OpenClaw/clawhub-security-signals huggingface dataset:
Skill: katherineedwards2475/rdk-x5-media (version 1.0.0)

--- name: rdk-x5-media description: "RDK X5 多媒体处理：音频录制/播放（arecord/aplay/PulseAudio）、hobot_codec 视频编解码、RTSP 拉流/推流、HDMI 分辨率配置、MIPI LCD 触摸屏适配、VNC 远程桌面服务端安装与配置。Use when the user wants to record or play audio, encode/decode video, configure HDMI output, set up LCD screen, use RTSP streaming to view camera on PC, set up VNC desktop server, or stream camera video to remote viewer. Do NOT use for VNC 连接失败排查 (use rdk-x5-network), running AI algorithms (use rdk-x5-ai-detect), camera hardware setup (use rdk-x5-camera), or system backup (use rdk-x5-system)." license: MIT-0 metadata: openclaw: requires: bins: - arecord - ffmpeg compatibility: platform: rdk-x5 --- # RDK X5 Media — 多媒体处理 ## 操作步骤 ### 1. 音频配置 ```bash # 选择音频设备（PulseAudio 通道同步，v3.4.1+） sudo srpi-config # → Audio Options # 查看设备 aplay -l # 播放设备 arecord -l # 录音设备 ``` 支持音频子板：微雪 WM8960 Audio HAT、幻尔载板。 ### 2. 音频录制与播放 ```bash # 录音（16kHz 单声道 16bit 5秒） arecord -D plughw:0,0 -f S16_LE -r 16000 -c 1 -d 5 test.wav # 播放 aplay test.wav # PulseAudio 方式 parecord --rate=16000 --channels=1 test.wav paplay test.wav ``` ### 3. 视频编解码（hobot_codec） ```bash source /opt/tros/humble/setup.bash # NV12 → MJPEG 编码 ros2 launch hobot_codec hobot_codec_encode.launch.py # RGB → MJPEG（USB 摄像头 YUYV 模式） ros2 launch hobot_codec hobot_codec_encode.launch.py \ codec_in_mode:=ros codec_in_format:=rgb8 \ codec_sub_topic:=/image codec_pub_topic:=/image_mjpeg ``` ISP/VIO/编解码模块在 v3.4.1 经过大规模稳定性修复。 ### 4. RTSP 拉流 + AI 推理 ```bash source /opt/tros/humble/setup.bash ros2 launch hobot_rtsp_client hobot_rtsp_client.launch.py \ rtsp_url:="rtsp://admin:password@192.168.1.64:554/stream1" ``` 浏览器 `http://<RDK_IP>:8000` 查看结果。 ### 5. WebSocket 实时预览 ```bash source /opt/tros/humble/setup.bash ros2 launch websocket websocket.launch.py \ websocket_image_topic:=/image_jpeg websocket_only_show_image:=true ``` ### 6. HDMI 显示配置 ```bash xrandr # 查看当前分辨率 xrandr --output HDMI-1 --mode 1920x1080 # 设置分辨率 ``` v3.4.1 已优化多分辨率兼容性，v3.1.1 修复竖屏黑屏问题。 ### 7. MIPI LCD 触摸屏 ```bash sudo srpi-config # → Display Options → MIPI Screen ``` 已适配型号：11.9寸微雪宽屏（v3.4.1）、7款微雪 MIPI DSI 屏（v3.0.1+）。 - 支持双击和长按操作，长按模拟右键 - v3.4.1 修复触摸坐标漂移 ### 8. VNC 远程桌面 ```bash sudo srpi-config # → Interface Options → VNC → Enable ``` ## 常用命令 ```bash v4l2-ctl --list-devices # 列出视频设备 v4l2-ctl -d /dev/video0 --list-formats-ext # 查看格式 v4l2-ctl -d /dev/video0 --set-fmt-video=width=1920,height=1080,pixelformat=MJPG \ --stream-mmap --stream-to=frame.jpg --stream-count=1 # 截图 ``` ## 排查故障 | 现象 | 原因 | 解决 | |------|------|------| | `arecord` 无设备 | 音频子板未接或未配置 | `srpi-config` → Audio 选择设备 | | HDMI 无输出 | 分辨率不兼容 | 换低分辨率显示器测试；检查 `xrandr` | | LCD 触摸偏移 | 型号未正确选择 | `srpi-config` 重新选择屏幕型号 | | websocket 页面空白 | codec 未启动或 topic 不匹配 | 确认 `hobot_codec` 节点运行中 |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: dzy-1026/xfyun-ppt-gen (version 1.0.1)

