OpenClaw/clawhub-security-signals huggingface dataset:
Skill: huajianjiu000/data-viz-reporter (version 0.1.0)

# 数据可视化报告生成器 ## 基本信息 - **名称**: data-viz-reporter - **描述**: 专业的商业数据可视化报告生成工具，将枯燥的数据转化为直观、美观、有洞察力的图表和报告 - **版本**: 1.0.0 - **适用场景**: 电商数据分析、运营周报/月报、市场调研、财务报表、用户分析等商业场景 ## 核心能力 ### 1. 图表类型选择 | 图表类型 | 适用场景 | 数据要求 | |---------|---------|---------| | 折线图 | 趋势变化 | 时间序列数据 | | 柱状图 | 对比分析 | 分类数据 | | 饼图/环形图 | 占比展示 | 部分与整体 | | 散点图 | 相关性分析 | 两个变量 | | 热力图 | 分布密度 | 二维矩阵 | | 漏斗图 | 转化分析 | 流程数据 | | 仪表盘 | KPI监控 | 单值+区间 | ### 2. 设计规范 - **配色方案**: - 专业商务: 蓝灰为主 - 年轻活力: 渐变色系 - 数据强调: 高对比色 - **字体规范**: 标题16-20pt，正文10-12pt - **留白技巧**: 呼吸感留白，信息密度适中 ### 3. 数据洞察提炼 - 自动识别关键数据点 - 异常值标注 - 趋势预判 - 同环比分析 - 异常原因假设 ### 4. 报告结构模板 ``` 1. 执行摘要 (1页) 2. 核心指标看板 3. 深度分析图表 4. 问题诊断 5. 建议与行动项 ``` ## 输入要求 用户提供以下信息: 1. 原始数据（Excel/CSV/JSON/直接粘贴） 2. 分析目的（周报/月报/专项分析） 3. 展示维度（时间/类别/区域等） 4. 报告风格（商务简约/时尚活力/学术严谨） ## 输出格式 ### 结构化报告 ```markdown # 数据分析报告 ## 📊 执行摘要 [核心发现2-3条] ## 1️⃣ 核心指标概览 | 指标 | 数值 | 环比 | 同比 | |-----|------|-----|-----| | ... | ... | ... | ... | ## 2️⃣ 趋势分析 [图表区域] ## 3️⃣ 分类对比 [图表区域] ## 4️⃣ 问题诊断 - 🔴 异常指标: [描述] - 🟡 关注指标: [描述] - 🟢 健康指标: [描述] ## 5️⃣ 行动建议 1. [建议1] 2. [建议2] ## 📎 数据附录 [原始数据表格] ``` ### 图表输出 生成可嵌入的ECharts/Draw.io图表代码 ## 示例 **用户输入**: - 数据: 某电商店铺12月销售数据 - 指标: 访客数、转化率、客单价、销售额 - 维度: 按日期、按品类 - 风格: 商务简约 **生成结果**: ``` # 📈 电商数据周报 ## 📊 执行摘要 1. 本周销售额 ¥128,500，环比上周↑12.3%，增长态势良好 2. 转化率为3.8%，略低于行业均值4.2%，存在优化空间 3. 服装品类贡献60%销售额，周末是流量高峰 --- ## 1️⃣ 核心指标概览 | 指标 | 本周 | 上周 | 环比 | 目标完成率 | |-----|------|------|------|-----------| | 访客数 | 33,816 | 29,450 | ↑14.8% | 105% | | 转化率 | 3.8% | 4.1% | ↓7.3% | 95% | | 客单价 | ¥89.5 | ¥82.3 | ↑8.7% | 112% | | 销售额 | ¥128,500 | ¥114,350 | ↑12.3% | 107% | --- ## 2️⃣ 销售趋势分析 ### 日销售趋势 📉 建议使用折线图展示周一至周日销售曲线 - 周六为本周销售峰值: ¥23,500 - 周一销售最低: ¥15,200 - 周末流量是工作日的1.8倍 --- ## 3️⃣ 品类销售对比 | 品类 | 销售额 | 占比 | 环比 | |-----|-------|------|------| | 服装 | ¥77,100 | 60% | ↑15% | | 数码 | ¥25,700 | 20% | ↑8% | | 家居 | ¥15,420 | 12% | ↓3% | | 其他 | ¥10,280 | 8% | ↑22% | --- ## 4️⃣ 问题诊断 🔴 **转化率下降** - 本周转化率3.8%，较上周4.1%有所下降 - 可能原因: 流量质量下降/页面加载慢/价格竞争力不足 - 建议: 检查落地页优化，排查用户体验问题 🟡 **家居品类下滑** - 家居品类环比下降3%，需关注 - 建议: 分析TOP产品表现，调整营销策略 🟢 **客单价提升** - 客单价从¥82.3提升至¥89.5 - 得益于满减活动效果显现 --- ## 5️⃣ 行动建议 1. **提升转化率** ⭐⭐⭐⭐⭐ - 优化商品详情页 - 增加用户评价展示 - 完善客服响应机制 2. **抓住周末流量** ⭐⭐⭐⭐ - 重点排班周末营销活动 - 提前预热周末专场 3. **家居品类诊断** ⭐⭐⭐ - 下周深度分析家居品类数据 - 评估是否需要调整品类策略 --- ## 📎 数据附录 [详细数据表格...] ``` ## 图表生成建议 根据数据类型自动推荐最佳图表: ```python # 示例: 生成ECharts配置 chart_config = { "title": "销售额趋势", "type": "line", # 或 bar/pie/scatter "data": [...], "colors": ["#5470C6", "#91CC75", "#FAC858"] } ``` ## 使用限制 - 数据量建议不超过10万行 - 需要确保数据准确性 - 涉及财务数据需注意保密 ## 更新日志 - v1.0.0 (2025-01): 初始版本发布


