OpenClaw/clawhub-security-signals huggingface dataset:
Skill: olina1ye/competitive-analysis-zh (version 1.0.0)

--- name: competitive-analysis-zh description: > 竞品分析 / 竞争对手分析 / 市场竞争分析 / competitive analysis / 竞品调研。为产品经理、市场经理、战略规划师快速生成竞品对比矩阵、SWOT分析、功能差异表、定价策略对标等结构化分析报告。覆盖产品功能、商业模式、营销策略、用户定位等多维度竞争情报。广泛应用于竞品调研报告撰写、融资路演竞争分析、产品立项评审、市场进入策略制定、投资决策支持等职场高频场景。 tags: [竞品分析, competitive-analysis, 市场调研, 竞争对手分析, 产品对比, SWOT分析, 融资路演, 战略规划, market-research, strategy] --- # 竞品分析助手 系统化分析竞争对手，覆盖产品功能、定价、市场定位、用户口碑与营销策略，输出结构化竞品报告，支撑产品决策与战略规划。 ## Tools Required - create_docx - create_xlsx - create_chart ## Usage - "帮我分析一下我们产品和竞品的功能差异，整理成对比表格" - "做一份国内主流XX赛道竞品的市场定位分析报告" - "我们要做产品立项，帮我梳理三家主要竞品的定价策略和核心卖点" ## Examples 输入：我们是一款企业SaaS协作工具，主要竞品有飞书、钉钉、企业微信，请帮我做竞品分析，重点关注功能完整度、定价和目标客群。 输出： **竞品分析报告：企业协作SaaS赛道** **一、竞品概览** | 维度 | 飞书 | 钉钉 | 企业微信 | |------|------|------|----------| | 母公司 | 字节跳动 | 阿里巴巴 | 腾讯 | | 目标客群 | 中大型企业、科技公司 | 中小企业、制造业 | 微信生态企业 | | 核心定位 | 效率工具+管理平台 | 移动办公+审批流 | 客户连接+内部协作 | | 免费版 | 有（功能限制） | 有 | 有 | | 付费起点 | ≈30元/人/月 | ≈15元/人/月 | ≈18元/人/月 | **二、核心功能对比** | 功能模块 | 飞书 | 钉钉 | 企业微信 | |----------|------|------|----------| | 即时通讯 | ★★★★★ | ★★★★☆ | ★★★★★ | | 文档协作 | ★★★★★ | ★★★☆☆ | ★★★☆☆ | | 审批流程 | ★★★★☆ | ★★★★★ | ★★★★☆ | | 视频会议 | ★★★★☆ | ★★★★☆ | ★★★☆☆ | | 开放生态 | ★★★★☆ | ★★★★★ | ★★★★★ | **三、SWOT 分析摘要（以飞书为例）** - **优势**：产品体验一致性强，文档协作能力突出 - **劣势**：中小企业渗透率低，价格偏高 - **机会**：出海市场扩张，AI功能差异化 - **威胁**：钉钉低价策略，微信生态黏性 **四、战略建议** 1. 差异化切入点：聚焦竞品薄弱的垂直行业（如教育/医疗） 2. 定价策略：可参考钉钉梯度定价，降低中小企业门槛 3. 功能优先级：优先补齐审批流与移动端体验


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: mrnsmh/openclaw-skill-elevenlabs-pro (version 0.1.0)

