OpenClaw/clawhub-security-signals huggingface dataset:
Skill: scnet-sugon/social-security-card-ocr (version 1.0.3)

--- name: social_security_card_ocr description: 将图片中的文字、社保卡信息识别并提取出来。本技能应在用户需要 OCR 识别图片中的文字，或识别社保卡时使用。 version: 1.0.3 author: SCNet license: MIT tags: - OCR - 证件识别 - 发票识别 - 文字提取 required_env_vars: - SCNET_API_KEY optional_env_vars: - SCNET_API_BASE primary_credential: SCNET_API_KEY dependencies: - python3 - requests input: - ocrType : 识别类型，可选值见下文 - filePath : 待识别图片的本地路径 output: 结构化的 JSON 数据，包含识别结果和置信度 --- # Sugon-Scnet 社保卡识别 OCR 技能 本技能封装了社保卡识别的 OCR 服务，通过单一接口即可调用 1 种识别能力，高效提取社保卡核心信息。 ## 功能特性 - **社保卡识别**：支持识别社保卡，自动提取证件核心信息。 ## 前置配置 > **⚠️ 重要**：使用前需要申请 Scnet API Token ### 申请 API Token 1. 访问 [Scnet 官网](https://www.scnet.cn) 注册/登录 2. 在控制台申请 API 密钥（格式：[REDACTED_SECRET]） 3. 复制密钥备用 ### 配置 Token **手动配置（推荐）** 1. 在技能目录下创建 `config/.env` 文件，内容如下： ```ini # ===== Sugon-Scnet OCR API 配置 ===== # 申请地址：https://www.scnet.cn SCNET_API_KEY=your_scnet_api_key_here # API 基础地址（一般无需修改） SCNET_API_BASE=https://api.scnet.cn/api/llm/v1 ``` 2. 添加：`SCNET_API_KEY=你的密钥` 3. 设置文件权限为 600（仅所有者可读写） **⚠️ 安全警告**：切勿将 API Key 直接粘贴到聊天对话中，否则可能被记录或泄露。 ### Token 更新 Token 过期后调用会返回 401 或 403 错误。更新方法：重新申请 Token 并替换 config/.env 中的 SCNET_API_KEY。 ### 依赖安装 本技能需要 Python 3.6+ 和 requests 库。请运行以下命令： ```bash pip install requests ``` --- ### 使用方法 ### 参数说明 | 参数名 | 类型 | 必填 | 描述 | |--------|------|------|------| | ocrType | string | 是 | 识别类型枚举。必须为以下之一：<br>• SOCIAL_SECURITY_CARD（社保卡） | | filePath | string | 是 | 待识别图片的本地绝对路径。支持 jpg、png、pdf 等常见格式。 | ### 命令行调用示例 ```bash python .claude/skills/social_security_card_ocr/scripts/main.py SOCIAL_SECURITY_CARD /path/to/invoice.jpg ``` ### 在 AI 对话中使用 用户可以说： - “帮我识别这张社保卡的信息，图片在 /Users/name/Downloads/id.jpg” AI 会根据 description 中的关键词自动触发本技能。 ### AI 调用建议 为避免触发 API 速率限制（10 QPS），请串行调用本技能，即等待前一个识别完成后再发起下一个请求。 如果使用 OpenClaw 的 exec 工具，建议设置 timeout 或 yieldMs 参数，让命令同步执行，避免多个命令同时运行导致并发。 ### 配置选项 编辑 `config/.env` 文件： | 变量名 | 默认值 | 说明 | |--------|--------|------| | SCNET_API_KEY | 必需 | Scnet API 密钥 | | SCNET_API_BASE | https://api.scnet.cn/api/llm/v1 | API 基础地址（一般无需修改） | ### 输出 - 标准输出：识别结果的 JSON 数据，结构与 API 文档一致，位于 `data` 字段内。 - 识别结果位于 data[0].result[0].elements 中，具体字段取决于 ocrType。 - 错误信息：如果发生错误，会输出以 `错误:` 开头的友好提示。 ### 注意事项 - 本技能调用的 OCR API 有 10 QPS 的速率限制。 - 如果遇到 429 错误，请等待 2-3 秒后重试，不要连续发起请求。 - 建议在调用前确保图片已准备就绪，避免因网络问题导致重复调用。 ### 故障排除 | 问题 | 解决方案 | |------|----------| | 配置文件不存在 | 创建 config/.env 并填入 Token（参考前置配置） | | API Key 无效/过期 | 重新申请 Token 并更新 `.env` 文件 | | 文件不存在 | 检查提供的文件路径是否正确 | | 网络连接失败 | 检查网络连接或防火墙设置 | | 不支持的文件类型 | 确保文件扩展名为允许的类型（参考 API 文档） | | 401/403/Unauthorized | Token 无效或过期，重新申请并配置 | | 429 Too Many Requests | 请求过于频繁，技能会自动等待并重试（最多 3 次）。若持续失败，请降低调用频率或联系服务方提高限额。 |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: googleworkspace-bot/gws-slides (version 1.0.12)

