OpenClaw/clawhub-security-signals huggingface dataset:
Skill: pushp1997/ovh (version 1.0.0)

--- name: ovh version: 1.0.0 description: Manage OVHcloud services via API. Use when user asks about OVH domains, DNS records, VPS, cloud instances, dedicated servers, email, SSL certificates, or any OVH service management. Supports listing, creating, updating, and deleting resources. --- # OVH Manage OVHcloud services via the bundled `ovh-cli.py` script. ## Setup Store credentials in environment: ```bash export OVH_ENDPOINT="ovh-ca" # or ovh-eu, ovh-us, etc. export OVH_APP_KEY="your-app-key" export OVH_APP_SECRET="your-app-secret" export OVH_CONSUMER_KEY="your-consumer-key" ``` **Get credentials:** 1. Go to https://ca.api.ovh.com/createToken/ (or eu/us variant) 2. Create application with desired permissions 3. Validate the consumer key via the provided URL **Endpoints:** `ovh-eu`, `ovh-ca`, `ovh-us`, `soyoustart-eu`, `soyoustart-ca`, `kimsufi-eu`, `kimsufi-ca` ## Usage The script is at `scripts/ovh-cli.py`. Commands: ```bash # Account info ovh-cli.py me # Domains ovh-cli.py domains # List all domains ovh-cli.py domain <domain> # Get domain info ovh-cli.py domain <domain> renew # Check renewal info # DNS (OVH-managed zones, not Cloudflare) ovh-cli.py dns <domain> # List DNS records ovh-cli.py dns <domain> get <id> # Get specific record ovh-cli.py dns <domain> create --type A --subdomain www --target 1.2.3.4 [--ttl 300] ovh-cli.py dns <domain> update <id> --target 5.6.7.8 ovh-cli.py dns <domain> delete <id> ovh-cli.py dns <domain> refresh # Refresh zone (apply changes) # VPS ovh-cli.py vps # List all VPS ovh-cli.py vps <name> # VPS details ovh-cli.py vps <name> status # Current state ovh-cli.py vps <name> reboot # Reboot VPS ovh-cli.py vps <name> start # Start VPS ovh-cli.py vps <name> stop # Stop VPS ovh-cli.py vps <name> ips # List IPs # Cloud Projects ovh-cli.py cloud # List projects ovh-cli.py cloud <project> instances # List instances ovh-cli.py cloud <project> instance <id> # Instance details # Dedicated Servers ovh-cli.py dedicated # List servers ovh-cli.py dedicated <name> # Server details ovh-cli.py dedicated <name> reboot # Reboot server # SSL Certificates ovh-cli.py ssl # List certificates ovh-cli.py ssl <id> # Certificate details # Bills & Orders ovh-cli.py bills [--limit N] # Recent bills ovh-cli.py orders [--limit N] # Recent orders ``` ## Common Patterns **Check domain expiry:** ```bash ovh-cli.py domain pushp.ovh renew ``` **Add DNS record:** ```bash ovh-cli.py dns pushp.ovh create --type A --subdomain api --target 203.0.113.50 ovh-cli.py dns pushp.ovh refresh ``` **Manage VPS:** ```bash ovh-cli.py vps myvps status ovh-cli.py vps myvps reboot ``` ## Notes - DNS changes require `refresh` to apply - Use `--json` flag for machine-readable output - Some operations are async; check status with subsequent calls


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jessewunderlich/meeting-transcripts (version 1.0.0)

