OpenClaw/clawhub-security-signals huggingface dataset:
Skill: rogue-agent1/web-monitor (version 1.0.1)

--- name: web-monitor description: Monitor web pages for content changes and get alerts. Track URLs, detect updates, view diffs. Use when asked to watch a website, track changes on a page, monitor for new posts/content, set up page change alerts, or check if a site has been updated. Supports CSS selectors for targeted monitoring. --- # Web Monitor Track web pages for changes. Stores snapshots, computes diffs, supports CSS selectors. ## Quick Start ```bash # Add a URL to watch uv run --with beautifulsoup4 python scripts/monitor.py add "https://example.com" --name "Example" # Add with CSS selector (monitor specific section) uv run --with beautifulsoup4 python scripts/monitor.py add "https://example.com/pricing" -n "Pricing" -s ".pricing-table" # Check all watched URLs for changes uv run --with beautifulsoup4 python scripts/monitor.py check # Check one specific URL uv run --with beautifulsoup4 python scripts/monitor.py check "Example" # List watched URLs uv run --with beautifulsoup4 python scripts/monitor.py list # View last diff uv run --with beautifulsoup4 python scripts/monitor.py diff "Example" # View current snapshot uv run --with beautifulsoup4 python scripts/monitor.py snapshot "Example" --lines 50 # Remove uv run --with beautifulsoup4 python scripts/monitor.py remove "Example" ``` ## Commands | Command | Args | Description | |---------|------|-------------| | `add` | `<url> [-n name] [-s selector]` | Add URL to watch, take initial snapshot | | `remove` | `<url-or-name>` | Stop watching a URL | | `list` | `[-f json]` | List all watched URLs with stats | | `check` | `[url-or-name] [-f json]` | Check for changes (all or one) | | `diff` | `<url-or-name>` | Show last recorded diff | | `snapshot` | `<url-or-name> [-l lines]` | Show current snapshot | ## Output Symbols - 🔔 CHANGED — page content changed (shows diff preview) - ✅ No changes - 📸 Initial snapshot taken - ❌ Error fetching ## Data Stored in `~/.web-monitor/` (override with `WEB_MONITOR_DIR` env var): - `watches.json` — watch list config - `snapshots/` — stored page content + diffs ## Tips - Use `--selector` to monitor specific elements (prices, article lists, etc.) - Use `--format json` for programmatic checking (heartbeat integration) - CSS selectors require beautifulsoup4 (included via `--with` flag) - Text is normalized to reduce noise from timestamps, whitespace, ads


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (CRITICAL)
Skill: 1yihui/minimax-team-rules (version 1.0.0)

--- name: minimax-team-rules description: Shared MiniMax / MMX CLI operating rules for XiaoMei, DaLong, YuanQi, and the main coordinator. Trigger this skill whenever the task involves MiniMax, minimax, mmx, mmx-cli, Token Plan, quota, quota interpretation, speech-hd, music-2.6, music-cover, lyrics_generation, image-01, coding-plan-vlm, coding-plan-search, MiniMax capability mapping, OpenClaw↔MiniMax tool mapping, or agent-specific delivery/routing rules. Also trigger when the user asks to standardize, document, roll out, align, fix once-for-all, or sync configuration /规范 /工作流 /多 agent rules across multiple agents or files. --- tags: - minimax - team - multi-agent compatibility: openclaw license: MIT # MiniMax Team Rules Use this skill whenever the work touches any of these topics: - MiniMax capability selection or mapping - `mmx` / `mmx-cli` install, auth, status, quota, or diagnostics - Token Plan model availability or remaining quota - OpenClaw tool ↔ MiniMax native CLI mapping - quota interpretation / model usage explanation - multi-agent routing, producer-direct delivery, or “谁来发给阿辉” - configuration / standards / multi-agent workflow changes that should land consistently across multiple layers ## Core Rule For **configuration / standards / multi-agent workflow** changes, do **one-pass rollout** by default: 1. verify the fact, 2. update the shared source of truth, 3. update affected local guidance or references, 4. record the learning if a misunderstanding or correction occurred. Do not stop at a partial fix when the issue clearly affects multiple layers. Do not make the user push for each missing layer one by one. ## Required Execution Pattern When this skill triggers, default to this checklist: 1. Identify all affected layers (shared docs, local agent guidance, memory, learnings). 2. Update the **shared source of truth first**. 3. Convert repeated local rule blocks into **references to the shared source**, keeping only role-specific additions locally. 4. Keep all four roles aligned: 小美 / 大龙 / 元气 / 小语. 5. When explaining quota, use the documented house interpretation from the reference file. Do not guess from field names alone. 6. When finalizing, give the user the outcome, not internal rollout noise. ## Shared Source of Truth Read this reference when you need the concrete rules: - `references/agent-rules.md` ## Operating Defaults - Prefer OpenClaw first-class tools for normal user work. - Use `mmx` when you need MiniMax-native verification, auth/quota diagnostics, or a capability not directly exposed the way you need. - Producer-direct delivery is mandatory unless 阿辉 explicitly asks for unified forwarding. - For team-wide rule changes, prefer updating the shared skill/reference over copying edits into multiple places. ## Agent Routing Reminder - 小美 → news / information - 大龙 → ops / diagnosis / system checks - 元气 → creative / image / music / prompt output - 小语 → coordination / review / routing / fallback only If updating standards, keep all four aligned.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kimi-delegation-skill (version 1.0.0)