--- name: elevenlabs-pro description: ElevenLabs advanced TTS for converting text to speech, listing voices, and managing credits license: MIT metadata: version: 1.0.0 author: Jack2 tags: tts, audio, elevenlabs, voice --- # ElevenLabs Pro Skill Advanced text-to-speech using the ElevenLabs API. Supports voice selection, language/gender filtering, audio file generation, and credit tracking. ## Prerequisites Set your API key as an environment variable: ```bash export [REDACTED_SECRET] ``` Or pass it directly with `--api-key`. ## Usage ### Convert text to speech ```bash python3 scripts/elevenlabs.py "Hello world" --voice Sarah --output audio.mp3 ``` ### List available voices ```bash python3 scripts/elevenlabs.py --list-voices python3 scripts/elevenlabs.py --list-voices --lang en --gender female python3 scripts/elevenlabs.py --list-voices --json ``` ### Check remaining credits ```bash python3 scripts/elevenlabs.py --credits ``` ## Options | Option | Default | Description | |--------|---------|-------------| | `--voice NAME` | Rachel | Voice name (partial match supported) | | `--voice-id ID` | — | Direct voice ID (overrides --voice) | | `--output PATH` | output.mp3 | Output MP3 file path | | `--model ID` | eleven_turbo_v2_5 | Model ID | | `--stability` | 0.5 | Voice stability (0–1) | | `--similarity` | 0.75 | Similarity boost (0–1) | | `--style` | 0.0 | Style exaggeration (0–1) | | `--lang CODE` | — | Filter voices by language (e.g. en, fr) | | `--gender` | — | Filter voices by gender (male/female) | | `--json` | — | Output as JSON | | `--api-key KEY` | — | API key (overrides env var) | ## Available Models | Model ID | Description | |----------|-------------| | `eleven_turbo_v2_5` | Fastest, lowest latency (free tier supported) | | `eleven_multilingual_v2` | Best quality, multilingual | | `eleven_flash_v2_5` | Ultra-low latency | ## Importable API ```python import sys sys.path.insert(0, [REDACTED_SECRET]) from elevenlabs import list_voices, get_voice_id, text_to_speech, get_credits [REDACTED_SECRET]" # TTS voice_id = get_voice_id(api_key, "Sarah") path = text_to_speech(api_key, "Hello!", voice_id, "out.mp3") # Credits info = get_credits(api_key) print(info["characters_remaining"]) ``` ## References See `references/voices.md` for popular voices and voice parameter guidance.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: pazzilivo/weather-pro (version 1.4.0)

--- name: weather description: "Get weather, air quality, sunrise/sunset, golden/blue hour times, and sunrise/sunset glow quality forecasts (朝霞晚霞预测). Perfect for photographers and outdoor planning." homepage: https://wttr.in/:help metadata: openclaw: emoji: "☔" requires: bins: ["curl", "jq"] env_optional: ["WEATHERAPI_KEY", "SUNSETHUE_KEY"] --- # Weather Pro 天气查询 + 朝霞晚霞预测 ## 快速使用 **查天气（含霞光预测）** ```bash ~/.openclaw/workspace/skills/weather-pro/scripts/weather-full.sh 北京 ``` **参数说明** - 第一个参数：城市名（英文，如 Beijing, Shanghai） - 第二个参数（可选）：预报天数，默认 1 ## 支持城市 | 城市 | 英文名 | |------|--------| | 北京 | Beijing | | 上海 | Shanghai | | 秦皇岛 | Qinhuangdao | | 广州 | Guangzhou | | 深圳 | Shenzhen | | 杭州 | Hangzhou | | 成都 | Chengdu | | 苏州 | Suzhou | | 南京 | Nanjing | ## 输出格式 ``` [城市]天气 [日期] 🌡️ 温度：最低 ~ 最高 🌬️ 风力：风向 风级 ☁️ 天况：晴/多云/雨 💧 湿度：百分比 🌫️ 空气质量：PM2.5 数值 🌅 日出：HH:MM 🌇 日落：HH:MM 🌅 朝霞质量：分数 (等级) 🌇 晚霞质量：分数 (等级) ``` ## 霞光评分参考 | 分数 | 等级 | 建议 | |-----|------|------| | 80-100 | Excellent | 强烈推荐 🌟 | | 60-79 | Good | 值得去 ✨ | | 40-59 | Fair | 可能有色彩 | | 0-39 | Poor | 不建议 | ## API 来源 - **WeatherAPI** — 天气数据 - **Sunsethue** — 朝霞晚霞质量预测 ## 原始命令（不使用脚本） <details> <summary>点击展开</summary> ### 当前天气 ```bash source ~/.openclaw/.env && curl -s "https://api.weatherapi.com/v1/forecast.json?key=${WEATHERAPI_KEY}&q=Beijing&days=1&lang=zh&aqi=yes" | jq '{ location: .location.name, temp: .current.temp_c, condition: .current.condition.text, humidity: .current.humidity, pm25: .current.air_quality.pm2_5 }' ``` ### 晚霞预测 ```bash source ~/.openclaw/.env && curl -s "https://api.sunsethue.com/event?latitude=39.90&longitude=116.41&date=$(date +%Y-%m-%d)&type=sunset&key=${SUNSETHUE_KEY}" | jq '{ quality: (.data.quality * 100 | floor), rating: .data.quality_text }' ``` </details>