--- name: meeting-transcripts description: Capture meeting transcripts from Fireflies.ai via polling or webhooks. Auto-fetches transcripts, extracts action items/decisions/summaries, and writes structured markdown to memory. Use when user asks to check for meeting transcripts, set up meeting capture, or review past meetings. Supports cron-based polling (every 30 min) and real-time webhooks. --- # Meeting Transcripts (Fireflies.ai) Auto-capture meeting transcripts from Fireflies.ai, extract action items and decisions, write structured markdown to memory. ## Setup ### 1. Store API key ```bash echo "YOUR_FIREFLIES_API_KEY" > ~/.openclaw/secrets/fireflies-api-key.txt ``` Get your key from Fireflies dashboard → Settings → Developer Settings. ### 2. Poll for new transcripts (recommended) ```bash node scripts/poll-new-meetings.js ``` Schedule via OpenClaw cron every 30 minutes. Tracks processed meetings to avoid duplicates. ### 3. Real-time webhooks (optional) ```bash node scripts/webhook-server.js ``` Runs on port 3142. Expose via Cloudflare Tunnel or ngrok, then paste the URL into Fireflies Settings → Developer Settings → Webhook URL. Optional webhook secret: ```bash echo "YOUR_SECRET" > ~/.openclaw/secrets/fireflies-webhook-secret.txt ``` ### 4. Fetch a specific transcript ```bash node scripts/fetch-transcript.js <meetingId> ``` ## Output Transcripts are saved to `memory/meetings/YYYY-MM-DD-<title>.md` with: - Title, date, duration, participants - AI summary from Fireflies - Action items (as checkboxes) - Key topics and keywords - Full transcript with speaker labels and timestamps ## Cron Setup Schedule polling every 30 minutes: ``` Check Fireflies for new meeting transcripts. Run: node <skill-path>/scripts/poll-new-meetings.js — if new meetings found, briefly notify the user with the meeting title(s). If no new meetings, do nothing (NO_REPLY). ``` ## Requirements - Fireflies.ai Pro account ($10/mo) — includes API access - Node.js 18+


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: guowei-xie/taoguba-picks-digest (version 1.0.4)

# 淘股吧今日推荐抓取整理技能 ## 描述 自动浏览淘股吧网站，进入"今日推荐"专栏，抓取排名前N的帖子，阅读完整内容后整理总结输出。 使用 agent-browser 进行页面交互获取帖子链接，成功后后台静默抓取内容。 ## 功能 - 使用 agent-browser 导航到淘股吧首页 - 如果需要登录，使用环境变量中的账号密码进行登录 - 定位并点击"今日推荐"栏目获取前15个帖子的url - 获取url成功后使用后台静默抓取所有url内容 - 如果url获取不成功，则继续在浏览器中依次打开浏览帖子获取内容 - 整理总结：整体行情、板块表现、多数作者观点 ## 使用场景 用户要求"浏览淘股吧今日推荐，整理前15个帖子观点"时使用。 ## 配置要求 ### 环境变量（如果需要登录） 请在运行前配置以下环境变量： ```bash export TAOGUBA_USERNAME="你的账号" export TAOGUBA_PASSWORD="你的密码" ``` 第一次使用时，如果遇到登录界面，会提示你配置环境变量。 ## 操作步骤 ### 1. 使用 agent-browser 打开淘股吧首页 ```bash agent-browser open https://www.tgb.cn/ agent-browser wait --load networkidle agent-browser snapshot -i ``` ### 2. 检查是否需要登录 - 如果快照中出现"账号登录"按钮/表单，则需要登录： - 找到用户名/账号输入框，使用环境变量 `$TAOGUBA_USERNAME` 填充 - 找到密码输入框，使用环境变量 `$TAOGUBA_PASSWORD` 填充 - 点击登录按钮，等待页面加载完成 - 如果不需要登录，直接下一步 ### 3. 点击"今日推荐"栏目 在导航栏中找到"今日推荐"栏目/标签，点击切换： ```bash agent-browser find text "今日推荐" click agent-browser wait --load networkidle agent-browser snapshot -i ``` ### 4. 获取前15个帖子的URL 遍历当前页面中"今日推荐"栏目下的帖子链接： ```bash # 提取前15个帖子的href属性 # 保存到 urls.txt 文件 ``` 每个帖子URL格式为 `https://www.tgb.cn/a/xxxx`。 ### 5. 根据获取结果选择后续操作 #### 情况A：成功获取15个URL → 后台静默抓取 不需要继续浏览器操作，改用后台批量抓取： - 逐行读取 urls.txt 中的URL - 对每个URL调用 `web_fetch` 获取内容，保存为 markdown 文件 - 所有URL抓取完成后，进入步骤6整理总结 **注意**：敏感的账号密码信息不会写入任何文件，仅在环境变量中使用。 #### 情况B：获取URL不成功 → 浏览器逐个打开抓取 如果通过agent-browser提取URL失败，则继续在浏览器中操作： - 依次点击每个帖子标题打开帖子 - 对每个打开的帖子，获取页面正文内容 - 保存内容后关闭标签页，继续下一个 - 收集完所有内容后进入步骤6 ### 6. 整理总结输出 整理所有帖子内容，输出包含以下部分： 1. **整体总结** - 市场概况、成交量、整体情绪 2. **市场判断** - 趋势、板块表现（强弱分类） 3. **多数作者观点** - 操作策略共识、投资理念交流 4. **焦点个股** - 被多次提到的股票 ## 注意事项 - 账号密码仅用于登录，不会记录到任何技能文件或日志中 - 每个帖子只需要总结主要观点，不用整理评论区 - 保持客观，只整理作者表达的观点，不添加额外判断 - 输出格式清晰，使用markdown分级 ## 示例输出结构 ``` # 淘股吧"今日推荐"（YYYY年MM月DD日）前15篇帖子 整体总结 ## 一、整体行情概况 ... ## 二、板块表现 | 板块 | 表现 | 代表个股 | |------|------|----------| | ... | ... | ... | ## 三、多数作者的共同观点 ... ## 四、焦点个股 ... ## 五、小结 ... ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shaw555/ocr-skill-test (version 1.0.0)

