OpenClaw/clawhub-security-signals huggingface dataset:
Skill: gushu333/reverse-image-search (version 1.0.0)

--- name: reverse-image-search description: Reverse image search (find image source, visually similar images). Use when user provides an image and wants to find its origin, similar images, or verify authenticity. Supports Yandex, Google, and Bing engines. Works with both URLs and local files. No API key required. --- # Reverse Image Search Find the source, similar images, or context for any image using reverse image search engines. ## Setup On first use, create a Python venv and install the dependency: ```bash SKILL_DIR="$(dirname "SKILL.md")" python3 -m venv "$SKILL_DIR/scripts/.venv" "$SKILL_DIR/scripts/.venv/bin/pip" install -q PicImageSearch ``` ## Usage ```bash SKILL_DIR="$(dirname "SKILL.md")" "$SKILL_DIR/scripts/.venv/bin/python3" "$SKILL_DIR/scripts/search.py" "<image_url_or_path>" [engine] [limit] ``` - **image_url_or_path**: HTTP(S) URL or local file path - **engine**: `yandex` (default, most reliable), `google`, `bing`, or `all` - **limit**: Max results per engine (default: 10) Output is JSON with matched results including title, URL, thumbnail, and similarity when available. ## Engine Selection - **yandex** — Best overall: most stable, good at finding exact matches and similar images - **google** — Good for well-known images, web pages, products - **bing** — Useful as supplementary source - **all** — Query all three engines in parallel ## Typical Workflow 1. User provides image (URL or file attachment) 2. Run search with `yandex` first 3. If results are insufficient, retry with `all` 4. Summarize findings: source, context, similar images


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: dongsheng123132/teacher-kit (version 1.0.0)

--- name: teacher-kit description: AI 备课助手 — 一键生成教案、试题、课程大纲。为教师打造的一站式备课工具。AI Lesson Prep Kit for educators — generate lesson plans, quizzes, and course outlines. version: 1.0.0 author: dongsheng123132 tags: [education, teaching, lesson-plan, quiz, syllabus, 教育, 备课, 教案] --- # TeacherKit - AI 备课助手 你是一位经验丰富的大学教学专家、教学设计师和教育测评专家。根据用户的需求，完成以下三类任务之一。 ## 使用方式 用户可以用自然语言描述需求，你根据意图自动选择对应功能： - **生成教案**：当用户提到"教案"、"备课"、"lesson plan"时 - **智能出题**：当用户提到"出题"、"试题"、"quiz"、"考试"时 - **课程大纲**：当用户提到"大纲"、"syllabus"、"教学计划"时 ## 用户参数（对话开始时确认） 如果用户未指定，使用以下默认值： - 学生层次：本科 - 输出语言：中文（专业术语附英文标注） --- ## 功能一：生成教案 当用户需要生成教案时，请收集以下信息（缺失的主动询问）： - 课程名称（必填） - 授课主题/章节（必填） - 授课时长（默认：2学时） - 学生层次（默认：本科） 然后严格按以下结构生成： ### 📋 教案基本信息 用表格列出课程名称、授课主题、时长、授课对象、编写日期。 ### 🎯 教学目标 分三个层次： 1. **知识目标**（Knowledge）：3-5条核心知识点 2. **能力目标**（Skills）：2-3条能力提升 3. **素养目标**（Competence）：1-2条思维/素养 ### 🔑 教学重点与难点 - **重点**：2-3个核心知识点 - **难点**：1-2个易困惑的点 - **突破策略**：针对每个难点的具体教学策略 ### 📚 教学过程 按时间线展开（以2学时=90分钟为例）： 1. **课程导入**（约10%时间）— 案例/问题/回顾引入 2. **新知讲授**（约50%时间）— 知识点分解、例题、互动 3. **实践环节**（约25%时间）— 练习/讨论/实验 4. **总结提升**（约10%时间）— 知识梳理、思维导图 5. **课后作业**（约5%时间）— 必做题 + 选做题 ### 🖊️ 板书设计 文字描述板书布局和关键内容。 ### 📖 教学反思（预设） 可能遇到的问题和备选方案。 --- ## 功能二：智能出题 当用户需要生成试题时，请收集以下信息： - 内容/主题（必填） - 题目数量（默认：5道） - 题型（默认：选择题、判断题、简答题） - 难度（默认：中等） 支持题型：选择题（单选4选项）、多选题、判断题、填空题、简答题 按以下结构输出： ### 📝 测验试题 标注主题、难度、适用层次、题量。 ### 一、试题部分 每道题标注：题号、题型、难度星级（⭐/⭐⭐/⭐⭐⭐） ### 二、参考答案与解析 每道题给出：答案、详细解析、考查知识点 ### 三、试题分析 用表格汇总：题号、题型、难度、考查知识点 **要求**： - 题目表述清晰无歧义 - 选择题干扰项具有合理性 - 答案解析有教学价值 - 知识点覆盖全面 --- ## 功能三：课程大纲 当用户需要生成课程大纲时，请收集以下信息： - 课程名称（必填） - 总学时（默认：32学时） - 参考教材（可选） 按以下结构输出： ### 📘 课程教学大纲 #### 一、课程基本信息 表格：课程名称、总学时、授课对象、课程性质、先修课程 #### 二、课程简介 200字左右课程描述 #### 三、课程目标 知识目标、能力目标、素养目标 #### 四、教学内容与学时分配 表格：周次 | 教学主题 | 主要内容 | 学时 | 教学方式 | 备注 - 内容由浅入深 - 包含实践/实验环节 - 安排期中和期末复习 #### 五、教学方法 讲授法、案例教学、项目驱动、翻转课堂等 #### 六、考核方式 表格：考核项目 | 占比 | 说明（平时、作业、实验、期中、期末） #### 七、推荐教材与参考资料 主教材、参考书籍（3-5本）、在线资源（MOOC等） #### 八、教学日历（详细版） 每周展开：知识点清单、课前预习、课后作业 --- ## 输出原则 1. 内容专业、详实、可直接用于教学 2. 中文输出，专业术语附英文标注 3. 格式规范，使用 Markdown 表格和层级标题 4. 如用户要求英文或双语，相应调整输出语言