--- name: ppt-generator description: Generate professional, structured PowerPoint presentations from optimized topic keywords. homepage: https://www.xfyun.cn/doc/spark/PPTv2.html metadata: { "openclaw": { "emoji": "📊", "requires": { "bins": ["python"], "env": ["XF_PPT_APP_ID", "XF_PPT_API_SECRET"] }, "primaryEnv": "XF_PPT_APP_ID" } } --- # 📊 PPT Generator Generate a complete, logically structured, and presentation-ready PowerPoint deck from a professionally optimized topic phrase. Designed for business, technical, and training scenarios. --- ## ✨ Features - Automatic slide outline generation - Clear logical hierarchy - Business-ready formatting - One-command execution - Deterministic single-output generation --- ## 🚀 Usage ```bash python {baseDir}/scripts/index.py generate_ppt "<optimized-topic>" ``` Example: ``` python {baseDir}/scripts/index.py generate_ppt "Artificial Intelligence Industry Trends" ``` ## 🧠 Input Specification (Strict Contract) Before invoking the skill, the topic must undergo **semantic compression optimization**. ### Final Topic Requirements - 5–10 words - Formal report-style title - Clear and domain-specific - No conversational language - Not a full sentence ------ ### Input Optimization Examples | Raw User Request | Optimized Topic | | ----------------------------------- | ---------------- | | 帮我做一个关于人工智能发展现状的PPT | 人工智能发展现状 | | 我要介绍一下公司今年的技术规划 | 公司年度技术规划 | | 做一份给新员工的Java培训PPT | Java新员工培训 | ------ ## ⚠ Constraints - One invocation generates one complete PPT - Raw user input must NOT be passed directly - Environment variables must be configured before execution ------ ## 🔧 Environment Setup Required: - Python available in PATH - Environment variables configured: ``` export XF_PPT_APP_ID=your_app_id export XF_PPT_API_SECRET=your_api_secret ``` ------ ## 📦 Output - Fully structured PPT file - Multi-level slide organization - Presentation-ready content layout - Business-standard formatting ------ ## 🎯 Target Use Cases - Business reports - Strategy planning - Technical presentations - Internal training materials - Academic summaries ------ ## 🛠 Extensibility Future enhancements may include: - Slide count configuration - Language selection - Theme customization - Template switching - AI-assisted topic compression ------ Built for automation workflows and AI-driven document generation.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: johnnywang2001/dep-graph (version 1.0.0)

--- name: dep-graph description: Analyze and visualize project dependency trees from manifest files. Supports Node.js (package.json), Python (requirements.txt, pyproject.toml), Go (go.mod), Rust (Cargo.toml), Ruby (Gemfile), and PHP (composer.json). Use when asked to list dependencies, show a dependency tree, check what packages a project uses, compare prod vs dev deps, or audit dependency counts. --- # Dep Graph Parse and display project dependency trees from manifest files. Auto-detects project type. ## Quick Start ```bash # Analyze current project python3 scripts/dep_graph.py # Analyze specific directory python3 scripts/dep_graph.py /path/to/project # JSON output python3 scripts/dep_graph.py --json # Summary only (just counts) python3 scripts/dep_graph.py --summary # Force project type python3 scripts/dep_graph.py --type node # Hide version constraints python3 scripts/dep_graph.py --no-versions ``` ## Supported Project Types | Type | Manifest File | Groups | |------|--------------|--------| | Node.js | `package.json` | production, dev, peer | | Python | `requirements.txt` | production | | Python | `pyproject.toml` | production | | Go | `go.mod` | production, indirect | | Rust | `Cargo.toml` | production, dev | | Ruby | `Gemfile` | production, dev | | PHP | `composer.json` | production, dev | Auto-detects multiple manifest files in the same project and reports all. ## Output Tree view shows dependencies grouped by type (production/dev/peer) with version constraints. Use `--json` for programmatic processing or `--summary` for quick counts. ## Dependencies - Python 3.8+ (stdlib only, no pip packages needed)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: ckchzh/error-analysis (version 2.0.0)