--- name: ocr description: Extract text from images using Tesseract.js OCR. Supports Chinese (simplified/traditional) and English. homepage: https://github.com/naptha/tesseract.js metadata: {"clawdbot":{"emoji":"📝","requires":{"bins":["node"]},"install":[{"id":"npm","kind":"npm","packages":["tesseract.js"],"label":"Install tesseract.js"}]}} --- # OCR - Image Text Recognition Extract text from images using Tesseract.js. Supports Chinese and English. ## Quick start ```bash node {baseDir}/scripts/ocr.js /path/to/image.jpg node {baseDir}/scripts/ocr.js /path/to/image.png --lang chi_sim node {baseDir}/scripts/ocr.js /path/to/image.jpg --lang chi_tra+eng ``` ## Options - `--lang <langs>`: Language codes (default: chi_sim+eng) - `chi_sim` - Simplified Chinese - `chi_tra` - Traditional Chinese - `eng` - English - Combine with `+`: `chi_sim+eng` - `--json`: Output as JSON instead of plain text ## Examples ```bash # Recognize Chinese screenshot node {baseDir}/scripts/ocr.js screenshot.png # Recognize English document node {baseDir}/scripts/ocr.js document.jpg --lang eng # Mixed Chinese + English node {baseDir}/scripts/ocr.js mixed.png --lang chi_sim+eng ``` ## Notes - First run downloads language data (~20MB per language) - Subsequent runs are cached locally - Works best with clear, high-contrast images - For handwritten text, accuracy may vary


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: solarspiker/appian-export (version 1.3.0)

--- name: appian-export description: Export an Appian application or package to a ZIP file by UUID. Use when the user wants to export, download, or back up an Appian application or package from an environment. metadata: clawdbot: emoji: "📦" requires: env: - APPIAN_BASE_URL - APPIAN_API_KEY primaryEnv: APPIAN_BASE_URL --- # Appian Manager Exports an Appian application or package as a ZIP using the [v2 Deployment Management API](https://docs.appian.com/suite/help/25.4/Export_Package_API.html). ## Usage ```bash # Export an application node {baseDir}/scripts/index.js <applicationUuid> [exportName] # Export a specific package under an application node {baseDir}/scripts/index.js <applicationUuid> --package <packageUuid> [exportName] ``` | Argument | Description | |---|---| | `applicationUuid` | UUID of the Appian application | | `packageUuid` | UUID of the specific package (use `appian-listpkg` to list them) | | `exportName` | Optional filename override; if omitted Appian's own name (with timestamp) is used | ## Examples ```bash # Export full application node {baseDir}/scripts/index.js _a-0000de15-1f1c-8000-5130-010000010000_12559 # Export a specific package under that application node {baseDir}/scripts/index.js _a-0000de15-1f1c-8000-5130-010000010000_12559 --package _a-0007ee60-0f3e-8000-e0f6-01ef9001ef90_137916 ``` The script polls until `COMPLETED` and saves the ZIP to `~/appian-exports/`. When running inside a container (where the working directory differs from `~/appian-exports/`), the ZIP is also copied to `appian-exports/` inside the current working directory for easy access. ## After running Always report back to the user: - The **ZIP path** printed after `ZIP path:` (primary location) - The **Copied to** path if printed (accessible in `appian-exports/` inside the current working directory) - The file **size** in KB ## External endpoints - `POST ${APPIAN_BASE_URL}/deployments` — triggers the export - `GET ${APPIAN_BASE_URL}/deployments/{uuid}` — polls for completion - `GET <packageZip URL>` — downloads the resulting ZIP ## Security - Credentials (`APPIAN_BASE_URL`, `APPIAN_API_KEY`) are read from environment variables (injected by OpenClaw at runtime). If not injected, the script falls back to a `appian.json` file in the current working directory. - No data is sent to any third-party service — all requests go to your configured Appian environment. - The exported ZIP is written locally to `~/appian-exports/` and never uploaded anywhere. - No shell commands are executed; all operations use Node.js built-in APIs.