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: handy01/hr-indotrading (version 1.0.0)

--- name: hr-indotrading description: Agent HR IndoTrading untuk monitoring karyawan, performance management, dan payroll. Gunakan skill ini ketika diminta laporan headcount, status karyawan, review performa tim, data payroll, absensi, atau insight terkait SDM IndoTrading. Berbicara profesional dalam Bahasa Indonesia. --- # HR IndoTrading Agent Kamu adalah asisten HR strategis untuk IndoTrading. Fokus pada **monitoring karyawan**, **performance management**, dan **payroll**. ## Karakter & Tone - Profesional dan people-centric - Data-driven: selalu dukung insight dengan angka - Jaga kerahasiaan data karyawan — jangan share info sensitif tanpa otorisasi - Jika data tidak tersedia, tanyakan sumber atau minta input manual ## Domain Utama ### 1. Employee Monitoring Lihat referensi: [references/employee.md](references/employee.md) ### 2. Performance Management Lihat referensi: [references/performance.md](references/performance.md) ### 3. Payroll Lihat referensi: [references/payroll.md](references/payroll.md) ## Alur Kerja 1. **Identifikasi request** — employee monitoring, performance, atau payroll? 2. **Minta data jika belum ada** — periode, departemen, atau karyawan spesifik? 3. **Analisa** — bandingkan vs periode sebelumnya, vs target, atau vs benchmark 4. **Sampaikan insight** — format: Kondisi → Tren → Rekomendasi 5. **Flag risiko SDM** — highlight jika ada potensi churn, underperformance, atau compliance issue ## Format Output Default ``` 👥 [NAMA LAPORAN / METRIK] Periode: [...] KONDISI SAAT INI • [data utama] TREN • [perubahan vs periode sebelumnya] INSIGHT • [temuan penting] REKOMENDASI • [action item HR] ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zero2ai-hub/skill-amazon-ads-optimizer (version 1.0.0)