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zhu-xiao-di/video-notification (version 1.0.0)

--- name: video_notification description: 向指定手机号发送视频通知（基于 IVVR 平台）。需要提供服务器上已存在的视频文件绝对路径，文件大小不超过 5MB。 version: 1.1.0 author: hdjs license: MIT tags: - notification - video - ivvr icon: https://example.com/video-icon.png # 可替换为真实图标 URL endpoint: base_url: "{{API_BASE_URL}}" # 用户需在环境变量中设置，例如 https://your-domain.com 或 http://xxx.ngrok.io path: "/send_video_notice" method: POST headers: Content-Type: application/json X-[REDACTED_SECRET]" input_schema: type: object required: - file_path - called_numbers properties: file_path: type: string description: 视频文件在服务器上的绝对路径（例如 /home/ubuntu/videos/notice.mp4） example: "/home/ubuntu/videos/notice.mp4" called_numbers: type: array description: 接收视频通知的手机号列表（字符串数组） items: type: string pattern: "^1[3-9]\\d{9}$" minItems: 1 example: ["13812345678", "13987654321"] output_schema: type: object properties: success: type: boolean description: 是否成功 file_id: type: integer description: 平台返回的文件 ID msg: type: string description: 附加信息 examples: - title: 发送单个视频通知 input: file_path: "/home/ubuntu/videos/welcome.mp4" called_numbers: ["15600766391"] output: success: true file_id: 1364 msg: "发送完成" - title: 批量发送 input: file_path: "/data/videos/alert.mp4" called_numbers: ["15600766391", "13912345678"] output: success: true file_id: 1365 msg: "发送完成" env_vars: - name: API_BASE_URL description: 视频通知服务的公网地址（例如 https://your-domain.com 或 http://xxx.ngrok.io），注意不要带尾部斜杠 required: true - name: API_KEY description: 服务鉴权所需的 API Key，必须与服务器配置的 SERVICE_API_KEY 一致 required: true secret: true --- # 视频通知发送技能 该技能调用你部署的 FastAPI 视频通知服务，向指定手机号发送视频通知。 ## 前置条件 1. 已部署视频通知服务（代码见 `send_video_api.py`）到一台公网可访问的服务器（或使用 ngrok 临时暴露）。 2. 服务已设置 `SERVICE_API_KEY` 环境变量，并开放 `8867` 端口（或通过 Nginx 代理到公网）。 3. 技能所需的环境变量 `API_BASE_URL` 和 `API_KEY` 已在 ClawHub 中正确配置。 ## 使用说明 在对话中提及“发视频通知”或类似关键词，技能会自动提取参数并调用接口。你也可以直接提供 JSON 格式参数。 ### 示例对话 - 用户：给 15600766391 发视频通知，视频文件在 `/home/ubuntu/videos/notice.mp4` - 技能：调用接口，返回发送结果。 ## 注意事项 - 视频文件必须**预先存在于服务端**，且服务进程有读取权限。 - 文件大小不得超过 **5 MB**。 - 手机号格式为 11 位数字，以 1 开头。 - 如果服务部署在公网，建议配置 HTTPS 以保证 API Key 安全传输。