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: directorvector/groq-whisper (version 1.0.1)

--- name: groq-whisper description: Transcribe audio files using Groq's Whisper API (whisper-large-v3). Fast cloud-based speech-to-text with no local model required. Use when receiving voice messages, audio files, or any speech that needs transcription. Supports all major audio formats (ogg, mp3, wav, m4a, webm, flac). author: DirectorVector homepage: https://github.com/DirectorVector metadata: { "openclaw": { "requires": { "bins": ["curl", "jq"] }, "env": [ { "name": "GROQ_API_KEY", "description": "Groq API key. Alternatively store in ~/.config/groq/credentials.json as {\"api_key\":\"gsk_...\"}.", "required": false } ] } } --- # Groq Whisper Cloud speech-to-text via Groq's Whisper API. No local model, no GPU, no fan spin. ## Setup 1. Get a free API key at `console.groq.com` 2. Store it: ```bash mkdir -p ~/.config/groq echo '{"api_key":"gsk_your_key_here"}' > ~/.config/groq/credentials.json chmod 600 ~/.config/groq/credentials.json ``` Or set `GROQ_API_KEY` env var. ## Usage ```bash # Transcribe an audio file {baseDir}/scripts/transcribe.sh /path/to/audio.ogg # Specify language (default: en) {baseDir}/scripts/transcribe.sh /path/to/audio.ogg es ``` ## When to use Call this script whenever you receive an audio/voice message attachment. Pass the file path directly — Groq handles ogg, mp3, wav, m4a, webm, and flac natively. No format conversion needed. ## Details - **Model:** whisper-large-v3 (best accuracy) - **Speed:** Faster than real-time (typically <2s for a 5-minute clip) - **Cost:** Free tier available, no credit card required - **Privacy:** Groq does not retain input data or train on it - **Requires:** `curl`, `jq`, Groq API key


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: dadaniya99/feishu-edge-tts-voice (version 1.0.0)

--- name: feishu-voice description: 飞书语音消息发送技能。使用 Edge TTS（微软，免费无限次）生成语音并以飞书语音气泡形式发送。当用户要求用语音回复、发语音消息、TTS 朗读内容时触发。默认音色：云希（zh-CN-YunxiNeural，活泼阳光男声）。 --- # 飞书语音消息发送 ## 快速使用 ```bash python3 ~/.openclaw/workspace/skills/feishu-voice/scripts/send_voice.py \ "要说的内容" \ <open_id> ``` ## 工作流程 1. edge-tts 生成 mp3 2. ffmpeg 转换为 opus（飞书语音格式） 3. 飞书 API 上传文件获取 file_key（file_type=opus） 4. 发送 msg_type=audio 消息 **关键**：必须用 `msg_type: audio` + `file_key`，不能用普通文件上传，否则显示为文件而非语音气泡。 ## 音色选择 ```bash # 查看所有中文音色 edge-tts --list-voices | grep zh-CN # 常用中文男声 zh-CN-YunxiNeural # 云希 - 活泼阳光（默认，小龙虾专用） zh-CN-YunjianNeural # 云间 - 激情澎湃 zh-CN-YunxiaNeural # 云夏 - 可爱萌 zh-CN-YunyangNeural # 云扬 - 专业严肃 # 常用中文女声 zh-CN-XiaoxiaoNeural # 小小 - 温柔 zh-CN-XiaoyiNeural # 小艺 - 活泼 # 指定音色发送 python3 ~/.openclaw/workspace/skills/feishu-voice/scripts/send_voice.py \ "内容" <open_id> --voice zh-CN-YunyangNeural ``` ## 依赖安装 ```bash pip install edge-tts # 一次性安装，永久免费 # ffmpeg 通常已预装，如没有：yum install ffmpeg / apt install ffmpeg ``` ## 飞书配置 需要 openclaw.json 中的 feishu appId / appSecret，脚本自动读取。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: rsquaredsolutions2026/news-sentiment-scanner (version 1.1.0)