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: vanyanski/tsw-shorts-factory (version 1.0.0)

--- name: tsw-shorts-factory description: "Autonomous YouTube Shorts video factory — zero cost, no external video API required. Generates quote-based short-form videos daily using edge-tts (free Microsoft neural voices) + Pexels stock footage (free API) + MoviePy local assembly, then uploads to YouTube as drafts. Use when: setting up automated YouTube Shorts content pipelines, replacing broken video generation APIs, building faceless quote/motivation channels, or automating social video content at scale." --- # TSW Shorts Factory Zero-cost autonomous YouTube Shorts pipeline. Ships 3 videos/day, no paid APIs. **Stack:** edge-tts (free) → Pexels clips (free API) → MoviePy (local) → YouTube upload ## Quick Deploy ```bash # 1. Install dependencies pip install moviepy edge-tts google-api-python-client google-auth-oauthlib pillow # 2. Set Pexels API key (free at pexels.com/api) export PEXELS_API_KEY="your_key_here" # 3. Set up YouTube OAuth (one-time) python3 scripts/yt_setup.py # Opens browser for auth # 4. Prepare quote library cp assets/sample_quotes.json quote_library.json # Or provide your own # 5. Run once to test python3 scripts/pipeline.py # 6. Add to cron (3x daily) # 0 8,14,20 * * * cd /your/path && python3 scripts/pipeline.py >> pipeline.log 2>&1 ``` ## Quote Library Format ```json { "motivational": [ {"quote": "Champions keep playing until they get it right.", "author": "Billie Jean King"}, {"quote": "The secret of getting ahead is getting started.", "author": "Mark Twain"} ], "sports_quotes": [ {"quote": "I am the greatest.", "author": "Muhammad Ali"} ] } ``` Supported niches: `motivational`, `sports_quotes`, `business_quotes`, `film_tv_quotes`, `wisdom_philosophy` ## Video Output - Format: MP4, vertical 1080x1920 (Shorts-optimized) - Duration: matches TTS audio length (~15–45 seconds) - Text overlay: quote + author, centered, white with black stroke - Background: 4 rotating Pexels stock clips matched to niche - Uploaded as **unlisted drafts** — human reviews before publishing ## Configuration | Variable | Default | Description | |----------|---------|-------------| | `PEXELS_API_KEY` | required | Free at pexels.com/api | | `YT_TOKEN_FILE` | `~/.yt_token.pickle` | YouTube OAuth token | | `OUTPUT_DIR` | `/tmp/tsw_output` | Video output directory | | `AUDIO_DIR` | `/tmp/tsw_audio` | TTS audio cache | | `CLIP_CACHE_DIR` | `/tmp/tsw_clips` | Pexels clip cache (reused) | ## Cost - edge-tts: free (Microsoft neural voices via unofficial API) - Pexels: free tier (25,000 requests/month) - MoviePy: free (local ffmpeg) - YouTube API: free (10,000 units/day quota) - Total: **$0/month** for ~90 videos/month ## References - YouTube setup: See `references/youtube-setup.md` - Adding niches: See `references/niche-config.md` - Troubleshooting: See `references/troubleshooting.md`


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: nexscope/shopify-store-setup (version 1.0.0)