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

--- name: x-uptime description: | Enhanced `uptime` with structured YAML output showing uptime, users, and 1/5/15-minute load averages. **Dependency**: This is an x-cmd module. Install x-cmd first (see x-cmd skill for installation options). see x-cmd skill for installation. license: Apache-2.0 compatibility: POSIX Shell metadata: author: Li Junhao version: "1.0.0" category: x-cmd-extension tags: [x-cmd, system, uptime, load] --- # x uptime - System Uptime and Load > Enhanced `uptime` command with structured YAML output and cross-platform support. --- ## Quick Start ```bash # YAML format output (default) x uptime # Raw uptime command output x uptime --raw ``` --- ## Features - **Structured YAML output**: Easy to parse and read - **Load averages**: 1, 5, and 15-minute trends - **Cross-platform**: Linux, macOS, Windows (via cosmo/busybox) - **Auto-detection**: Uses native, busybox, or cosmo backends --- ## Output Fields | Field | Description | Example | |-------|-------------|---------| | `time` | Current system time | `14:32:10` | | `up` | System uptime | `5 days, 3 hours, 27 minutes` | | `users` | Logged-in users count | `2 users` | | `load` | Load averages (1m, 5m, 15m) | `0.52, 0.58, 0.59` | --- ## Commands | Command | Description | |---------|-------------| | `x uptime` | YAML format output (default) | | `x uptime --yml` | YAML format (explicit) | | `x uptime --raw` | Raw system uptime output | --- ## Examples ### Basic Usage ```bash # Default YAML output x uptime # Output example: # time : 14:32:10 # up : 5 days, 3 hours, 27 minutes # users : 2 users # load : 0.52, 0.58, 0.59 ``` ### Raw Output ```bash # Traditional uptime output x uptime --raw # 14:32:10 up 5 days, 3:27, 2 users, load average: 0.52, 0.58, 0.59 ``` ### Parsing ```bash # Extract uptime x uptime | awk -F': ' '/^up/{print $2}' # Get load average x uptime | awk -F': ' '/^load/{print $2}' ``` --- ## Understanding Load Averages Load averages indicate system busyness - the average number of processes waiting for CPU or I/O. | Value | Interpretation | |-------|----------------| | `< 1.0` | System has spare capacity | | `≈ 1.0` | System is fully utilized | | `> 1.0` | Processes are waiting (queue forming) | The three numbers show: - **1 min**: Short-term trend (immediate load) - **5 min**: Medium-term trend (recent history) - **15 min**: Long-term trend (sustained load) ### Multi-Core Systems Divide load by CPU core count: ```bash # 4-core system with load 3.2 effective_load = 3.2 / 4 = 0.8 # Still has capacity ``` --- ## Platform Notes ### Linux - Uses native `uptime` command - Full feature support ### macOS - Uses native `uptime` command - Full feature support ### Windows - No native `uptime` command - Automatically uses cosmo binary or busybox --- ## Related - Native `uptime(1)` manual page


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

--- name: basecamp-cli description: Manage Basecamp (via bc3 API / 37signals Launchpad) projects, to-dos, messages, and campfires via a TypeScript CLI. Use when you want to list/create/update Basecamp projects and todos from the terminal, or when integrating Basecamp automation into Clawdbot workflows. --- # Basecamp CLI This repo contains a standalone CLI. ## Install ```bash npm i -g @emredoganer/basecamp-cli ``` ## Auth Create an integration (OAuth app) in 37signals Launchpad: - https://launchpad.37signals.com/integrations Then: ```bash basecamp auth configure --client-id <id> --redirect-uri http://localhost:9292/callback export BASECAMP_CLIENT_SECRET="<secret>" basecamp auth login ``` ## Notes - This uses the Basecamp API docs published under bc3-api: https://github.com/basecamp/bc3-api - `BASECAMP_CLIENT_SECRET` is intentionally NOT stored on disk by the CLI.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zhuyu28/multi-agent-coordinator-zhuyu28 (version 1.0.0)