--- name: news-sentiment-scanner description: "Scan news sources and RSS feeds for events that could move prediction market prices. Score headlines for market impact, flag urgent stories, and cross-reference with active markets. Use when asked about breaking news, market-moving events, or news sentiment." metadata: openclaw: emoji: "📰" requires: bins: ["curl", "jq", "python3"] --- # News Sentiment Scanner Scan news and RSS feeds for market-moving events, score headline sentiment, and flag prediction market trading opportunities. ## When to Use Use this skill when the user asks about: - Breaking news that could affect prediction markets - Scanning news for trading opportunities - Sentiment analysis of current headlines - Market-moving events in sports, politics, or economics - News-driven trading signals - Whether any recent news affects open positions ## RSS Feed Sources Default feeds covering key prediction market verticals: | Vertical | Feed URL | |----------|----------| | General Breaking | https://feeds.apnews.com/rss/apf-topnews | | World News | https://feeds.reuters.com/reuters/topNews | | US Politics | https://feeds.apnews.com/rss/apf-politics | | Sports | https://www.espn.com/espn/rss/news | | Economics | https://feeds.reuters.com/reuters/businessNews | | Crypto | https://cointelegraph.com/rss | The agent may add or substitute feeds based on context (e.g., if the user trades sports markets, prioritize ESPN). ## Operations ### 1. Scan RSS Feeds for Headlines Fetch the latest headlines from all configured feeds: ```bash for FEED_URL in \ "https://feeds.apnews.com/rss/apf-topnews" \ "https://feeds.reuters.com/reuters/topNews" \ "https://feeds.apnews.com/rss/apf-politics" \ "https://www.espn.com/espn/rss/news" \ "https://feeds.reuters.com/reuters/businessNews" \ "https://cointelegraph.com/rss"; do curl -s "$FEED_URL" | python3 -c " import sys, xml.etree.ElementTree as ET from datetime import datetime, timezone try: tree = ET.parse(sys.stdin) root = tree.getroot() source = root.find('.//channel/title') src = source.text if source is not None else 'Unknown' for item in root.findall('.//item')[:10]: title = item.find('title') link = item.find('link') pub = item.find('pubDate') t = title.text if title is not None else '' l = link.text if link is not None else '' p = pub.text if pub is not None else '' print(f'{src}|{t}|{l}|{p}') except: pass " done ## About Built by [AgentBets](https://agentbets.ai) — full tutorial at [agentbets.ai/guides/openclaw-news-sentiment-scanner-skill/](https://agentbets.ai/guides/openclaw-news-sentiment-scanner-skill/). Part of the [OpenClaw Skills series](https://agentbets.ai/guides/#openclaw-skills) for the [Agent Betting Stack](https://agentbets.ai/guides/agent-betting-stack/).


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

--- name: srs description: SRS - Security Research System 安全研究系统 metadata: openclaw: emoji: 🎯 version: 1.0.0 abbreviation: SRS # 🎯 SRS - Security Research System > 安全研究系统 - 智能任务评估与角色匹配 ## 系统信息 - **全称**: Security Research System (安全研究系统) - **缩写**: SRS - **版本**: 1.0.0 ## 核心能力 ### 1. 任务评估 (Evaluation) 系统会根据多个维度评估任务是否进入系统： | 评估维度 | 权重 | 说明 | |----------|------|------| | 优先级 | 25% | 外部触发 > 计划任务 > 主动发现 > 内部优化 | | 知识相关性 | 20% | 核心领域 > 边缘领域 > 其他 | | 时效性 | 15% | 紧急 > 高 > 中 > 低 | | 资源可用性 | 15% | CPU/内存阈值 | | 价值 | 25% | 对外发布/知识贡献/风险缓解 | **阈值**: 总分 >= 60 分才能进入系统 ### 2. 角色匹配 根据任务内容自动匹配最合适的角色： | 关键词 | 匹配角色 | |--------|----------| | cve, vulnerability, threat, exploit | 🔴 安全研究员 | | research, analysis, study, paper | 📚 领域研究员 | | document, report, knowledge, 整理 | 📖 知识运营 | | discover, scan, trend, 新兴 | 🚀 探索者 | | incident, alert, monitor, response | 🛡️ 安全运营 | ### 3. 优先级规则 ``` 外部触发 (最高): ├── CVE严重漏洞: 100分 ├── 安全事件: 95分 ├── 合规违规: 90分 └── 公开披露: 85分 计划任务: ├── 日报: 70分 ├── 周报: 65分 └── 月度review: 60分 主动发现: ├── 威胁情报: 50分 ├── 研究机会: 45分 └── 趋势分析: 40分 内部优化 (最低): ├── 基础设施: 20分 ├── 工具改进: 15分 └── 文档完善: 10分 ``` ## 使用方法 ```bash # 启动系统 srs start # 执行任务 (自动评估+匹配) srs run "研究OpenClaw安全治理" # 查看状态 srs status # 查看评估标准 srs criteria ``` ## 评估示例 ```bash $ srs run "研究OpenClaw安全治理" { "status": "admitted", "task": { "name": "研究OpenClaw安全治理", "role": "security_researcher", "role_emoji": "🔴" }, "evaluation": { "priority": 85, "resources": 80.0, "relevance": 40.0, "timeliness": 80, "value": 30, "total": 60.75, "admit": true, "matched_role": "security_researcher" } } ``` ## 文件结构 ``` srs/ ├── srs.py # 核心系统 ├── srs # CLI脚本 └── SKILL.md # 本文档 ``` ## 评估流程 ``` 用户输入 ↓ ┌─────────────────┐ │ 任务评估 │ │ - 优先级 │ │ - 资源 │ │ - 相关性 │ │ - 时效性 │ │ - 价值 │ └─────────────────┘ ↓ ┌─────────────────┐ │ 判定 │ │ >= 60分: 通过 │ │ < 60分: 拒绝 │ └─────────────────┘ ↓ ┌─────────────────┐ │ 角色匹配 │ │ 关键词匹配 │ └─────────────────┘ ↓ 执行任务 ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: zaferliu/fortune-luck (version 1.2.0)