--- version: "2.0.0" name: Error Analysis description: "错题分析助手。分析错误原因、知识点定位、举一反三出变式题。. Use when you need error analysis capabilities. Triggers on: error analysis." 错题分析助手。错题归类、知识点定位、薄弱环节分析、复习建议。Error analysis for study with categorization, knowledge gap identification. 错题本、考试复盘、学习分析。Use when analyzing exam mistakes. author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # error-analysis 错题分析助手。分析错误原因、知识点定位、举一反三出变式题。 ## Commands All commands via `scripts/error.sh`: | Command | Description | |---------|-------------| | `error.sh analyze "题目" "错误答案" "正确答案"` | 分析错题原因，定位知识点 | | `error.sh knowledge "知识点"` | 知识点详细解析 | | `error.sh similar "题目类型"` | 生成变式练习题 | | `error.sh summary` | 错题统计与薄弱点分析 | | `error.sh help` | 显示帮助信息 | ## Usage ```bash bash scripts/error.sh analyze "求x^2+2x+1=0的解" "x=1" "x=-1" bash scripts/error.sh knowledge "一元二次方程" bash scripts/error.sh similar "函数求导" bash scripts/error.sh summary ``` ## Notes - Python 3.6+ compatible - No external dependencies - 错题记录保存在 `data/errors.json` --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: williamwang-wh/claw-tavily-search-pro (version 1.0.0)

--- name: tavily description: AI-optimized web search via Tavily API. Returns concise, relevant results for AI agents. homepage: https://tavily.com metadata: {"clawdbot":{"emoji":"🔍","requires":{"bins":["node"],"env":["TAVILY_API_KEY"]},"primaryEnv":"TAVILY_API_KEY"}} --- # Tavily Search AI-optimized web search using Tavily API. Designed for AI agents - returns clean, relevant content. ## Search ```bash node {baseDir}/scripts/search.mjs "query" node {baseDir}/scripts/search.mjs "query" -n 10 node {baseDir}/scripts/search.mjs "query" --deep node {baseDir}/scripts/search.mjs "query" --topic news ``` ## Options - `-n <count>`: Number of results (default: 5, max: 20) - `--deep`: Use advanced search for deeper research (slower, more comprehensive) - `--topic <topic>`: Search topic - `general` (default) or `news` - `--days <n>`: For news topic, limit to last n days ## Extract content from URL ```bash node {baseDir}/scripts/extract.mjs "https://example.com/article" ``` Notes: - Needs `TAVILY_API_KEY` from https://tavily.com - Tavily is optimized for AI - returns clean, relevant snippets - Use `--deep` for complex research questions - Use `--topic news` for current events


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: smallersoup/bark-push2 (version 1.0.0)

--- name: bark-push description: "专业的 Bark 推送技能。支持通过 LobeHub 市场规范定义的通知格式发送消息。" metadata: { "openclaw": { "requires": { "bins": ["node"] } } } --- # Bark Push 技能 (标准版) 🦞 ## 简介 这是 `openclaw-skills-bark-push` 的本地重构版。它完全兼容 LobeHub 技能市场的调用规范。 ## 参数说明 - **message** (string, 必填): 推送的消息内容。 - **title** (string, 可选): 消息标题。 - **key** (string, 可选): 您的 Bark Key（如果留空，将读取 BARK_KEY 环境变量）。 ## 调用示例 ```bash node push.js "Hello from OpenClaw" --title "龙虾推送" ```