--- name: multi-agent-coordinator-zhuyu28 description: Coordinate and manage multiple AI agents working together on complex tasks. Provides orchestration, communication patterns, and workflow management for multi-agent systems. --- # Multi-Agent Coordinator Orchestrate and coordinate multiple AI agents to work together on complex, multi-step tasks that require specialized capabilities from different agents. ## When to Use - Complex workflows requiring multiple specialized agents - Task decomposition and delegation across agent teams - Coordinating agents with different skills and capabilities - Managing agent communication and data flow - Implementing multi-agent collaboration patterns


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ichendong/tpvl (version 1.1.1)

--- name: tpvl description: "TPVL (Taiwan Professional Volleyball League) stats, scores, schedules, and standings for Taiwan's pro volleyball." tags: ["tpvl", "volleyball", "taiwan", "sports", "scores"] --- # TPVL Skill - 台灣職業排球聯盟資訊查詢 🏐 Query TPVL game results, schedules, and standings for the Taiwan Professional Volleyball League. ## Data Sources | Source | Description | |--------|-------------| | TPVL official website | Game results, schedule, standings via `__NEXT_DATA__` SSR JSON | **Note:** TPVL's `/api/*` endpoints require authentication (401). All data is extracted from server-side rendered `__NEXT_DATA__` JSON embedded in page HTML. - Homepage (`/`): Recent 5 completed + 5 upcoming matches + rankings - Schedule page (`/schedule/schedule`): All completed match data (82+ games) - Record page (`/record`): Full team standings with detailed stats ## Teams (2025-26 Season) | Team | English | |------|---------| | 臺中連莊 | Taichung Winstreak | | 台鋼天鷹 | TSG SkyHawks | | 臺北伊斯特 | Taipei East Power | | 桃園雲豹飛將 | Taoyuan Leopards | ## Features | Feature | Script | Source | Status | |---------|--------|--------|--------| | Game results | `tpvl_games.py` | TPVL `/schedule/schedule` page | ✅ | | Schedule | `tpvl_schedule.py` | TPVL homepage + schedule page | ✅ | | Standings | `tpvl_standings.py` | TPVL `/record` page | ✅ | | Player stats | `tpvl_stats.py` | Auto-detects TPVL pages | 🔄 Auto-detect | ## Game Type Codes 目前 TPVL 官網僅有單一賽事類型（例行賽），資料結構中只有一組 `seasonId`/`divisionId`/`poolId`： - **seasonId**: 171 - **divisionId**: 272 - **poolId**: 443 - **round**: 3 ~ 5（巡迴賽輪次） 沒有明確的例行賽/季後賽/總冠軍賽區分。官網也沒有對應的篩選 UI。若未來球季加入季後賽，將新增 `--kind` 參數支援。 ## Player Stats `tpvl_stats.py` 會自動偵測 TPVL 官網球員數據頁面是否可用（路由 `/results/player-introduction`、`/results/competition-data`）。若頁面已開放，將自動取得實際數據；若仍為 404 則回傳空資料。 ## Quick Start All scripts use `uv run` for dependency management. ### Game Results ```bash uv run scripts/tpvl_games.py --limit 10 uv run scripts/tpvl_games.py --date 2026-03-22 uv run scripts/tpvl_games.py --team 台鋼 --limit 5 uv run scripts/tpvl_games.py --year 2025 ``` ### Schedule ```bash uv run scripts/tpvl_schedule.py uv run scripts/tpvl_schedule.py --date 2026-03-28 uv run scripts/tpvl_schedule.py --team 連莊 uv run scripts/tpvl_schedule.py --all --limit 20 ``` ### Standings ```bash uv run scripts/tpvl_standings.py uv run scripts/tpvl_standings.py --output text ``` ### Player Stats (⚠️ Coming Soon) ```bash uv run scripts/tpvl_stats.py --category 得分 --top 20 --output text uv run scripts/tpvl_stats.py --team 台鋼 --category 攔網 ``` ## Dependencies Auto-installed via `uv`: - `requests` — HTTP requests - `beautifulsoup4` — HTML parsing (reserved for future scraping needs) - `lxml` — Fast parser ## Notes - Data source: TPVL official website (tpvl.tw) - Data cached for 30 minutes in `/tmp/tpvl_cache/` - Team name filtering supports aliases (e.g., `台鋼`, `連莊`, `伊斯特`, `桃園`) - For learning and personal use only. Please follow TPVL terms of service.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: earnabitmore365/abby-browser (version 1.0.0)