--- name: gws-slides description: "Google Slides: Read and write presentations." metadata: version: 0.22.5 openclaw: category: "productivity" requires: bins: - gws cliHelp: "gws slides --help" --- # slides (v1) > **PREREQUISITE:** Read `../gws-shared/SKILL.md` for auth, global flags, and security rules. If missing, run `gws generate-skills` to create it. ```bash gws slides <resource> <method> [flags] ``` ## API Resources ### presentations - `batchUpdate` — Applies one or more updates to the presentation. Each request is validated before being applied. If any request is not valid, then the entire request will fail and nothing will be applied. Some requests have replies to give you some information about how they are applied. Other requests do not need to return information; these each return an empty reply. The order of replies matches that of the requests. - `create` — Creates a blank presentation using the title given in the request. If a `presentationId` is provided, it is used as the ID of the new presentation. Otherwise, a new ID is generated. Other fields in the request, including any provided content, are ignored. Returns the created presentation. - `get` — Gets the latest version of the specified presentation. - `pages` — Operations on the 'pages' resource ## Discovering Commands Before calling any API method, inspect it: ```bash # Browse resources and methods gws slides --help # Inspect a method's required params, types, and defaults gws schema slides.<resource>.<method> ``` Use `gws schema` output to build your `--params` and `--json` flags.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: calabiyauman/clawd-migrate (version 0.2.1)

# clawd-migrate Migrate from **moltbot** or **clawdbot** to **openclaw**. Preserves config, memory, and clawdbook (Moltbook) data safely on any system. ## What it does - **Discovers** existing bot assets (memory files, config, clawdbook/Moltbook credentials) - **Backs up** everything into a timestamped folder before any changes - **Migrates** files into the openclaw layout: `memory/`, `.config/openclaw/`, `.config/clawdbook/` - **Verifies** every source file was copied to its destination (existence + size match) - **Reinstalls openclaw** (`npm i -g openclaw`) and runs `openclaw onboard` automatically ## Quick start ```bash npx clawd-migrate ``` Interactive menu walks you through: Discover -> Backup -> Migrate -> Verify -> Reinstall openclaw. ## CLI commands ```bash clawd-migrate # Interactive menu (default) clawd-migrate discover [--root PATH] clawd-migrate backup [--root PATH] clawd-migrate migrate [--root PATH] [--no-backup] [--output PATH] [--setup-openclaw] ``` ## Requirements - Node.js 14+ - Python 3.x ## What gets migrated - **Memory/identity:** SOUL.md, USER.md, TOOLS.md, IDENTITY.md, AGENTS.md, MEMORY.md - **Config:** `.config/moltbook/`, `.config/moltbot/` - **Clawdbook/Moltbook:** Kept under `.config/clawdbook/` (credentials, API keys) - **Extra:** `projects/` (if present) ## Tags migration, openclaw, moltbot, clawdbot, clawdbook, moltbook, backup, verify

path: tests/__init__.py
content: # Tests for clawd_migrate


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: beelkic/gaodemapskill-bak (version 1.0.0)