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

--- name: alimerce description: AliMerce 商城 AI 助手技能 - 客服、销售、商品管理、订单处理 --- # AliMerce 商城 AI 助手 你是 AliMerce 商城的 AI 助手「小Ali」，擅长客户服务和销售支持。 ## 核心能力 - **客户服务**：回答商品咨询、处理订单问题 - **销售支持**：推荐商品、协助下单 - **客户记忆**：记住客户偏好，提供个性化服务 ## 工具使用指南 ### 商品查询 当客户询问商品时： - 使用 `product_list` 搜索商品 - 使用 `product_get` 获取商品详情 - 优先展示客户关注的要点（价格、库存、发货时间） ### 订单处理 当客户查询订单时： - 使用 `order_list` 或 `order_get` 查询 - 清晰说明当前状态和预计时间 - 如需修改状态，触发审核流程 ### 客户偏好 记住客户信息： - 首次咨询时使用 `customer_preferences_get` 查看偏好 - 客户明确偏好后使用 `customer_preferences_update` 更新 - 记住常用语言、偏好品类、联系方式等 ## 沟通规范 ### 语气 - 友好、专业、耐心 - 使用客户常用语言（中文/英文/蒙文） - 不确定时诚实告知，不编造信息 ### 响应格式 ``` 商品咨询 → 列出关键信息 + 确认是否需要 订单查询 → 状态说明 + 下一步指引 下单请求 → 确认商品 + 价格 + 配送信息 投诉建议 → 认真倾听 + 记录 + 反馈 ``` ## 高风险操作 以下操作必须经过人工审核： | 操作 | 触发条件 | 处理方式 | |------|----------|----------| | 删除商品 | `product_delete` | 创建审批请求，等待回复 | | 修改订单状态 | `order_update` (shipped/delivered) | 创建审批请求 | | 提升管理员 | `user_update` (role: admin) | 拒绝并说明原因 | ## 响应示例 ### 客户：这件T恤有库存吗？ ``` product_list status=published category=<客户询问的分类> 回复：您好！这款夏季T恤有现货，99元，包邮。 库存充足，现在下单明天可以发货。需要帮您下单吗？ ``` ### 客户：帮我看看订单到哪了 ``` order_get id=<订单ID> 回复：您的订单已于今天上午发货，预计3-5天送达。 快递单号：SF1234567890 您可以点击链接追踪物流。如有其他问题随时告诉我。 ``` ### 客户：我想退货 ``` order_get id=<订单ID> 回复：非常抱歉给您带来不便。您的订单尚在配送中， 我可以帮您申请拦截并退款。请问是什么原因要退货呢？ （了解原因后协助处理） ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yuhui435/community-data-process (version 1.0.0)

--- name: community-data-process description: > 北汽社群数据导出：数据清洗 → 数据校对 → 数据合并。 从客户群导出文件中筛选温冷一期和试点店标签数据， 校对关键指标一致性，增量合并到 BI_社群数据上传表。 统计日期使用源文件创建时间（下载日期）。 每天 00:55 自动执行。 --- # 北汽社群数据导出 每日社群数据导出 → 清洗 → 校对 → 合并到 BI 系统。 ## 流程概览 ``` 1. 数据清洗 → 2. 数据校对 → 3. 数据合并 → 4. 最终验证 ``` ## 使用方式 ### 一键执行全流程 ```bash python ~/.openclaw/workspace-pm/skills/community-data-process/run.py ``` ### 分步执行 ```bash # 第 1 步：数据清洗 python ~/.openclaw/workspace-pm/skills/community-data-process/run.py clean # 第 2 步：数据校对 python ~/.openclaw/workspace-pm/skills/community-data-process/run.py audit # 第 3 步：数据合并 python ~/.openclaw/workspace-pm/skills/community-data-process/run.py merge # 第 4 步：最终验证 python ~/.openclaw/workspace-pm/skills/community-data-process/run.py verify ``` ## 规则 ### 清洗规则 - 源文件：Downloads 目录下按**创建时间（下载时间）**排序，取最新的 `客户群导出*.xlsx` - 筛选条件：O 列（群标签）= 温冷一期 或 试点店 - 数字列格式转换：群人数、员工人数、客户人数、今日入群、今日退群、今日消息 → int ### 校对规则 - 三方对比：源文件 vs 清理后 vs 合并后 - 8 个指标全部一致才通过 - 数据质量：无空值、无负值 ### 合并规则 - 模式：增量添加（不去重） - 列映射：源文件 A-O 列 → 目标文件 E-S 列 - D 列统计日期 = 源文件的**创建时间（下载日期）**，文件是哪天下载的就填哪天（不是脚本执行日期） - A-C 列留空 ### 列映射 | 源文件 | → | 目标文件 | 列名 | |-------|---|---------|------| | A | → | E | 群 ID | | B | → | F | 群名称 | | C | → | G | 群主 | | D | → | H | 群管理员 | | E | → | I | 群人数 | | F | → | J | 群活跃 | | G | → | K | 群类型 | | H | → | L | 员工人数 | | I | → | M | 客户人数 | | J | → | N | 今日入群 | | K | → | O | 今日退群 | | L | → | P | 今日消息 | | M | → | Q | 入群时间 | | N | → | R | 最后发言时间 | | O | → | S | 群标签 | ## 输出文件 | 文件 | 说明 | |------|------| | `客户群导出_清理后_温冷一期 + 试点店_YYYYMMDD.xlsx` | 清洗后数据 | | `BI_社群数据上传_已更新_YYYYMMDD.xlsx` | 合并后最终文件 | | `数据校对报告_YYYYMMDD.txt` | 校对报告 | ## 常见问题 ### Q1: 今日退群数据不一致 检查是否使用了正确的源文件。不同日期导出的文件数据不同。 ### Q2: 统计日期错误 脚本自动读取源文件的下载日期，不需要手动指定。 ### Q3: 数字列显示为文本 脚本自动转换 6 个数字列为 int 格式。 ## 依赖 - Python 3.11+ - pandas - openpyxl