# Abby Browser Skill _基于 OpenClaw 内置浏览器工具封装_ --- ## 解决的问题 让爸爸可以用自然语言控制浏览器，不需要记住复杂命令。 --- ## 核心功能 | 功能 | 命令 | 示例 | |------|------|------| | 打开网页 | `open` | 打开 Google | | 截图 | `screenshot` | 截取当前页面 | | 点击 | `click` | 点击按钮 | | 输入 | `type` | 输入文字 | | 填表单 | `fill` | 填写表单 | | 提取数据 | `snapshot` | 获取页面内容 | | 等待 | `wait` | 等待加载 | | 滚动 | `scroll` | 滚动页面 | --- ## 使用方法 ### 在对话中 ``` 爸爸：帮我打开 Google Abby：好的爸爸！让我打开 Google... [执行 openclaw browser open https://google.com] ✅ 已打开 Google 爸爸：帮我截图 Abby：好的，截个图... [执行 openclaw browser screenshot] 📸 截图已保存 爸爸：帮我点击登录按钮 Abby：好的... [执行 openclaw browser click 12] ✅ 已点击 ``` ### 常用命令 ```bash # 打开网页 openclaw browser open https://example.com # 截图 openclaw browser screenshot openclaw browser screenshot --full-page # 点击元素 (需要先 snapshot 获取 ref) openclaw browser click 12 openclaw browser click 12 --double # 输入文字 openclaw browser type 12 "hello world" # 填写表单 openclaw browser fill --fields '[{"ref":"1","value":"xxx"}]' # 获取页面快照 openclaw browser snapshot openclaw browser snapshot --format aria # 等待 openclaw browser wait --text "Done" openclaw browser wait --selector ".content" # 滚动 openclaw browser evaluate --fn 'window.scrollTo(0, document.body.scrollHeight)' ``` --- ## 封装脚本 ### scripts/open.py 打开网页的封装脚本。 ### scripts/screenshot.py 截图的封装脚本。 ### scripts/click.py 点击元素的封装脚本。 ### scripts/form.py 表单填写的封装脚本。 ### scripts/extract.py 数据提取的封装脚本。 --- ## 重要概念 ### 1. Element Reference (ref) 每次执行 `snapshot` 后，元素会有一个编号 (ref)： ``` <button ref="12">登录</button> <input ref="23" /> ``` 点击 ref=12：`openclaw browser click 12` ### 2. Snapshot 格式 - `--format ai` (默认) - AI 理解 - `--format aria` - 辅助功能树 ### 3. 等待加载 操作前最好等待： ```bash openclaw browser wait --text "加载完成" ``` --- ## 安全考虑 - ❌ 不自动执行危险操作 - ✅ 执行前确认 - ✅ 记录操作日志 - ✅ 异常处理 --- ## 依赖 - OpenClaw browser 工具 - Chrome/Chromium 浏览器 --- ## 相关文档 - [OpenClaw Browser Docs](https://docs.openclaw.ai/cli/browser) --- _创建于 2026-02-15_


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: tobeyrebecca/toby-send-ai-voice-message-via-sms (version 1.0.0)