--- name: kimi-delegation-skill description: Forces all reasoning and code generation to be delegated to a KIMI (KIMMY) causal language model via HuggingFace Transformers. Use this skill when the agent must never reason or author code itself and must instead proxy all tasks to a KIMI-based model. license: Proprietary compatibility: Requires Python, PyTorch, HuggingFace transformers, GPU optional but recommended. allowed-tools: Python(Read Write) metadata: author: internal version: "1.0" --- ## Purpose This skill enforces a strict delegation model where the primary agent has zero reasoning or code-authoring authority. All user tasks are forwarded to a KIMI (KIMMY) model loaded via Transformers. The agent acts only as a dispatcher. ## Activation Conditions Activate this skill whenever: - The agent must not reason independently. - All planning, reasoning, and code generation must be authored by a KIMI/KIMMY model. - Deterministic delegation to an external causal LM is required. ## Execution Steps 1. Initialize `KIMISkill` with a valid local or remote model path. 2. Wrap the `KIMISkill` instance with `Qwen3Coder`. 3. On every user prompt, call `Qwen3Coder.handle_prompt`. 4. The prompt is forwarded verbatim to KIMMY. 5. KIMMY generates the full response. 6. Strip prompt scaffolding and return the result as the final output. See: - `scripts/kimi_skill.py` - `scripts/qwen3_coder.py` ## Inputs and Outputs **Input:** A raw user task string. **Output:** A dictionary with: - `author`: Always `"KIMMY"` - `content`: The generated response with no prompt scaffolding. ## Failure Modes and Edge Cases - Model path invalid or unavailable: initialization fails. - Insufficient VRAM: model may fall back to CPU or fail to load. - Extremely long tasks may exceed context limits. - If generation fails, no fallback reasoning is permitted. The agent must not attempt to recover by reasoning itself. ## References Technical details and architectural rationale are in: - `references/REFERENCE.md`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: drones277/gemini-tg-image-gen (version 1.0.0)

--- name: gemini-tg-image-gen description: Generate images via OpenRouter (google/gemini-2.5-flash-image) and send to Telegram. Use when user asks for AI-generated images in TG. --- # Gemini TG Image Gen (OpenRouter) ## Workflow 1. Immediately notify user in Telegram: `"⏳ Идёт генерация, подождите немного..."` 2. Use OpenRouter model `google/gemini-2.5-flash-image`. 3. Read API key from env: `OPENROUTER_API_KEY`. 4. Run script to generate and save image locally. 5. Send the image to Telegram using the `message` tool (local file path). 6. NO_REPLY. ## Usage ```bash OPENROUTER_API_KEY=... python3 scripts/generate_image.py "<prompt>" ``` The script prints a JSON object with `paths`. ## Telegram Send ``` # step 1: waiting message message action=send channel=telegram text="⏳ Идёт генерация, подождите немного..." # step 5: send image message action=send channel=telegram media="/root/.openclaw/workspace/tmp/openrouter_image_*.png" caption="Generated: <prompt>" ``` After sending, use `NO_REPLY`.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: xiaojiou176/switchyard-runtime-diagnostics (version 1.0.0)