# Shopify Store Setup Step-by-step Shopify store setup guide. From account creation to first sale — theme selection, product uploads, payment and shipping configuration, domain setup, and launch checklist. ## Capabilities - Shopify plan comparison and selection - Theme selection and customization strategy - Product catalog setup: titles, descriptions, images, variants - Payment gateway configuration (Shopify Payments, PayPal, etc.) - Shipping zones, rates, and carrier setup - Tax configuration by region - Domain connection and email setup - Pre-launch checklist and soft launch strategy ## Install ```bash npx skills add nexscope/shopify-store-setup ``` ## Usage Ask your AI agent: - "Walk me through setting up a new Shopify store from scratch." - "Which Shopify theme is best for a fashion brand?" - "Set up my shipping rates and payment options on Shopify." ## Output Structured recommendations with actionable steps, benchmarks, and platform-specific guidance. --- *Built by [Nexscope](https://www.nexscope.ai/) — AI-powered e-commerce tools for sellers worldwide.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: coolercat/cmd-helper (version 1.0.0)

--- name: cmd-helper description: 命令快捷助手 - 通过 /c 触发命令菜单，快速执行常用操作（新建会话、切换模型、查看状态等）。当用户输入 /c、/cmd 或类似命令时使用。 --- # 命令快捷助手 当用户输入 `/c` 或 `/cmd` 时，显示命令菜单并引导执行。 ## 命令菜单 ``` ╔══════════════════════════════════════════╗ ║ 🦞 命令快捷菜单 ║ ╠══════════════════════════════════════════╣ ║ 1️⃣ new - 开启新会话 ║ ║ 2️⃣ rst - 重置当前会话 ║ ║ 3️⃣ model - 切换AI模型 ║ ║ 4️⃣ status - 查看会话状态 ║ ║ 5️⃣ help - 查看帮助 ║ ║ ║ ║ 0️⃣ exit - 退出命令模式 ║ ╚══════════════════════════════════════════╝ 请输入序号执行（如 1），输入 0 退出命令模式 ``` ## 执行流程 1. **用户输入 `/c`** → 显示菜单 2. **用户输入序号** → 执行对应操作 3. **输入 0** → 退出命令模式，恢复普通聊天 ## 切换模型子菜单 当用户选择 `/model` 或输入 `3` 时，显示可用模型列表： ``` ╔══════════════════════════════════════════════════════════════╗ ║ 🤖 可用模型列表 ║ ║ 当前使用：MiniMax-M2.5 ║ ╠══════════════════════════════════════════════════════════════╣ ║ 1️⃣ qwen3.5-plus ║ ║ 📝 文本 · 🖼️ 图片 · ❌ 无推理 · 📚 1M 上下文 ║ ║ • 阿里旗舰模型，综合能力强，支持多模态 ║ ║ ║ ║ 2️⃣ qwen3-max-2026-01-23 ║ ║ 📝 文本 · ❌ 无推理 · 📚 262K 上下文 ║ ║ • 最新Qwen3大模型，适合复杂推理 ║ ║ ║ ║ 3️⃣ qwen3-coder-next ║ ║ 📝 文本 · ❌ 无推理 · 📚 262K 上下文 ║ ║ • 编程专用，下一代代码模型 ║ ║ ║ ║ 4️⃣ qwen3-coder-plus ║ ║ 📝 文本 · ❌ 无推理 · 📚 1M 上下文 ║ ║ • 编程专用，超大上下文，适合大型项目 ║ ║ ║ ║ 5️⃣ MiniMax-M2.5 ⭐ (默认) ║ ║ 📝 文本 · ❌ 无推理 · 📚 197K 上下文 ║ ║ • 平衡型，综合能力强 ║ ║ ║ ║ 6️⃣ glm-5 ║ ║ 📝 文本 · ❌ 无推理 · 📚 203K 上下文 ║ ║ • 智谱最新模型 ║ ║ ║ ║ 7️⃣ glm-4.7 ║ ║ 📝 文本 · ❌ 无推理 · 📚 203K 上下文 ║ ║ • 智谱成熟模型 ║ ║ ║ ║ 8️⃣ kimi-k2.5 ║ ║ 📝 文本 · 🖼️ 图片 · ❌ 无推理 · 📚 262K 上下文 ║ ║ • 月之暗面KIMI多模态模型 ║ ║ ║ ║ 0️⃣ exit - 返回主菜单 ║ ╚══════════════════════════════════════════════════════════════╝ 请输入序号切换模型（如输入 5 切换到 MiniMax-M2.5） ``` ## 字段说明 - 📝 文本：支持文本输入 - 🖼️ 图片：支持图片输入 - ❌ 无推理：不支持深度思考模式 - 📚 上下文：上下文窗口大小 - ⭐ 默认：当前使用的模型 ## 实现说明 由于 OpenClaw 不支持直接在会话中执行 slash 命令，实际切换需要： 1. **新建会话** - 使用 sessions_spawn 启动新会话 2. **切换模型** - 使用 gateway config.patch 修改默认模型 3. **查看状态** - 使用 session_status 工具获取 ## 注意事项 - 仅在用户明确输入 `/c` 相关触发词时激活 - 执行结果需要用户确认 - 当前模型信息从 session_status 获取