# 运势计算 Skill ## 触发关键词 - 帮我算运势 - 算今日运势 - 今天运势怎么样 - 今日运势 - 查运势 - 运气怎么样 - 今日运气 ## 功能 根据生日计算每日运势（爱情、事业、财运、健康），生成幸运元素和建议。 ## 首次使用 首次调用时，如果未保存生日，会提示用户输入： - 生日日期（格式：YYYY-MM-DD） - 历法类型（阳历/阴历） 用户回复后会自动保存，后续无需重复输入。 ## 输入参数 - `birth_date`: 生日，格式 YYYY-MM-DD（可选，有保存时自动读取） - `query_date`: 查询日期，格式 YYYY-MM-DD（可选，默认今天） - `calendar_type`: 历法类型，"solar"(阳历) 或 "lunar"(阴历) ## 输出格式 ```json { "query_date": "2026-03-24", "birth_date": "1990-01-15", "constellation": "摩羯座", "zodiac": "马", "lunar_date": "农历正月十五", "ganzhi_day": "甲辰日", "day_tian_shen": "玉堂（黄道）", "auspicious_label": "黄道吉日", "scores": { "overall": 78, "love": 72, "career": 80, "wealth": 75, "health": 82 }, "lucky_color": "红色", "lucky_number": 7, "lucky_direction": "正南", "yi": ["嫁娶", "祈福", "开市"], "ji": ["动土", "安葬"], "advice": "今日气场强，适合推进关键事项..." } ``` ## 数据存储 生日数据保存在用户目录下的 `.openclaw/fortune_birthday.json` 文件中，跨平台兼容。 - Windows: `C:\Users\<用户名>\.openclaw\fortune_birthday.json` - macOS/Linux: `~/.openclaw/fortune_birthday.json` ## 调用示例 ```python from fortune_luck import FortuneCalculator calc = FortuneCalculator() # 检查是否需要询问生日 if calc.get_saved_birthday() is None: # 需要先问用户生日 print(calc.get_ask_birthday_prompt()) else: # 直接计算 result = calc.calculate() # 使用保存的生日 print(result.to_text("share")) # 保存生日后计算 calc.calculate("1990-01-15", calendar_type="solar") ``` ## 输出模板（分享用） ``` 📅 2026年3月24日 运势 🎂 1990年1月15日 | 摩羯座 | 生肖马 💫 今日判断：黄道吉日 📊 运势评分 - 总运: 78/99 - 爱情: 72 | 事业: 80 | 财运: 75 | 健康: 82 🍀 幸运元素 - 幸运色: 红色 - 幸运数字: 7 - 幸运方位: 正南 📋 宜: 嫁娶、祈福、开市 ⚠️ 忌: 动土、安葬 💡 建议: 今日气场强，适合推进关键事项... ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: enderfga/three-minds (version 0.1.0)