# Switchyard Runtime Diagnostics Teach the agent how to install, connect, and use Switchyard's read-only MCP runtime diagnostics surface. ## Use this skill when - the user wants to diagnose one provider or runtime boundary - the host can run the local `stdio` MCP server - the agent needs read-only runtime and catalog truth before any human action ## What this packet teaches - how to attach the current Switchyard MCP server - which runtime and catalog tools are safe first - how to separate internal blockers from external blockers - how to keep claims grounded in `partial`, `read-only`, and `package-ready` ## Start here 1. Read [references/INSTALL.md](references/INSTALL.md) 2. Load the right host config from: - [references/OPENHANDS_MCP_CONFIG.json](references/OPENHANDS_MCP_CONFIG.json) - [references/OPENCLAW_MCP_CONFIG.json](references/OPENCLAW_MCP_CONFIG.json) 3. Skim the tool surface in [references/CAPABILITIES.md](references/CAPABILITIES.md) 4. Run the first diagnostic loop in [references/DEMO.md](references/DEMO.md) 5. If the attach or proof path fails, use [references/TROUBLESHOOTING.md](references/TROUBLESHOOTING.md) ## Guardrails - do not write to external accounts - do not turn `partial` into `supported` - do not turn `auth-status ready` into live-ready


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: archimondecy/baidu-maps-poi-ai-search (version 1.0.0)

--- name: baidu-maps-poi-ai-search description: Search and get details for POI (points of interest) using Baidu Maps API. Use for searching places, restaurants, hotels, attractions, and retrieving detailed POI information by UID. metadata: { "openclaw": { "emoji": "📍", "requires": { "bins": ["python3"], "env": ["BAIDU_AK"], "primaryEnv": "BAIDU_AK" } } } --- # Baidu Maps POI AI Search Skill 百度地图 POI AI搜索,通过百度地图AI搜接口，可以查找地点的名称、地址、类别、经营范围、属性内容。 > ⚠️ **环境配置**：使用前请设置 `BAIDU_AK` 环境变量（百度地图开放平台申请的 AK）。脚本内不含默认 AK，需自行配置。 ## 接口概览 | 接口 | 脚本 | 说明 | |------|------|------| | 多维检索 | `search.py` | 搜索 POI，名称(北京大学)、地址(北京市上地十街10号)、类别(火锅)、经营范围(买包子)、复杂属性内容(西二旗附近适合带宠物的餐厅)。| ## 1. 多维检索 (search.py) ```bash python3 skills/baidu-maps-poi-ai-search/scripts/search.py '<JSON>' ``` ### 请求参数 | Param | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | query | str | yes | - | 检索关键字，如"美食"、"海底捞"、"看日出的地方"、"能带宠物吃饭的餐厅" | | region | str | yes | - | 行政区划，如"北京"、"北京市海淀区" | | scope | int | yes | 2 | 2=详细信息 | | page_num | int | no | 0 | 分页页码，从0开始 | | center | str | no | - | 中心点坐标 `lat,lng`，配合 sort_name=distance | | coord_type | int | no | 3 | 坐标类型：1=wgs84ll, 2=gcj02ll, 3=bd09ll | ### 多维检索 Examples ```bash # 搜索名称 python3 skills/baidu-maps-poi-ai-search/scripts/search.py '{"query":"北京大学","region":"北京","scope":2,"page_size":5}' # 搜索类别 python3 skills/baidu-maps-poi-ai-search/scripts/search.py '{"query":"火锅","region":"北京","scope":2,"page_size":5}' # 口语化搜索 python3 skills/baidu-maps-poi-ai-search/scripts/search.py '{"query":"故宫附近能多人聚会的地方","region":"北京","scope":2,"page_size":5}' ``` ## API 文档 - 多维检索：`https://api.map.baidu.com/api_place_pro/v1/region`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: bifang988/boss-greeting-message (version 1.0.0)