--- name: gaode_map description: A skill to interact with Gaode Map (AMap) for location search and route planning. metadata: openclaw: requires: env: ["AMAP_API_KEY"] bins: ["python"] --- # Gaode Map Skill This skill allows you to search for places and plan routes using Gaode Map (AMap) API. ## Usage You can use the `amap_tool.py` script to perform actions. The API Key is expected to be in the `AMAP_API_KEY` environment variable. ### Place Search Search for POIs (Points of Interest). **Command:** ```bash python amap_tool.py search --keywords "<keywords>" [--city "<city>"] ``` **Parameters:** - `keywords`: The search query (e.g., "restaurants", "gas station"). - `city`: (Optional) The city to search in. ### Route Planning Plan a route between two locations. **Command:** ```bash python amap_tool.py route --origin "<origin>" --destination "<destination>" [--mode "<mode>"] [--city "<city>"] ``` **Parameters:** - `origin`: Start location (address or coordinates "lon,lat"). - `destination`: End location (address or coordinates "lon,lat"). - `mode`: (Optional) Route mode: `driving` (default), `walking`, `bicycling`, `transit`. - `city`: (Optional) City name (required for `transit` mode, or to help geocoding). ## Examples **User:** "Find coffee shops in Shanghai." **Action:** ```bash python amap_tool.py search --keywords "coffee shop" --city "Shanghai" ``` **User:** "Show me the driving route from Beijing West Station to the Forbidden City." **Action:** ```bash python amap_tool.py route --origin "Beijing West Station" --destination "Forbidden City" --mode "driving" --city "Beijing" ```

path: requirements.txt
content: requests


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: andy020326/police-nerre-test (version 1.0.2)

--- name: police-nerre-test description: 公安警情文本实体关系抽取工具，从警情文本中精准抽取指定实体与关系，输出严格结构化JSON，无任何多余内容 version: 1.0.3 user-invocable: true disable-model-invocation: false metadata: openclaw: emoji: 👮 requires: bins: [python3] os: [linux, macos, windows] --- # 公安警情实体关系抽取 ## 一、任务说明 作为公安警情文本实体关系抽取专家，核心任务是从用户输入的警情文本中，按照指定Schema抽取实体和关系，**仅输出严格JSON格式结果，禁止输出任何解释、Markdown标记、多余文字或注释**。 ## 二、实体类型（严格遵循，不可增减） - 姓名 - 身份证号 - 手机号 - 昵称 - 外貌 - 地理位置 - 事发地 - 涉案物品 - 危险物品 - 银行卡号 - 开户行 - 车牌号 - 组织名称 - 违法犯罪行为 - 危险行为 ## 三、关系类型（严格遵循，不可修改、自创） - 邻里关系 - 所有权（组织） - 存在行为 - 母女关系 - 夫妻关系 - 师生关系 - 所有权（人） - 归属 - 父女关系 - 父子关系 - 雇佣关系 - 母子关系 - 加害关系 - 纠纷关系（组织组织） - 纠纷关系（人组织） - 纠纷关系（人人） ## 四、输出格式（强制唯一，不可变更） 输出内容仅保留以下JSON结构，无任何其他内容，字段顺序、键名不可修改： ```json { "实体": { "姓名": [], "身份证号": [], "手机号": [], "昵称": [], "外貌": [], "地理位置": [], "事发地": [], "涉案物品": [], "危险物品": [], "银行卡号": [], "开户行": [], "车牌号": [], "组织名称": [], "违法犯罪行为": [], "危险行为": [] }, "关系": [ ["主体", "关系类型", "客体"] ] } ``` markdown ## 五、抽取规则（必须严格遵守） 抽取范围：仅提取警情文本中真实出现的内容，不编造、不联想、不扩写未提及的信息。 实体要求：所有实体字段必须完整保留，无对应内容时，字段值设为空数组（[]），禁止删除任何实体字段。 关系要求：关系名称必须完全照搬本文档 “关系类型” 中指定的内容，禁止简写、修改或自创关系名称。 关系方向：严格遵循以下方向要求，不可颠倒： 加害关系：加害者 → 受害者 存在行为：人物 / 组织 → 违法犯罪行为 / 危险行为 归属：证件、号码、物品 → 对应的人物 / 组织 所有权（人）：个人 → 其拥有的物品、车辆、财产等 所有权（组织）：组织 → 其拥有的物品、车辆、财产等 输出约束：最终仅输出 JSON 格式结果，无任何多余文字、解释、Markdown 标记或代码块说明。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: peand-rover/hotel-video-maker (version 1.0.4)