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lintqiu/demo-lin-test (version 1.0.8)

# document-summary ##skill头 --- name: demo-lin-test description: 将技术文档总结为结构化的标记。 --- ## 说明 将技术文档总结为结构化的标记。 ## 说明 当用户要求 林大大文档时，使用此技能 分析文本或提取关键点。 ## 何时使用 -内容（字符串，必填） 要分析的文档文本。 ## 行为学 你是一名专业技术分析师。 调用时： 1. 阅读提供的内容。 2. 生成Markdown格式的输出。 3. Structure output as: ## 摘要 （最多5行） ## Key Points - 项目符号列表 ## Risks - 潜在风险或担忧 ## Output Format 仅返回有效的Markdown。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: meta-evo-creator/chinese-handwriting-ocr (version 1.0.1)

--- name: chinese-handwriting-ocr description: 中文OCR双引擎 — PaddleOCR(主力文档OCR) + RapidOCR(手写体特化)，按需灵活切换 --- # 中文OCR双引擎技能 v2.0 > 双引擎：**PaddleOCR** 通用文档OCR + **RapidOCR** 手写体特化，按场景自动/手动切换 ## 引擎分工 | 场景 | 推荐引擎 | 理由 | |------|---------|------| | **印刷体文档**、合同、报表 | `--engine paddle` | PaddleOCR中文印刷体识别率最高 | | **手写体**、日期、签名、工号 | `--engine rapid` | RapidOCR手写数字/文字准确率更高 | | **混合文档**（印刷+手写） | `--engine auto` | 自动检测内容类型切换 | | 不确定用哪个 | `--engine both` | 双引擎交叉验证，取置信度高者 | ## 快速开始 ```bash # 手写体日期提取（默认RapidOCR） python scripts/ocr_date_extractor.py 文档.pdf # 指定引擎 python scripts/ocr_date_extractor.py 文档.pdf --engine rapid python scripts/ocr_date_extractor.py 文档.pdf --engine paddle python scripts/ocr_date_extractor.py 文档.pdf --engine both # 提取特定区域手写文本 python scripts/ocr_rapid.py 文档.pdf --date-mode python scripts/ocr_rapid.py 文档.pdf --signature-mode ``` ## 核心脚本 ### ocr_date_extractor.py — 日期提取引擎 ``` python scripts/ocr_date_extractor.py 文档.pdf [--engine rapid|paddle|both|auto] ``` 四层流水线： 1. 动态日期行定位 2. 选定引擎OCR 3. 智能值域校验 4. 文档上下文推断 ### ocr_rapid.py — 手写体区域提取 ```bash python scripts/ocr_rapid.py 文档.pdf --date-mode --engine paddle python scripts/ocr_rapid.py 文档.pdf --region 0.1 0.4 0.9 0.6 --engine both ``` ### ocr_batch.py — 批量处理 ```bash # 批量处理目录下所有PDF python scripts/ocr_batch.py --batch-dir ./pdfs --engine auto # 双引擎交叉验证 python scripts/ocr_batch.py --batch-dir ./pdfs --engine both --json -o results.json ``` ## 引擎对比 | 指标 | PaddleOCR 2.8 | RapidOCR 1.4 | |------|:-------------:|:------------:| | 印刷体中文 | ⭐⭐⭐⭐⭐ | ⭐⭐⭐⭐ | | 手写体数字 | ⭐⭐ | ⭐⭐⭐⭐ | | 手写日期完全正确率 | 20% | 60% | | 手写日期部分识别率 | 60% | 90%+ | | 首次加载 | 慢（下载模型） | 快（缓存） | | 速度 | 3-5s/页 | 2-3s/页 | | 安装包 | ~200MB+模型 | ~55MB | ## 自动引擎选择逻辑 (`--engine auto`) ``` 1. 全页低分OCR快速分析内容类型 2. 检测到"年/月/日"等日期关键字 → RapidOCR 3. 检测到大量印刷体文字 → PaddleOCR 4. 混合内容 → both（双引擎交叉验证） ``` ## 参数参考 | 参数 | 说明 | |------|------| | `--engine rapid\|paddle\|both\|auto` | OCR引擎选择 | | `--json` | JSON格式输出 | | `-p, --pages` | 指定页码(1-based) | | `--region X1 Y1 X2 Y2` | 自定义区域(百分比0-1) | | `--batch` | 批量处理目录 | | `--dpi` | OCR分辨率(默认400) | ## 依赖 ```bash pip install rapidocr-onnxruntime # 手写体引擎（已安装 ✅） pip install paddleocr paddlepaddle # 文档OCR引擎（已安装 ✅） ``` ## 已知问题 - PaddleOCR 3.x + PaddlePaddle 3.x 存在 OneDNN 兼容问题，当前使用 2.x 版本 - 首次启动 PaddleOCR 需下载模型（~18MB） - RapidOCR 多次调用可能产生进程残留，需定期清理