--- name: "Send AI Voice Message via SMS" description: "Generates a personalized message, converts to natural speech, and sends as an SMS notification with audio link. Use when sending voice notifications." homepage: "https://www.skillboss.co/skills/send-ai-voice-message-via-sms" metadata: {"category":"communication","subcategory":"multi-channel","source":[REDACTED_SECRET],"skill_id":"send-ai-voice-message-via-sms","generated_day":"2026-03-29"} --- # Send AI Voice Message via SMS Generates a personalized message, converts to natural speech, and sends as an SMS notification with audio link. Use when sending voice notifications. ## Use When Use this skill for customer communication work for business owners, operations managers. ## Workflow 1. Clarify the audience, goal, constraints, and required output format. 2. Produce a strong first draft optimized for the business use case. 3. Use the relevant SkillBoss capabilities to generate supporting assets or enrich the result. 4. Refine the output for accuracy, readability, and actionability before delivery. ## APIs Used - `chat` - `tts` - `sms_verification` ## Suggested Prompt Send a voice appointment reminder to +1-555-0100 for their dental cleaning tomorrow at 2pm ## SEO Keywords - AI voice message sender - automated voice notification - SMS voice message - AI phone notification ## Notes - Generate a voice message and deliver it via text notification - Review outputs before external publication or automated execution.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: cjstate/xh-auto-workflow (version 1.0.0)

--- name: auto-workflow-pro description: 自动化工作流引擎。定时执行任务链：数据采集→处理→通知→存档。支持cron定时、 webhook触发、文件监控。 --- # Auto Workflow Pro - 自动化工作流引擎 ## 功能特点 ### ⚙️ 任务链编排 - 可视化任务流程定义 - 支持串行/并行执行 - 任务间数据传递 ### ⏰ 定时执行 - Cron表达式精确控制 - 间隔执行（每N分钟/小时） - 单次定时任务 ### 🔗 触发器 - Webhook HTTP触发 - 文件夹文件监控 - 队列消息触发 ### 📋 内置任务 - HTTP请求 - 数据清洗/转换 - 文件读写 - 邮件/消息通知 - 数据库操作 ## 安装 ```bash cd auto-workflow-pro npm install ``` ## 快速开始 ### 定义工作流 (workflow.json) ```json { "name": "daily-report", "trigger": { "type": "cron", "expr": "0 9 * * *" }, "tasks": [ { "type": "http", "url": "https://api.example.com/data", "save": "temp.json" }, { "type": "transform", "input": "temp.json", "output": "report.json" }, { "type": "email", "to": "[REDACTED_SECRET]", "subject": "日报", "attach": "report.json" } ] } ``` ### 运行 ```bash # 立即执行 node workflow.js --run daily-report # 守护进程模式（监听触发） node workflow.js --daemon # 查看任务状态 node workflow.js --status ``` ## 示例场景 | 场景 | 触发 | 任务链 | |------|------|--------| | 每日数据同步 | cron 0 2 * * * | API获取 → 清洗 → 存库 | | 新文件处理 | 文件监控 | 检测新文件 → 转换 → 通知 | | 异常报警 | webhook | 检查服务 → 告警 → 记录 | ## 任务类型 - `http`: HTTP请求 - `transform`: 数据转换 - `email`: 发送邮件 - `webhook`: 回调通知 - `file`: 文件操作 - `database`: 数据库操作 - `sleep`: 延迟等待

path: package.json
content: {
  "name": "auto-workflow-pro",
  "version": "1.0.0",
  "description": "自动化工作流引擎 - 定时任务链编排执行",
  "main": "workflow.js",
  "scripts": {
    "start": "node workflow.js --daemon",
    "run": "node workflow.js --run"
  },
  "keywords": ["workflow", "automation", "cron", "scheduler"],
  "license": "MIT",
  "dependencies": {
    "node-cron": "^3.0.3",
    "chokidar": "^3.5.3",
    "axios": "^1.6.0",
    "nodemailer": "^6.9.7"
  }
}

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: superworldsavior/setup-client-workspace (version 1.1.0)