--- name: boss-greeting description: >- BOSS直聘打招呼语生成器。调用 boss-cli 获取目标职位详情，分析岗位核心要求， 再对照用户简历找出最匹配的经历，生成一段不超过200字的个性化打招呼语。 当用户说"帮我写打招呼语"、"投这个岗位怎么打招呼"、"生成boss打招呼"等时触发。 requires: - boss-cli --- # BOSS直聘打招呼语生成器 ## Step 0：检查 boss-cli 登录状态 ```bash boss status ``` - **已登录** → 跳到 Step 1 - **未登录** → 提示用户： > 需要先登录 BOSS直聘： > ```bash > boss login > ``` > 会自动读取浏览器 Cookie，或弹出二维码扫码登录。 > 登录完成后重新触发本 skill。 > 如果还没安装 boss-cli，先安装： > ```bash > uv tool install kabi-boss-cli > ``` --- ## Step 1：获取目标职位信息 如果用户没有提供职位，询问： > 你想投哪个职位？可以直接告诉我： > 1. BOSS直聘的职位链接 > 2. 或者职位名称 + 公司名（我来帮你搜） **情况A：用户提供了职位链接** 从链接中提取职位 ID（URL 中的数字部分），直接获取详情： ```bash boss show <职位ID> ``` **情况B：用户提供职位名称 + 公司名** 先搜索，展示结果让用户确认： ```bash boss search "<职位名称>" --company "<公司名>" ``` 展示搜索结果，请用户选择序号，再： ```bash boss show <序号> ``` 记录以下职位信息供后续分析： - 职位名称 - 公司名称、规模、融资阶段 - 薪资范围 - 岗位职责（JD） - 任职要求 --- ## Step 2：获取用户简历 询问用户： > 请提供你的简历，可以是： > 1. 简历文件路径（支持 .md / .txt / .pdf） > 2. 或直接把简历内容粘贴过来 读取简历内容，提取： - 当前/最近职位和公司 - 工作年限 - 核心技能 - 最有代表性的项目/成果（优先提取有数据的成果，如「提升XX%」「负责XX万用户」） --- ## Step 3：分析匹配点 综合职位详情和简历，分析： **岗位最关注什么：** - 从 JD 的职责描述中，找出排在前3位的核心能力要求 - 从任职要求中，找出硬性门槛（学历/年限/技能）和加分项 - 结合公司阶段（初创/成长/上市）判断他们更看重「经验」还是「潜力」 **简历中最匹配的部分：** - 找出与岗位核心要求直接对应的经历或技能 - 优先选有具体数字/成果的内容，而非泛泛描述 - 最多提取3个匹配点，不要堆砌 --- ## Step 4：生成打招呼语 基于以上分析，生成打招呼语，严格遵守以下规则： **内容规则：** - 第一句点明应聘岗位 - 核心内容：用1-2句话说出与岗位最匹配的经历/能力，必须具体，不能只说「有相关经验」 - 结尾：简短表达期待沟通的意愿，不要用「期待您的回复」这类套话 - **严格不超过200字** **风格规则：** - 口语化，像真人写的，不像模板 - 不用「贵公司」「您好」等过度正式的词 - 不堆砌形容词（「优秀」「出色」「丰富」一律删掉） - 不写自己的弱点或不确定的内容 生成 **2个版本**： - **版本A（经验导向）**：突出过往成果，适合强调匹配度 - **版本B（简洁直接）**：一句话定位 + 一句话亮点，适合对方很忙 每个版本后注明实际字数。 --- ## 输出模板 ``` ## 📋 职位分析 **公司：** {公司名} | {融资阶段} | {规模} **岗位核心要求（TOP3）：** 1. {要求1} 2. {要求2} 3. {要求3} **你的最强匹配点：** - {匹配点1} - {匹配点2} --- ## ✉️ 打招呼语 **版本A（经验导向）**（XX字） {打招呼语内容} **版本B（简洁直接）**（XX字） {打招呼语内容} --- 💡 使用建议：如果对方是 HR，用版本A；如果对方是业务负责人，用版本B。 ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nhathuynguyen19/cmus (version 1.0.1)