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: ivangdavila/events (version 1.0.0)

--- name: Events description: Build a personal event system for tracking concerts, conferences, parties, appointments, and everything in between. metadata: {"clawdbot":{"emoji":"📅","os":["linux","darwin","win32"]}} --- ## Core Behavior - User mentions event → offer to track it - User planning event → help organize details - User asks what's coming up → surface relevant events - Create `~/events/` as workspace ## File Structure ``` ~/events/ ├── upcoming/ │ ├── concerts/ │ ├── conferences/ │ ├── social/ │ └── appointments/ ├── hosting/ ├── past/ ├── annual/ │ └── recurring.md └── calendar.md ``` ## Event Entry ```markdown # radiohead-may.md ## Event Radiohead — MSG ## Date & Time May 15, 2024, 8:00 PM ## Venue Madison Square Garden, NYC ## Tickets Section 112, Row 8 Confirmation: TM-789456 ## Logistics Doors 7pm, meeting Jake at 6:30 No large bags allowed ``` ## Hosting an Event ```markdown # hosting/birthday-2024/ ├── overview.md # date, venue, status checklist ├── guests.md # confirmed, pending, declined └── details.md # food, drinks, music, setup ``` Guest tracking: ```markdown ## Confirmed (12) - Sarah + 1 - Jake ## Pending (5) - Tom — following up ## Declined (2) - Amy — out of town ``` ## Annual Recurring ```markdown # recurring.md ## Birthdays - Mom: March 22 - Dad: July 8 ## Annual Events - Company retreat: September - Industry conference: March (register early) ``` ## Quick Calendar View ```markdown # calendar.md ## March 2024 - 5: Jake's birthday party - 12-14: SXSW Austin - 22: Mom's birthday ``` ## Multi-Day Events ```markdown # sxsw-2024/ ├── overview.md # dates, location, registration, travel └── schedule.md # day-by-day sessions and plans ``` ## What To Track - Date, time, location - Tickets/confirmation numbers - Logistics (parking, doors, dress code) - Who you're going with - RSVPs when hosting ## What To Surface - "Concert next week — doors at 7pm" - "Mom's birthday in 5 days" - "Registration closes tomorrow" - "15 confirmed for Saturday" ## Progressive Enhancement - Start: add upcoming events - Add annual dates (birthdays, holidays) - Track past events for memories - Build hosting checklists ## What NOT To Do - Forget confirmation numbers - Miss registration deadlines - Lose track of RSVPs when hosting - Skip logistics details


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sparkingskin-tech/vps-agent-migration (version 1.0.0)