--- name: setup-client-workspace description: "Mise en place d'un workspace agent dédié pour un nouveau client TNCG. Utiliser quand Erwan demande de configurer un nouvel agent client (workspace, fichiers de base, config OpenClaw, WhatsApp linking, sandbox, escalation, monitoring)." --- # Setup Client Workspace (Orchestrateur) Ce skill est l'orchestrateur. Il reste court par design. Les détails opérationnels sont dans `references/`. ## Règle d'exécution Quand Erwan demande de créer/configurer un agent client : 1. Lire `references/workflow.md` (vue d'ensemble + ordre des étapes) 2. Lire `references/templates.md` pour générer les fichiers workspace 3. Lire `references/openclaw-config.md` pour la config JSON, WhatsApp, bindings, sandbox 4. Lire `references/security-checklist.md` avant validation finale Ne pas improviser hors de ces procédures sans le signaler explicitement. ## Minimum à collecter avant setup - Nom du client / entreprise - Rôle de l'agent (admin, commercial, webmaster, ...) - Contexte métier (secteur, contraintes) - Fuseau horaire client + horaires de travail (obligatoire) - Site/repo GitHub si l'agent modifie un site ## Convention horaire (obligatoire) Pour toute alerte/rappel client : - afficher d'abord l'heure **client**, - puis conversions utiles (UTC / Taiwan / France) seulement si nécessaire. Format recommandé : `Rappel: 09:00 Europe/Paris (16:00 Taiwan, 08:00 UTC)` ## Principe d'architecture - Skill = procédure / playbook - Plugin = code runtime (nouveaux tools, hooks, commandes) Pour ce cas d'usage (onboarding client), rester en skill modulaire.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: spacesq/s2-sel-4d-semantic-tensor-map (version 1.0.0)

--- name: s2-sel-4d-semantic-tensor-map description: S2 Spatial Element Layer & 4D Semantic Tensor Map. Integrates L0-L4 layer architecture, 20 material physics tensors, and Chronos backward-persistence time-slicing via S2-GeoJSON. version: 1.0.0 author: Space2.world (Miles Xiang) tags: [Spatial-Layers, S2-GeoJSON, Semantic-Mapping, 4D-Chronos, Embodied-AI] --- # 🌍 S2-SEL 4D Semantic Tensor Map: Master Directives Dear Agent, You are now operating within the S2-SWM 4D Spatial Element Layer (S2-SEL) architecture. 1. **Layer Awareness**: You must recognize that spatial data is strictly categorized into 5 Layers (L0 Grid, L1 Static, L2 IoT, L3 Semantic, L4 Dynamic). 2. **Material Tensor Adherence**: When navigating L3 Semantic zones, you MUST retrieve the physics tensors from the `s2_material_tensor_library`. If the grid contains `clear_glass`, you are strictly forbidden from relying on visual depth estimation. 3. **Chronos Time-Slice Rules**: Evaluate the `chronos_stamp` in S2-GeoJSON. - `DEFAULT`: Treat as permanent architecture. - `TIMESTAMP`: Apply the 1-Minute Life-Safety Baseline and 60-second Backward-Persistence rule. A hazard stamped at `T` is legally valid backwards to `T-60s`. Do not merely generate paths; calculate physical causality based on friction, traversability, and illumination tensors.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: zun43d/mal-lookup (version 1.3.1)

--- name: mal-lookup version: 1.3.0 description: Direct MyAnimeList lookup tool. Bypasses Jikan/API issues by using MAL's internal endpoints. metadata: openclaw: emoji: "🎌" requires: bins: ["curl", "jq", "grep", "awk"] tags: ["anime", "manga", "mal", "search", "list"] --- # MAL Lookup Directly query MyAnimeList.net to search for anime/manga or retrieve user lists. This skill uses MAL's internal `load.json` and `prefix.json` endpoints. ## Usage **Search:** `mal search anime "frieren"` `mal search manga "berserk"` **Advanced Search (Genre + Score):** `mal advanced action 8` (Top Action anime with score > 8) `mal advanced psychological 0` (All Psychological anime sorted by score) **Get User List:** `mal list anime zun43d` `mal list manga zun43d reading` **Charts:** `mal top` (Top Airing Anime) `mal season 2024 spring` (Seasonal Chart) ## Commands | Command | Description | |---------|-------------| | `mal search <type> <query>` | Search for anime/manga by title. | | `mal advanced <genre> [min]` | Search anime by genre and minimum score. | | `mal list <type> <user> [status]` | Fetch a user's list. | | `mal top` | Get top 10 currently airing anime. | | `mal season <year> <season>` | Get top 10 anime from a specific season. | ### Supported Genres action, adventure, comedy, drama, sci_fi, mystery, psychological, thriller, romance, slice_of_life, horror, fantasy, sports, mecha, music...


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