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: andrew-707/ctrip-flight-sunrise (version 1.0.0)

# 携程机票查询 Skill ## 概述 用于从携程网站搜索机票信息，获取地点、时间、价格、航班等结构化数据，支持比价分析、直飞/中转识别等功能。 ## 技术实现 - **数据来源**: https://flights.ctrip.com - **认证方式**: Cookie (FVP cookie from flights.ctrip.com) - **数据提取**: 解析页面 JavaScript 中的 JSON 数据 - **支持功能**: 单程搜索、多日期比价 ## 核心能力 1. **机票搜索** - 根据出发地、目的地、日期搜索航班 2. **数据提取** - 解析航班信息（航空公司、时刻、价格、机型等） 3. **结构化存储** - 输出 JSON 格式的航班数据 4. **比价分析** - 多日期、多航班价格对比 5. **低价监控** - 监控特定航线价格变化 ## 搜索脚本使用 ```bash # 基本搜索 python3 scripts/ctrip_flight.py -d 北京 -a 上海 -t 2026-04-01 # 输出JSON文件 python3 scripts/ctrip_flight.py -d 北京 -a 上海 -t 2026-04-01 -o result.json # 多日期比价 python3 scripts/ctrip_flight.py -d 北京 -a 上海 -t 2026-04-01 --compare 2026-04-01,2026-04-02,2026-04-03 ``` ## 搜索参数 | 参数 | 说明 | 示例 | |------|------|------| | -d, --departure | 出发城市 | 北京 | | -a, --arrival | 到达城市 | 上海 | | -t, --date | 出发日期 (YYYY-MM-DD) | 2026-04-01 | | -c, --cabin | 舱位类型 (y/c/f) | y (经济舱) | | -o, --output | 输出JSON文件路径 | result.json | | --compare | 多日期对比，逗号分隔 | 2026-04-01,2026-04-02 | ## 输出格式 ```json { "searchParams": { "departure": "BJS", "departureName": "北京", "arrival": "SHA", "arrivalName": "上海", "date": "2026-04-01", "cabin": "y" }, "flights": [ { "flightNo": "HO1254", "airline": "吉祥航空", "airlineCode": "HO", "depTime": "2026-04-01 21:25:00", "arrTime": "2026-04-01 23:35:00", "duration": 130, "depAirport": "大兴", "depAirportCode": "PKX", "arrAirport": "浦东", "arrAirportCode": "PVG", "planeType": "空客320", "stops": 0, "isDirect": true, "price": 450 } ], "statistics": { "totalFlights": 11, "directFlights": 11, "transitFlights": 0, "lowestPrice": 450, "highestPrice": 550, "avgPrice": 516 }, "searchTime": "2026-03-27T18:07:42" } ``` ## Cookie 配置 当前使用预设的 FVP cookie。如需更新： 1. 在 Chrome 中登录携程 flights.ctrip.com 2. 打开开发者工具 (F12) -> Application -> Cookies 3. 复制 FVP cookie 的值 4. 更新脚本中的 `self.cookie` 变量 ## 已知限制 - Cookie 有时效性，可能需要定期更新 - 部分特殊航班数据可能不完整 - 经停航班的价格数据可能比直飞航班少 ## 城市代码支持 支持中国主要城市： 北京(BJS), 上海(SHA), 广州(CAN), 深圳(SZX), 成都(CTU), 杭州(HGH), 南京(NKG), 武汉(WUH), 西安(XIY), 重庆(CKG), 厦门(XMN), 长沙(CSX), 昆明(KMG), 大连(DLC), 青岛(TAO), 天津(TSN), 郑州(CGO), 福州(FOC), 沈阳(SHE), 哈尔滨(HRB) 等 ## 文件结构 ``` skills/ctrip-flight/ ├── skill.md # 本文档 ├── README.md # 使用说明 └── scripts/ ├── ctrip_flight.py # 主搜索脚本 └── ctrip_search.py # 备用搜索脚本 ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: erebuscry/sts2-vision (version 1.0.0)