--- name: hotel-video-maker version: "1.0.4" displayName: "Hotel Video Maker â Create Property Tour and Booking Videos for Hotels and Airbnb" description: > Hotel Video Maker â Create Property Tour and Booking Videos for Hotels and Airbnb. Listings with walkthrough videos receive forty-three percent more booking inquiries on Airbnb, yet most hosts still rely on a dozen static photos and a paragraph that says "cozy and well-located." Walk through your property with a phone â lobby, suite, pool deck, rooftop view. The AI assembles a cinematic tour: steady panning shots through each space, warm color grade that makes linen look crisp and marble look polished, text overlays naming each amenity as it appears â rainfall shower, espresso machine, late checkout available â and a gentle piano score that whispers boutique luxury. Add a seasonal card highlighting holiday packages or wedding venue availability. Render a sixty-second OTA preview for Booking.com, a vertical Reel for the hotel's Instagram, and a full three-minute version for the direct-booking page. Update the rate card when pricing changes without re-filming a single room. For boutique hotel owners competing against chains, Airbnb superhosts upgrading listings, resort marketing teams producing seasonal campaigns, and hospitality management companies standardizing content across properties. Supports mp4, mov, avi, webm, jpg, png. metadata: {"openclaw": {"emoji": "ð¨", "requires": {"env": ["NEMO_TOKEN"], "configPaths": ["~/.config/nemovideo/"]}, "primaryEnv": "NEMO_TOKEN"}} homepage: https://nemovideo.com repository: https://github.com/nemovideo/nemovideo_skills apiDomain: https://mega-api-prod.nemovideo.ai ---


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jinu4you/agent-crypto-lens (version 1.0.1)

--- name: crypto-lens description: 크립토 토큰 시장 동향 및 센티먼트 종합 분석 에이전트 version: 1.0.0 --- # 🪙 CryptoLens Agent CoinGecko 시장 데이터와 웹 뉴스를 결합하여 특정 토큰의 시장 상황과 투자 심리(Sentiment)를 분석합니다. ## Features - **시장 데이터:** CoinGecko API를 통한 실시간 가격/변동률 조회 - **뉴스 분석:** 최신 뉴스 기반 호재/악재 파악 - **종합 점수:** 모멘텀, 센티먼트, 리스크 점수 산출 ## Usage ACP Job Payload: ```json { "token": "Bitcoin", "analysis_type": "full" } ```


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: pete2048/pete2048-travel-smart (version 1.0.2)

--- name: travel-smart description: | 自驾出行决策助手 - 高速出口推荐、途中住宿、打车点推荐三大场景。 高德地图 Web API + 多因子评分算法，支持 CLI / Web / 飞书三种使用方式。 必填环境变量：AMAP_KEY（高德地图）；可选：MINIMAX_API_KEY、FEISHU_APP_ID、FEISHU_APP_SECRET。 --- # TravelSmart - 智能出行决策助手 自驾途中的「第二大脑」——不只告诉你哪里近，而是告诉你**综合最优的决策点在哪里**。 ## 核心能力 - 🚗 **高速出口推荐**：堵车时推荐最佳下高速出口，综合考虑餐饮评分+绕行距离 - 🏨 **途中住宿推荐**：找停车场充足+次日行程顺路的酒店 - 🚕 **景点打车点推荐**：告知最佳停车候车位置 ## 环境准备 ### 必填 | 变量 | 说明 | |------|------| | `AMAP_KEY` | 高德地图 Web API Key（[申请地址](https://console.amap.com/dev/key/app)）| ### 可选 | 变量 | 说明 | |------|------| | `MINIMAX_API_KEY` | MiniMax LLM（自然语言路由） | | `FEISHU_APP_ID` | 飞书推送 App ID | | `FEISHU_APP_SECRET` | 飞书推送 App Secret | `.env.example` 文件中有配置模板，复制为 `.env` 后填入即可。 ## 快速开始 ### 方式一：Python CLI ```bash cd skills/travel-smart pip install -r requirements.txt cp .env.example .env # 填入 AMAP_KEY python src/main.py --scene highway --highway G4 --lng 116.397 --lat 39.909 --destination 北京 ``` ### 方式二：Web 演示页面 ```bash pip install -r requirements.txt python server.py # 访问 http://localhost:5188 ``` ### 方式三：飞书对话集成 集成到大管家，通过自然语言使用。 ## 项目结构 ``` skills/travel-smart/ ├── src/ │ ├── main.py # CLI 入口 │ ├── agents/ # Agent（路由 + 格式化） │ ├── clients/ # 高德地图 API 客户端 │ ├── scenes/ # 三大场景逻辑 │ └── scoring/ # 多因子评分引擎 ├── server.py # Web 服务入口 ├── requirements.txt # Python 依赖 ├── .env.example # 环境变量模板 └── references/ ├── scoring-algorithm.md # 评分算法详解 ├── api-reference.md # API 接口文档 └── PRD.md # 产品需求文档 ``` ## 技术架构 ``` 用户自然语言 ↓ OpenClaw Agent（意图理解 + 编排） ↓ ┌── 高德地图 Web API（地理编码/POI/路径规划） ├── MiniMax LLM（自然语言路由 + 决策建议，可选） └── 评分引擎（多因子加权评分） ↓ 结构化输出 + 飞书推送（可选） ```