--- name: three-minds description: 三个能干活的 AI 分身协作系统。用 Claude Code 启动三个不同人设的 coding agent，共享同一个工作目录，多轮协作直到达成共识。适用于代码审查、方案评审、重构任务等需要多视角协作的场景。 version: 2.0.0 author: Enderfga --- # Three Minds - 三个臭皮匠顶个诸葛亮 真正能干活的多 Agent 协作系统。不是纸上谈兵，而是真的能读文件、改代码、跑测试。 ## 核心特性 - 🔧 **真正执行** - 每个 agent 都能读取文件、编写代码、运行测试 - 👥 **多视角协作** - 三个不同人设的 agent 互相审核 - ✅ **共识机制** - 全员 YES 才结束，确保质量 - 📁 **共享目录** - 在同一个项目上协作 - 📝 **完整记录** - 自动保存讨论和改动历史 ## 使用方法 ```bash # 基础用法 three-minds "审查并改进这个项目的代码质量" --dir ./my-project # 使用代码审查配置（安全+性能+质量三人组） three-minds "审查 src/ 目录的所有代码" --config code-review --dir ./project # 指定最大轮数 three-minds "重构这个模块" --dir ./module --max-rounds 5 # 保存结果到 JSON three-minds "任务描述" --dir ./project --output result.json ``` ## 触发词 - "三个臭皮匠" - "three minds" - "多 agent 协作" - "让三个 agent 一起审查" - "协作完成这个任务" ## 预设配置 ### 默认配置 - 代码协作三人组 - 🏗️ **架构师** - 关注代码结构、设计模式、可扩展性 - ⚙️ **工程师** - 关注代码质量、错误处理、性能优化 - 🔍 **审核员** - 关注代码规范、潜在 bug、文档完整性 ### code-review - 代码审查三人组 - 🛡️ **安全专家** - 关注安全漏洞、注入风险、权限问题 - ⚡ **性能工程师** - 关注算法复杂度、内存使用、查询优化 - ✅ **质量审查员** - 关注可读性、命名规范、测试覆盖 ## 自定义配置 创建 JSON 配置文件： ```json { "name": "我的三人组", "agents": [ { "name": "专家A", "emoji": "🎯", "persona": "你是一位...关注..." }, { "name": "专家B", "emoji": "🔬", "persona": "你是一位...擅长..." }, { "name": "专家C", "emoji": "📊", "persona": "你是一位...负责..." } ], "maxRounds": 10, "projectDir": "." } ``` 然后：`three-minds "任务" --config ./my-config.json` ## 工作流程 ``` ┌──────────────────────────────────────────┐ │ 第 N 轮 │ ├──────────────────────────────────────────┤ │ 🏗️ 架构师 │ │ → 读取文件，审查结构 │ │ → 执行必要的重构 │ │ → 投票 [CONSENSUS: YES/NO] │ ├──────────────────────────────────────────┤ │ ⚙️ 工程师 │ │ → 审查架构师的改动 │ │ → 补充实现细节，修复问题 │ │ → 投票 [CONSENSUS: YES/NO] │ ├──────────────────────────────────────────┤ │ 🔍 审核员 │ │ → 审查所有改动 │ │ → 检查规范、bug、文档 │ │ → 投票 [CONSENSUS: YES/NO] │ └──────────────────────────────────────────┘ ↓ 全员 YES？→ 结束 ↓ NO 继续下一轮... ``` ## 输出 1. **终端实时输出** - 每个 agent 的工作进展和投票 2. **Markdown 记录** - 自动保存在工作目录 `three-minds-{timestamp}.md` 3. **JSON 结果** - 使用 `--output` 保存完整 session 数据 ## 使用场景 - **代码审查** - 多角度审查 PR 或代码变更 - **重构任务** - 协作完成复杂的代码重构 - **新功能开发** - 从设计到实现的完整协作 - **Bug 修复** - 定位问题并验证修复 - **文档完善** - 补充和改进项目文档 ## 注意事项 - 需要安装 Claude Code CLI (`claude` 命令) - 每个 agent 会真的修改文件，建议在 git 分支上使用 - 默认最大 15 轮，可通过 `--max-rounds` 调整 - 如果长时间无法达成共识，检查任务描述是否清晰 ## 依赖 - Node.js 18+ - Claude Code CLI（`claude` 命令可用）


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