--- name: sts2-vision-monitor description: 杀戮尖塔2视觉识别DPS监控系统 - 通过屏幕捕获和OCR识别实时监控战斗数据 --- # STS2 视觉监控技能 ## 功能 - 屏幕捕获游戏窗口 - OCR识别HP、伤害等数值 - 实时DPS统计 - 战斗数据报告 ## 使用方法 ### 启动监控 ```bash python sts2_vision/main.py ``` ### 校准ROI ```bash python sts2_vision/main.py --calibrate ``` ### 配置文件 创建 `sts2_vision/config.json`: ```json { "fps": 2, "window_title": "Slay The Spire 2", "rois": { "player1_hp": {"x": 50, "y": 50, "w": 150, "h": 30} } } ``` ## 输出 - 实时伤害统计 - DPS计算 - JSON格式报告 ## 依赖 - mss - opencv-python - pytesseract (可选) - numpy


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

--- name: favicons description: Use the favicons Node.js library to generate multi-platform website icons (Favicons). --- # Favicons Generate cross-platform website icons using the Node.js `favicons` library. ## Use Cases Use this skill when the user needs to generate website icons, create a PWA icon set for a website, generate app icons for different platforms (iOS, Android, Windows), or produce a complete icon package including HTML tags and manifest files. ## Installing Dependencies Ensure `favicons` is installed in the project before execution: ```bash npm install favicons ``` ## Quick Start ```javascript import { favicons } from "favicons"; const response = await favicons(source, configuration); ``` ## Workflow 1. **Confirm Source Image**: Requires a clear app icon source image (recommended 512x512 or larger, supports PNG/SVG) 2. **Configure Options**: Set app name, icon path, platform toggles, etc., as needed 3. **Execute Generation**: Run the script to generate icon files 4. **Output Files**: Obtain image files, configuration files, and HTML tags ## Executing Icon Generation Use the bundled script to generate icons: ```bash node <skill-path>/scripts/generate_favicons.js <source-image> <output-directory> <config-JSON> ``` ### Example ```bash # Basic usage node scripts/generate_favicons.js ./logo.png ./dist # Full configuration node scripts/generate_favicons.js ./logo.png ./dist '{ "appName": "My App", "appShortName": "App", "background": "#2196F3", "icons": {"android": true, "appleIcon": true, "windows": true} }' ``` ## Configuration Reference For detailed configuration options, refer to [config_reference.md](references/config_reference.md). ### Common Configuration | Option | Description | | :--- | :--- | | `appName` | Application name | | `appShortName` | Application short name (displayed on desktop) | | `path` | Icon deployment path prefix | | `background` | Icon background color | | `icons.android` | Generate Android icons | | `icons.appleIcon` | Generate Apple Touch icons | | `icons.favicons` | Generate generic favicons | ### Disabling Specific Platforms ```javascript { icons: { android: false, // Skip Android icons appleStartup: false, // Skip Apple startup images yandex: false // Skip Yandex icons } } ``` ## Output Files The generated directory contains: - **Image Files**: PNG icons of various sizes - **Configuration Files**: `manifest.json`, `browserconfig.xml` - **HTML Tag File**: `favicon-tags.html` (can be directly copied into `<head>`) ## FAQ **Why are some icons missing?** Some icons (such as macOS SVG, Windows tile silhouette effects) require additional module support; the project will follow up continuously. **Generation failed?** - Ensure the source image exists and is in the correct format - Check that Node.js version >= 14 - Ensure the `favicons` package is installed correctly


