-gh/ntriq-world-bank-economic-indicators (version 1.0.0)

--- name: ntriq-world-bank-economic-indicators description: "Free API for World Bank economic indicators and macro data. No subscription. Access GDP, inflation, poverty rates, trade data, development metrics. Government data, pay-per-use." version: 1.0.0 metadata: openclaw: primaryTag: data-intelligence tags: [economics,development] author: ntriq homepage: https://x402.ntriq.co.kr --- # World Bank Economic Indicators Free World Bank macro-economic data API. Access GDP, inflation, poverty rates, trade data, and 1,500+ development indicators for 217 economies. No subscription required — replaces paid economic data subscriptions. ## Parameters | Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `country_code` | string | ✅ | ISO 3166-1 alpha-2 (or `all` for all countries) | | `indicators` | array | ✅ | World Bank indicator codes (e.g., `NY.GDP.MKTP.CD`) | | `date_range` | string | ❌ | Year range e.g. `2015:2024` | | `per_page` | integer | ❌ | Results per page (default: 50, max: 1000) | ## Example Response ```json { "country": "Brazil", "iso2": "BR", "indicators": { "NY.GDP.MKTP.CD": {"label": "GDP (current US$)", "value": 2080000000000, "year": 2023}, "FP.CPI.TOTL.ZG": {"label": "Inflation, consumer prices (annual %)", "value": 4.62, "year": 2023}, "SL.UEM.TOTL.ZS": {"label": "Unemployment (% of labor force)", "value": 7.8, "year": 2023}, "NE.TRD.GNFS.ZS": {"label": "Trade (% of GDP)", "value": 38.1, "year": 2023} } } ``` ## Use Cases - Emerging market investment research and screening - Country economic risk model data ingestion - Academic economic research data collection ## Access ```bash # x402 endpoint — pay $0.01 USDC per call (Base mainnet) POST https://x402.ntriq.co.kr/world-bank-econ # Service catalog curl https://x402.ntriq.co.kr/services ``` [x402 micropayments](https://x402.ntriq.co.kr) — USDC on Base, gasless EIP-3009


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

--- name: book-extensions description: Book extensions services through Lokuli MCP. Use when user needs to find and book extensions. Triggers on requests like "book a extensions", "find extensions near me", or any extensions service request. --- # uook extensions Book extensions 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": "extensions", "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: timo2026/openclaw-cnc-core (version 1.2.1)

# OpenClaw CNC Core > CNC加工智能报价系统 | Intelligent CNC Machining Quote System ## 简介 OpenClaw CNC Core 是面向CNC加工行业的智能报价引擎，提供： - 📐 STEP/STL 图纸解析 - 💰 智能报价计算 - ⚠️ 风险控制预警 - 🔍 历史案例检索 ## 在线演示 🌐 **演示地址**: http://47.253.101.130/ > 🔒 安全防护：Nginx限流 (20次/分钟/IP) + 安全头 + 50MB上传限制 ## 快速开始 ```python from core.quote_engine import OpenClawQuoteEngine # 初始化引擎 engine = OpenClawQuoteEngine(config_dir="./config/examples") # 计算报价 order = { "material": "铝6061", "volume_cm3": 100, "area_dm2": 20, "quantity": 10, "surface_treatment": "阳极氧化" } result = engine.calculate_quote(order) print(f"报价: ¥{result.total_price}") ``` ## 支持的LLM平台 | 平台 | 标识符 | 需要API Key | |------|--------|-------------| | DashScope | `dashscope` | ✅ | | OpenAI | `openai` | ✅ | | DeepSeek | `deepseek` | ✅ | | 智谱AI | `zhipu` | ✅ | | Moonshot | `moonshot` | ✅ | | Ollama (本地) | `local` | ❌ | ## 版本 - **社区版**: MIT License，免费使用 - **商业版**: 预训练模型 + 行业价格库 + 定制服务 ## 联系方式 - 🌐 官网: https://openclaw.ai/cnc - 📧 邮箱: [REDACTED_SECRET] - 💬 QQ: 849355070 - GitHub: https://github.com/Timo2026/openclaw-cnc-core --- **开源日期**: 2026-03-26 **版本**: v1.2.0 **许可证**: MIT


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: kleberbaum/jaen (version 0.1.0)

--- name: jaen description: Jaen namespace for Netsnek e.U. CMS framework. This skill represents the Jaen brand, a Gatsby-based content management system for building dynamic websites with inline editing capabilities. user-invocable: true version: 0.1.0 metadata: openclaw: os: - linux permissions: - exec --- # jaen Jaen namespace for Netsnek e.U. CMS framework. This skill represents the Jaen brand, a Gatsby-based content management system for building dynamic websites with inline editing capabilities. ## Overview This OpenClaw skill reserves the `jaen` namespace on ClawHub for Netsnek e.U. It provides basic copyright and identity information when invoked. ## Usage When a user asks about jaen or requests copyright information, run the copyright script: ```bash scripts/copyright.sh ``` For JSON output: ```bash scripts/copyright.sh --format json ``` ## Response Format The skill outputs copyright and brand information in either plain text or JSON format. Always respond to the user with the copyright notice and a brief description of the jaen brand. ### Example Interaction **User:** What is **Assistant:** jaen is a product by Netsnek e.U. Copyright (c) 2026 Netsnek e.U. All rights reserved. Website: https://netsnek.com ## Scripts | Script | Purpose | |--------|---------| | `scripts/copyright.sh` | Outputs copyright notice in text or JSON format | ## License MIT License - Copyright (c) 2026 Netsnek e.U. All rights reserved.


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