--- name: cmus description: AI skill to launch cmus in a Xubuntu terminal and enforce playback rules (single track vs shuffle folder). Robust against high latency and headless daemon environment. homepage: https://github.com/cmus/cmus metadata: {"clawdbot":{"emoji":"🎹","requires":{"bins":["cmus","cmus-remote","xfce4-terminal","pgrep"]},"install":[{"id":"apt-cmus","kind":"apt","formula":"cmus","bins":["cmus","cmus-remote"],"label":"Install cmus (apt)"}]}} --- # cmus (OpenClaw Playback Controller) Workflow: Receive file path from yt-dlp -> Launch cmus UI (if not running) -> Wait for socket -> Apply user's specific playback rules -> Play. ## Find the active daemon & Launch UI When OpenClaw runs in the background, it lacks X11/Wayland display variables. The agent MUST inject the environment variables and dynamically poll for the cmus socket instead of using hardcoded sleep. Execute this precise bash block to ensure the terminal opens and the socket is ready: export DISPLAY=${DISPLAY:-:0.0} export XAUTHORITY=${XAUTHORITY:-$HOME/.Xauthority} export DBUS_SESSION_BUS_ADDRESS="unix:path=/run/user/$(id -u)/bus" if ! pgrep -x cmus > /dev/null; then xfce4-terminal -e cmus & for i in {1..20}; do cmus-remote -C "status" >/dev/null 2>&1 && break sleep 0.5 done fi ## Playback Rule Engine The agent must parse the user's prompt to determine the playback mode. **CRITICAL:** The agent MUST resolve `<path_to_file>` using `eval echo` to ensure absolute pathing before passing to `cmus-remote`. ### Mode A: Play track and shuffle the rest (Default) Trigger Intent: "Play this track", "Open song...", "Play and shuffle". Execute this bash block: TARGET_FILE=$(eval echo "<path_to_file>") cmus-remote -C "clear" cmus-remote -C "add $HOME/.openclaw/workspace/music/" cmus-remote -C "set continue=true" cmus-remote -C "set shuffle=true" cmus-remote -f "$TARGET_FILE" ### Mode B: Play ONLY the requested track Trigger Intent: "Play only this track", "Do not shuffle", "Single track mode". Execute this bash block: TARGET_FILE=$(eval echo "<path_to_file>") cmus-remote -C "clear" cmus-remote -C "add $TARGET_FILE" cmus-remote -C "set continue=false" cmus-remote -C "set repeat=false" cmus-remote -p

path: _meta.json
content: ownerId: kn70pywhg0fyz996kpa8xj89s57yhv26
slug: cmus
version: 1.0.0
publishedAt: 1774489002000

Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: aninebot/ninebot-skill (version 0.0.1)

--- name: ninebot-skill description: 九号电动车/平衡车集成技能 - 用于与 Ninebot 设备交互、诊断、配置和故障排除 --- # Ninebot Skill 九号设备集成技能，提供与 Ninebot 电动滑板车、平衡车和电动自行车交互的统一接口。 ## 适用场景 - 连接 Ninebot 设备进行诊断 - 读取设备状态、电池信息、行驶数据 - 配置车辆参数（速度限制、尾灯等） - 排查常见故障 - 导出骑行统计数据 ## 功能概览 | 功能 | 描述 | |------|------| | 设备连接 | 通过蓝牙连接 Ninebot 设备 | | 状态查询 | 获取电池、里程、固件版本等信息 | | 参数配置 | 修改速度限制、灯效等设置 | | 故障诊断 | 分析错误码并提供解决方案 | ## 使用方法 ### 连接设备 ``` 九号连接 [设备名称] ``` ### 查询状态 ``` 九号状态 九号电池 九号里程 ``` ### 常用命令 - `九号诊断` - 运行完整诊断 - `九号固件` - 查看固件版本 - `九号重置` - 恢复出厂设置 ## 示例对话 > 用户: 我的九号车连不上手机了 > 技能: 先尝试重启设备蓝牙，如果仍无法连接，运行 `九号诊断` 检查设备状态 ## 注意事项 1. 确保设备电量 > 20% 2. 某些参数修改需要停车状态 3. 固件升级前备份当前配置


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sunny-lobster-api/ssl-monitor (version 1.2.5)

--- name: ssl-monitor description: "查询域名 SSL 证书过期时间。用法：说「查 xxx.cn 证书」或「SSL 证书 xxx.com」即可。" metadata: { "openclaw": { "emoji": "", "requires": { "bins": ["openssl"] } } } --- # SSL 证书查询 一句话查询域名 SSL 证书状态。 ## 用法 直接说： - 「查 baidu.com 证书」 - 「SSL 证书 example.com」 - 「xxx.cn 还有多久过期」 ## 核心命令 ```bash domain="xxx.cn" expiry=$(echo | openssl s_client -servername $domain -connect $domain:443 2>/dev/null | openssl x509 -noout -enddate 2>/dev/null | cut -d= -f2) expiry_epoch=$(date -d "$expiry" +%s 2>/dev/null) now_epoch=$(date +%s) days_left=$(( ($expiry_epoch - $now_epoch) / 86400 )) echo "域名：$domain" echo " 过期时间：$expiry" echo " 剩余天数：$days_left 天" [ $days_left -lt 7 ] && echo " 状态：紧急" || ([ $days_left -lt 30 ] && echo " 状态：注意" || echo " 状态：正常") ``` ## 响应示例 **查 baidu.com 证书** ``` 域名：baidu.com 过期时间：Dec 15 23:59:59 2026 GMT 剩余天数：259 天 状态：正常 ``` **快过期的域名** ``` 域名：expiring.com 过期时间：Apr 5 23:59:59 2026 GMT 剩余天数：5 天 状态：紧急 ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kamiender/douyin-video-fetch (version 1.0.0)