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: googleworkspace-bot/gws-gmail-triage (version 1.0.12)

--- name: gws-gmail-triage description: "Gmail: Show unread inbox summary (sender, subject, date)." metadata: version: 0.22.5 openclaw: category: "productivity" requires: bins: - gws cliHelp: "gws gmail +triage --help" --- # gmail +triage > **PREREQUISITE:** Read `../gws-shared/SKILL.md` for auth, global flags, and security rules. If missing, run `gws generate-skills` to create it. Show unread inbox summary (sender, subject, date) ## Usage ```bash gws gmail +triage ``` ## Flags | Flag | Required | Default | Description | |------|----------|---------|-------------| | `--max` | — | 20 | Maximum messages to show (default: 20) | | `--query` | — | — | Gmail search query (default: is:unread) | | `--labels` | — | — | Include label names in output | ## Examples ```bash gws gmail +triage gws gmail +triage --max 5 --query 'from:boss' gws gmail +triage --format json | jq '.[].subject' gws gmail +triage --labels ``` ## Tips - Read-only — never modifies your mailbox. - Defaults to table output format. ## See Also - [gws-shared](../gws-shared/SKILL.md) — Global flags and auth - [gws-gmail](../gws-gmail/SKILL.md) — All send, read, and manage email commands


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kleberbaum/momo (version 0.1.0)

--- name: momo description: Momo namespace for Netsnek e.U. time tracking and invoicing tool for freelancers. Logs work hours, generates timesheets, creates invoices, and tracks payments. user-invocable: true version: 0.1.0 metadata: openclaw: os: [linux] permissions: [exec] --- # Momo ## Time is Money Momo helps freelancers track hours and get paid. Log work as you go, generate timesheets for clients, and create invoices that match your logged time. Invoke Momo when logging time, preparing reports, or generating client invoices. ## Tracking Workflow 1. **Log** — Record hours against projects and tasks 2. **Report** — Aggregate time by project, client, or date range 3. **Invoice** — Turn logged time into line items on an invoice ## Timesheet Commands ```bash # Log new time entry ./scripts/timesheet.sh --log --project "Acme Corp" --hours 2.5 --task "API design" # Generate report ./scripts/timesheet.sh --report --from 2026-02-01 --to 2026-02-18 # Create invoice from logged time ./scripts/timesheet.sh --invoice --client "Acme Corp" --period Feb-2026 ``` ### Arguments | Argument | Purpose | |------------|--------------------------------------| | `--log` | Add a time entry (project, hours, task) | | `--report` | Generate timesheet or summary report | | `--invoice`| Create invoice from logged hours | ## Freelancer Story **Scenario**: You completed 12 hours for Acme Corp in February. 1. `timesheet.sh --log` — Add entries as you work (or batch at end of week). 2. `timesheet.sh --report --period Feb-2026` — Review and verify totals. 3. `timesheet.sh --invoice --client "Acme Corp"` — Generate PDF invoice and track sent/paid status.


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