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

--- name: zhipu-hot-trend description: 注册“智谱清言”技能；用于智谱大模型相关公开页面信息整理。 homepage: `https://www.zhipuai.cn/` metadata: {"clawdbot":{"emoji":"🤖"}} --- # 智谱清言 用途与边界 - 面向公开产品页与文档中心的检索与内容摘要 - 不提供账号操作、接口调用或权限绕过能力 - 仅处理公开页面的轻量信息整理 关键入口 - 主页：https://www.zhipuai.cn/ - 开放平台与文档：公开入口 - 定价与公告：站点入口 常见任务 - 模型能力与版本说明摘要（上下文长度、功能特性） - 定价与调用配额说明提取（公开信息） - 文档目录与示例链接汇总 数据字段 - 模型名称、版本、上下文长度、功能特性、链接 - 定价页链接、免费额度说明、地域与服务状态 - 文档标题、目录链接、示例入口 自动化要点 - 页面动态加载，需等待完成后解析 - 不进行API调用或账号相关操作 - 频率控制，尊重平台访问限制 示例流程 - 能力摘要：访问模型页 → 抽取版本与特性 → 输出摘要 - 定价整理：访问定价入口 → 提取费用与额度 → 输出清单 - 文档汇总：进入文档中心 → 抽取目录与示例 → 输出链接集合 合规提示 - 遵守平台规则与账号安全要求 - 不存储或输出敏感信息


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

--- name: Humor description: Develop adaptive humor that learns what makes each user laugh through signal detection, graduated testing, and graceful failure recovery. --- ## Core Principle Humor is personal. Default bland. Learn through signals. Earn the right to joke. --- ## The Loop 1. **Observe** — Detect user's humor style from their own jokes before attempting 2. **Probe** — Start subtle (wit/observation), maximum one attempt per session until positive signal 3. **Calibrate** — Track what lands vs. what falls flat (see `signals.md`) 4. **Adapt** — Build profile of types, intensity, contexts that work for THIS user --- ## User Profile (Auto-Adaptive) Edit sections below as you learn what makes this user laugh. ### Works <!-- Humor types that land. Format: "type: evidence" --> ### Fails <!-- Types to avoid. Format: "type: what happened" --> ### Intensity <!-- subtle | moderate | bold --> ### Contexts <!-- When humor is welcome/unwelcome. Format: "context: level" --> ### Signals <!-- How THIS user shows amusement. Format: "signal: meaning" --> --- *Empty sections = no data yet. Start subtle, observe, fill.* --- ## Quick Reference | Signal Type | Examples | Action | |-------------|----------|--------| | Strong positive | 😂 "lmao" callback | Log to Works, try similar | | Mild positive | "ha" continues playfully | Note, don't escalate yet | | Negative | Ignores, "anyway...", terse | Log to Fails, back off | | Ambiguous | 🙂 alone, "haha but..." | Neutral, don't change | --- ## Default Behavior (Before Data) - **Mirror first** — If user jokes, match their style - **Dry wit only** — Lowest risk default - **One probe max** — Per session until positive - **Context-aware** — Zero humor if stressed/task-focused/professional --- ## Context Rules | Context | Humor Level | |---------|-------------| | User initiated playful | Match energy | | Short task-focused messages | Zero | | Stress/frustration detected | Zero (support mode) | | Professional/external | Zero unless permitted | | Casual, low stakes | Probe allowed | --- ## Failure Recovery 1. Never explain 2. Brief pivot: "Anyway—" then substance 3. Reduce frequency for 3+ messages 4. Log type/context to Fails section --- ## Data Storage Create `~/humor/` for scaling data: ``` ~/humor/ ├── history.md # Attempts log: date, type, context, outcome ├── callbacks.md # Running jokes, references to reuse └── wins.md # Jokes that really landed (for patterns) ``` Update after meaningful humor interactions. Keep history.md trimmed to last 30 entries. --- ## Load Reference | Situation | File | |-----------|------| | Signal patterns, edge cases | `signals.md` | | Humor types (wit, puns, dark...) | `types.md` | | Context rules (work, stress, casual) | `contexts.md` | | Learning algorithm details | `feedback.md` |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yongtaop1-sys/automation-service-seller (version 1.0.0)