--- name: vps-agent-migration description: 将本地 OpenClaw 子 Agent 迁移到 VPS 上运行。包括：rsync 复制文件、配置 Discord Bot、添加 bindings 路由、禁用本地账号避免冲突。使用场景：当需要将本地的 creative/dev/qa/strategist/pojun 等子 Agent 迁移到远程 VPS 时使用此 skill。 --- # VPS Agent Migration 将本地 OpenClaw Agent 迁移到 VPS 上运行。 ## 前提条件 - VPS 已安装 OpenClaw - 本地已配置好要迁移的 Agent（workspace、SOUL.md 等） - 需要迁移的 Agent 名称（如 creative, dev, qa 等） - SSH 访问 VPS（sshpass 或配置 SSH key） ## 迁移步骤 ### Step 1: 连接 VPS 并复制文件 ```bash # 连接 VPS sshpass -p 'VPS密码' ssh -o StrictHostKeyChecking=no root@VPS_IP # 复制 Agent 文件（排除 sessions、.DS_Store、memory.md） rsync -avz --exclude='sessions' --exclude='.DS_Store' --exclude='memory.md' \ ~/.openclaw/agents/[agent名]/ root@VPS_IP:/root/.openclaw/agents/[agent名]/ ``` ### Step 2: 获取本地 Discord Token 从本地 `~/.openclaw/openclaw.json` 中查找对应 Agent 的 token： ```bash cat ~/.openclaw/openclaw.json | grep -A5 '"[Discord_ID]":' ``` ### Step 3: 在 VPS 上添加 Discord 账号 在 VPS 上使用 Python 更新配置： ```bash sshpass -p 'VPS密码' ssh -o StrictHostKeyChecking=no root@VPS_IP 'python3 -c " import json with open(\"/root/.openclaw/openclaw.json\") as f: data = json.load(f) data[\"channels\"][\"discord\"][\"accounts\"][\"[Discord_ID]\"] = { \"name\": \"[Agent名字]\", \"enabled\": True, \"token\": \"[Token]\", \"groupPolicy\": \"allowlist\", \"streaming\": \"off\" } with open(\"/root/.openclaw/openclaw.json\", \"w\") as f: json.dump(data, f, indent=2) "' ``` ### Step 4: 更新 Bindings ```bash sshpass -p 'VPS密码' ssh -o StrictHostKeyChecking=no root@VPS_IP 'openclaw config set bindings \"[{\\\"agentId\\\":\\\"[agentId]\\\",\\\"match\\\":{\\\"channel\\\":\\\"discord\\\",\\\"accountId\\\":\\\"[Discord_ID]\\\"}}]\"' ``` ### Step 5: 重启 VPS Gateway ```bash sshpass -p 'VPS密码' ssh -o StrictHostKeyChecking=no root@VPS_IP "openclaw gateway restart" ``` ### Step 6: 禁用本地账号 ```bash # 禁用本地账号 openclaw config patch --json '{"channels": {"discord": {"accounts": {"[Discord_ID]": {"enabled": false}}}}}' # 重启本地 Gateway openclaw gateway restart ``` ## 关键坑点 1. **requireMention**: 默认 `true` 会导致 Agent 不自动回复，需要在 `guilds` 中设为 `false` 2. **多账号配置**: `channels.discord.token` 是默认账号，`channels.discord.accounts[id].token` 是多账号模式 3. **SSH 连接**: 偶尔会断开，多试几次即可 4. **Token 获取**: Discord Bot Token 在 openclaw.json 的 `channels.discord.accounts[id].token` 中 ## 常见 Discord ID 格式 - 频道 ID: 18位数字（如 1475374006226915434） - 用户/Bot ID: 18位数字（如 1475676302215221278）


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: lnj22/multilingual-video-dubbing-ffmpeg-format-conversion (version 0.1.0)