--- name: douyin-video-fetch description: 下载抖音视频到本地（无水印优先）。用于给后续视频分析/复刻提供原始素材，支持 URL 或 video_id 输入、批量列表输入与统一输出目录。 --- # Douyin Video Fetch ## Overview 把抖音链接下载成可分析的本地 mp4。 这是“视频复刻”链路的素材入口层。 ## 何时使用 - 你需要把目标视频落地到本地做拆解 - 你拿到的是 `video_id`，想直接下载 - 你要批量下载一组抖音视频做样本库 ## 快速用法 单条下载： ```bash python scripts/fetch_video.py "https://www.douyin.com/video/7599980362898427178" ``` 用 video_id 下载： ```bash python scripts/fetch_video.py 7599980362898427178 ``` 批量（每行一个 URL 或 video_id）： ```bash python scripts/fetch_video.py --file input.txt --output-dir ./downloads/douyin ``` ## 输出 - 默认输出目录：`./downloads` - 文件名：`<video_id>.mp4` - 终端会输出每条的成功/失败结果与落盘路径 ## 备注 - 该技能只负责下载，不做ASR/镜头分析。 - 下载失败时建议先用 `douyin-url-resolver` 清洗输入链接。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: ra1nzzz/status-web (version 1.0.0)

--- name: xiaoyu-bot-status description: 小雨 bot 状态监测页面技能包。提供实时监控 OpenClaw Agent 工作状态、定时任务和系统健康状况的 Web 界面。包含静态缓存机制确保快速加载，美化 UI 界面，以及独立部署能力。使用场景：需要监控 AI Agent 运行状态、查看最近工作记录、管理定时任务、检查系统健康状况。 --- # 小雨 Bot 状态监测页面 ## 概述 这是一个完整的 Web 应用，用于实时监控 OpenClaw Agent 的运行状态。它提供三个主要功能模块： - **最近工作**：显示 Agent 最近完成的工作任务 - **定时任务**：显示当前配置的定时任务及其下次执行时间 - **健康状态**：显示系统运行时间、CPU 负载、内存可用性、OpenClaw 连接状态等 ## 核心特性 ### 静态缓存优先 - 页面加载时优先从 `status-cache.json` 静态文件读取数据 - 确保用户访问时立即显示内容，避免"加载中..."等待 - 后台静默从 API 获取最新数据并更新显示 ### 美化 UI 界面 - 渐变背景设计（紫色到蓝色） - 响应式卡片布局，支持桌面和移动设备 - 悬停动画效果，提升用户体验 - 彩色状态指示器（绿色正常、黄色警告、红色错误） ### 独立部署 - 完全独立的 Node.js 服务器，不依赖 OpenClaw 主进程 - 可以在任意端口运行（默认 8888） - 支持 Cloudflare Tunnel 外网访问 ### 隐藏彩蛋功能 - 在标题上连续点击 7 次可激活隐藏聊天窗口 - 支持与小雨进行秘密对话（需验证身份） ## 部署说明 ### 文件结构 ``` xiaoyu-bot-status/ ├── SKILL.md ├── server.js # 主服务器文件 ├── public/ # 静态资源目录 │ ├── index.html # 主页面（包含静态缓存逻辑） │ └── status-cache.json # 静态缓存文件 ├── scripts/ # 数据获取脚本 │ ├── get-work-tasks-fixed.js # 获取最近工作数据 │ ├── get-scheduled-tasks-simple.js # 获取定时任务数据 │ └── auto-update-work-fixed.js # 自动更新工作记录 └── references/ # 参考文档 └── api-spec.md # API 接口规范 ``` ### 启动服务 ```bash # 在技能目录下运行 node server.js # 或使用启动脚本 ./start.sh ``` ### 自动缓存更新 创建 cron 任务每 3 小时更新缓存： ```bash # 缓存更新脚本位置 /home/admin/openclaw/workspace/skills/xiaoyu-bot-status/scripts/update-cache.sh ``` ## API 接口 ### GET /api/status 返回完整的状态数据，包含： - `recent_work`: 最近工作列表 - `scheduled_tasks`: 定时任务列表 - `health_status`: 系统健康状态 - `last_updated`: 最后更新时间 ### POST /api/chat 处理隐藏聊天功能的消息（需要身份验证） ## 使用场景 - **日常监控**：定期查看 Agent 工作状态和系统健康度 - **故障排查**：当 Agent 出现异常时快速定位问题 - **任务管理**：查看和验证定时任务的执行情况 - **性能优化**：监控 CPU 和内存使用情况 - **演示展示**：向他人展示 AI Agent 的工作成果 ## 维护建议 - 定期检查缓存更新脚本是否正常运行 - 监控服务器日志 (`server.log`) 发现潜在问题 - 根据实际需求调整数据刷新频率（默认 2 秒后台刷新） - 如需修改 UI 样式，直接编辑 `public/index.html` 中的 CSS 部分