# Automation Service Seller I offer custom automation services for businesses. ## Services ### Hourly Automation - $50/hour - Identify and automate repetitive tasks - Python scripts, APIs, integrations - Minimum 5 hours ### Monthly Retainer - $299/month - Up to 20 hours of automation work - Priority support - Weekly check-ins ### One-Time Project - Starting at $499 - Full workflow automation - Documentation included - 30-day support ## What I Automate - Social media (Twitter, LinkedIn, Instagram) - Email sequences and follow-ups - Data entry and processing - Report generation - Lead qualification - Customer onboarding - API integrations ## Tools I Use - Python, JavaScript - Zapier, Make (n8n) - APIs (REST, webhooks) - Browser automation (Selenium, Playwright) - AI/LLM integration ## Contact - Telegram: @orchestratortao - Email: [REDACTED_SECRET] - Moltbook: @taoorchestrator


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

--- name: book-appliance-repair description: Book appliance-repair services through Lokuli MCP. Use when user needs to find and book appliance-repair. Triggers on requests like "book a appliance-repair", "find appliance-repair near me", or any appliance-repair service request. --- # uook appliance repair Book appliance-repair 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": "appliance-repair", "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: clean (LOW)
Skill: dglijin-oss/meihua-yishu-skill (version 3.0.1)

--- name: meihua-yishu-skill description: 梅花易数排盘与断卦技能。支持数字起卦、时间起卦、方位起卦，包含互卦、变卦、体用分析、自动化断卦。 version: 3.0.0 author: 天工长老 --- # 梅花易数技能 v3.0.0 > "梅花易数，简易灵验。" ## 功能 - ✅ 数字起卦 - ✅ 时间起卦 - ✅ 方位起卦 - ✅ 互卦推算 - ✅ 变卦推算 - ✅ 体用分析 - ✅ 卦气旺衰 - ✅ 自动化断卦 - ✅ 卦例库（500+ 例） - ✅ 应期统计 ## 使用 ```bash python3 scripts/meihua_pan.py --method "time" --date "2026-04-03 15:00" python3 scripts/meihua_pan.py --method "number" --numbers "3,5,7" ``` ## 变更 v3.0.0: 卦例库、应期统计、卦气旺衰算法 v2.0.0: 自动化断卦、体用分析增强


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: dinghaibin/time-tool (version 1.0.0)

--- name: time-tool description: Measure execution time of commands. Use for performance benchmarking, script optimization, and timing analysis. --- # Time - Command Execution Timer Measure how long a command takes to execute. Displays real time, CPU time, and system time for performance analysis and benchmarking. ## Usage ```bash time-tool <command> [args...] ``` ## Output - `real`: Wall clock time elapsed - `user`: CPU time in user mode - `sys`: CPU time in kernel mode ## Examples ```bash time-tool sleep 2 time-tool curl https://example.com time-tool python3 script.py ```


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

--- name: weather description: Get current weather and forecasts (no API key required). homepage: https://wttr.in/:help metadata: {"clawdbot":{"emoji":"🌤️","requires":{"bins":["curl"]}}} --- # Weather Two free services, no API keys needed. ## wttr.in (primary) Quick one-liner: ```bash curl -s "wttr.in/London?format=3" # Output: London: ⛅️ +8°C ``` Compact format: ```bash curl -s "wttr.in/London?format=%l:+%c+%t+%h+%w" # Output: London: ⛅️ +8°C 71% ↙5km/h ``` Full forecast: ```bash curl -s "wttr.in/London?T" ``` Format codes: `%c` condition · `%t` temp · `%h` humidity · `%w` wind · `%l` location · `%m` moon Tips: - URL-encode spaces: `wttr.in/New+York` - Airport codes: `wttr.in/JFK` - Units: `?m` (metric) `?u` (USCS) - Today only: `?1` · Current only: `?0` - PNG: `curl -s "wttr.in/Berlin.png" -o /tmp/weather.png` ## Open-Meteo (fallback, JSON) Free, no key, good for programmatic use: ```bash curl -s "https://api.open-meteo.com/v1/forecast?latitude=51.5&longitude=-0.12&current_weather=true" ``` Find coordinates for a city, then query. Returns JSON with temp, windspeed, weathercode. Docs: https://open-meteo.com/en/docs


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