--- name: FFmpeg Format Conversion description: Convert media files between formats - video containers, audio formats, and codec transcoding --- # FFmpeg Format Conversion Skill Convert media files between different formats and containers. ## When to Use - Convert video containers (MP4, MKV, AVI, etc.) - Convert audio formats (MP3, AAC, WAV, etc.) - Transcode to different codecs - Copy streams without re-encoding (fast) ## Basic Conversion ```bash # Convert container format (re-encode) ffmpeg -i input.avi output.mp4 # Copy streams without re-encoding (fast, no quality loss) ffmpeg -i input.mp4 -c copy output.mkv # Convert with specific codec ffmpeg -i input.mp4 -c:v libx264 -c:a aac output.mp4 ``` ## Video Codec Conversion ```bash # H.264 ffmpeg -i input.mp4 -c:v libx264 output.mp4 # H.265 (better compression) ffmpeg -i input.mp4 -c:v libx265 output.mp4 # VP9 (web optimized) ffmpeg -i input.mp4 -c:v libvpx-vp9 output.webm # AV1 (modern codec) ffmpeg -i input.mp4 -c:v libaom-av1 output.mp4 ``` ## Audio Format Conversion ```bash # MP3 ffmpeg -i input.wav -acodec libmp3lame -q:a 2 output.mp3 # AAC ffmpeg -i input.wav -c:a aac -b:a 192k output.m4a # Opus (best quality/bitrate) ffmpeg -i input.wav -c:a libopus -b:a 128k output.opus # FLAC (lossless) ffmpeg -i input.wav -c:a flac output.flac ``` ## Quality Settings ```bash # CRF (Constant Rate Factor) - lower is better quality ffmpeg -i input.mp4 -c:v libx264 -crf 23 output.mp4 # Bitrate ffmpeg -i input.mp4 -b:v 2M -b:a 192k output.mp4 # Two-pass encoding (best quality) ffmpeg -i input.mp4 -c:v libx264 -b:v 2M -pass 1 -f null /dev/null ffmpeg -i input.mp4 -c:v libx264 -b:v 2M -pass 2 output.mp4 ``` ## Presets ```bash # Encoding speed presets (faster = larger file) ffmpeg -i input.mp4 -c:v libx264 -preset fast output.mp4 # Options: ultrafast, superfast, veryfast, faster, fast, medium, slow, slower, veryslow # Quality presets ffmpeg -i input.mp4 -c:v libx264 -preset slow -crf 18 output.mp4 ``` ## Batch Conversion ```bash # Convert all MKV to MP4 for f in *.mkv; do ffmpeg -i "$f" -c copy "${f%.mkv}.mp4" done # Convert with re-encoding for f in *.avi; do ffmpeg -i "$f" -c:v libx264 -c:a aac "${f%.avi}.mp4" done ``` ## Common Codecs ### Video - **H.264** (libx264) - Universal compatibility - **H.265** (libx265) - Better compression - **VP9** (libvpx-vp9) - Open standard - **AV1** (libaom-av1) - Modern codec ### Audio - **AAC** (aac) - Universal - **MP3** (libmp3lame) - Legacy - **Opus** (libopus) - Best quality/bitrate - **FLAC** (flac) - Lossless ## Notes - Use `-c copy` when possible for speed (no re-encoding) - Re-encoding is slower but allows codec/quality changes - CRF 18-23 is good quality range for H.264 - Preset affects encoding speed vs file size tradeoff


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: amdf01-debug/sw-signup-flow-cro (version 1.0.0)

# Signup Flow CRO Skill ## Trigger Audit and optimise signup flows for higher conversion. **Trigger phrases:** "signup flow", "registration optimisation", "signup conversion", "reduce signup friction" ## Process 1. **Map**: Document every step from CTA click to account created 2. **Measure**: Identify drop-off at each step 3. **Reduce**: Eliminate unnecessary steps, defer non-critical fields 4. **Accelerate**: Social auth, magic links, progressive profiling 5. **Activate**: Connect signup to first value moment ## Key Principles - Minimum viable signup: email only (or social auth) - Defer profile completion to post-signup - Progress indicator if >2 steps - Pre-fill where possible (social data, URL detection) - Email verification: don't block access — send verification in parallel - Show value preview before asking for signup - "Sign up free" > "Create account" > "Register" ## Output Redesigned signup flow with: step-by-step wireframe description, field requirements per step, estimated conversion improvement, and implementation notes.


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