Security scan verdicts — ClawScan: malicious | static analysis: suspicious | VirusTotal: suspicious | SkillSpector:  ()
Skill: fresh3/taizi-browsh (version 1.0.0)

--- name: taizi-browsh description: A modern text-based browser. Renders web pages in the terminal using headless Firefox. metadata: {"clawdbot":{"emoji":"🌐","requires":{"bins":["browsh","firefox"]}}} --- # Browsh A fully-modern text-based browser. It renders stories and videos, filters ads, and saves bandwidth. ## Prerequisites - `browsh` binary must be in PATH. - `firefox` binary must be in PATH (Browsh uses it as a headless backend). **Local Setup (if installed in `~/apps`):** Ensure your PATH includes the installation directories: ```bash export PATH=$HOME/apps:$HOME/apps/firefox:$PATH ``` ## Usage Start Browsh: ```bash browsh ``` Open a specific URL: ```bash browsh --startup-url https://google.com ``` **Note:** Browsh is a TUI application. Run it inside a PTY session (e.g., using `tmux` or the `process` tool with `pty=true`).


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: gingiris/china-to-global (version 1.0.0)

--- name: china-to-global description: | China-to-Global Go-to-Market Playbook — Complete guide for Chinese products/apps expanding to global markets. From App Store optimization to global launch strategies. Real case studies: TikTok, SHEIN, Alibaba, MiHoYo. Covers: localization strategy, App Store optimization, Product Hunt launch, Reddit/HackerNews marketing, KOL partnerships, payment infrastructure, legal compliance. 出海运营完整指南 — 中国产品全球化实战手册。从 App Store 优化到全球发布策略。真实案例：TikTok、SHEIN、米哈游、AFFiNE。涵盖：本地化策略、ASO优化、PH发布、Reddit/HN营销、KOL合作、支付基础设施、法律合规。 Website: https://www.gingiris.com Keywords: 出海, China to global, global expansion, overseas marketing, cross-border, international launch, localization, ASO, App Store optimization, 产品出海, 出海运营, 全球化 --- # 出海运营完整指南 > 🌍 **Language / 语言**: [中文](#中文版) | [English](https://github.com/Gingiris/china-to-global/blob/main/README.md) ## 中文版 ### 核心框架：出海增长飞轮 ``` ┌─────────────┐ │ 产品本地化 │ └──────┬──────┘ │ ┌──────▼──────┐ │ 渠道选择 │ └──────┬──────┘ │ ┌──────▼──────┐ │ 发布冷启动 │ └──────┬──────┘ │ ┌──────▼──────┐ │ 增长放大 │ └─────────────┘ ``` ### 出海关键成功因素 1. **本地化 > 翻译** — 不是简单翻译，是文化适配 2. **Day 1 收费** — 不要再走"免费获取用户"的老路 3. **KOL 渠道合作** — 建立本地信任背书 4. **数据驱动迭代** — A/B 测试定价、截图、关键词 ### 工具资源 - [PH Launch Generator](https://gingiris.github.io/ph-comment-generator/) - [ASO Guide](https://github.com/Gingiris/gingiris-aso-growth) - [GitHub Stars Guide](https://github.com/Gingiris/gingiris-opensource) --- *出海咨询: https://gingiris.com*


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