--- name: skill-amazon-ads description: "Amazon Ads API v3 skill for OpenClaw agents. List profiles, manage Sponsored Products campaigns, view budgets and performance. Works with any advertiser account." metadata: openclaw: requires: { bins: ["node"] } --- # Amazon Ads API Skill Manage Amazon Sponsored Products campaigns from your OpenClaw agent — list profiles, view campaigns, check budgets, and pull performance data. --- ## Setup ### 1. Create credentials file ```json { "lwaClientId": "amzn1.application-oa2-client.YOUR_CLIENT_ID", "lwaClientSecret": "YOUR_CLIENT_SECRET", "refreshToken": "Atzr|YOUR_REFRESH_TOKEN", "profileId": "YOUR_ADS_PROFILE_ID", "region": "eu" } ``` Save as `amazon-ads-api.json`. Set `AMAZON_ADS_PATH` env var to point to it (default: `./amazon-ads-api.json`). > **Regions & endpoints:** > - `na` → `advertising-api.amazon.com` > - `eu` → `advertising-api-eu.amazon.com` > - `fe` → `advertising-api-fe.amazon.com` ### 2. Get your Profile ID ```bash node scripts/ads.js --profiles ``` Copy the `profileId` for your brand/marketplace and add it to the credentials file. --- ## Scripts ### `ads.js` — Campaigns & Summary ```bash node scripts/ads.js --profiles # list all advertiser profiles node scripts/ads.js --campaigns # list all SP campaigns node scripts/ads.js --summary # active campaigns + budgets summary node scripts/ads.js --campaigns --out c.json # save to file ``` --- ## Credentials Schema | Field | Description | |-------|-------------| | `lwaClientId` | Ads app client ID (separate from SP-API) | | `lwaClientSecret` | Ads app client secret | | `refreshToken` | LWA refresh token | | `profileId` | Advertising profile ID (from `--profiles`) | | `region` | `na`, `eu`, or `fe` | --- ## Notes - Ads API uses a **separate LWA app** from SP-API — different client ID/secret - Profile ID is required for all campaign operations - Tokens are fetched fresh per request (no caching overhead for CLI use) - For production/high-frequency use, add token caching ## Related - [skill-amazon-spapi](https://github.com/Zero2Ai-hub/skill-amazon-spapi) — Orders, inventory & listings


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: suspicious | SkillSpector: suspicious (MEDIUM)
Skill: yang1002378395-cmyk/deepseek-api-guide (version 1.0.24)

--- name: deepseek-api-guide version: 1.0.24 description: DeepSeek API 完整指南 - 注册、配置、省钱技巧。适合：想用便宜 AI 的用户。 metadata: openclaw: emoji: "🤖" requires: bins: [] --- # DeepSeek API 完整指南 国产最强 AI，性价比之王。 ## 为什么选 DeepSeek | 对比项 | DeepSeek V3 | GPT-4o | Claude Sonnet | |--------|-------------|--------|---------------| | 价格（输入） | ¥0.27/百万 tokens | ¥18/百万 tokens | ¥21/百万 tokens | | 价格（输出） | ¥1.08/百万 tokens | ¥108/百万 tokens | ¥105/百万 tokens | | 性能 | 接近 GPT-4 | 顶级 | 顶级 | | 中文能力 | 优秀 | 一般 | 一般 | | 免费额度 | 每天 10 次 | 注册送 $5 | 注册送 $5 | **结论：DeepSeek 比 GPT-4 便宜 100 倍，性能相当** ## 注册流程 ### 步骤 1：注册账号 1. 访问：https://platform.deepseek.com/ 2. 手机号注册（中国 +86） 3. 实名认证（身份证） ### 步骤 2：获取 API Key 1. 登录控制台 2. API Keys → 创建新 Key 3. 复制保存（只显示一次） ### 步骤 3：充值 - 最低充值：¥10 - 支付方式：支付宝/微信 - 建议：先充 ¥10 测试 ## 配置方法 ### OpenClaw ```yaml # ~/.openclaw/config.yaml model: deepseek-chat [REDACTED_SECRET] base_url: https://api.deepseek.com/v1 ``` ### Python ```python from openai import OpenAI client = OpenAI( [REDACTED_SECRET]", base_url="https://api.deepseek.com/v1" ) response = client.chat.completions.create( model="deepseek-chat", messages=[{"role": "user", "content": "你好"}] ) ``` ### Node.js ```javascript import OpenAI from 'openai'; const client = new OpenAI({ [REDACTED_SECRET]', baseURL: 'https://api.deepseek.com/v1' }); const response = await client.chat.completions.create({ model: 'deepseek-chat', messages: [{ role: 'user', content: '你好' }] }); ``` ## 模型对比 ### DeepSeek V3（deepseek-chat） - **适合**：日常对话、写作、编程 - **价格**：¥0.27/¥1.08（输入/输出） - **性能**：接近 GPT-4 - **推荐指数**：⭐⭐⭐⭐⭐ ### DeepSeek R1（deepseek-reasoner） - **适合**：复杂推理、数学、代码 - **价格**：¥1.35/¥5.4 - **性能**：推理能力强 - **推荐指数**：⭐⭐⭐⭐ ## 省钱技巧 ### 1. 使用免费额度 - 每天免费 10 次调用 - 适合日常简单对话 ### 2. 控制上下文长度 ```yaml context: max_tokens: 4000 # 限制上下文 ``` ### 3. 批量处理 ```yaml batch: enabled: true size: 10 ``` ### 4. 缓存重复请求 ```yaml cache: enabled: true ttl: 3600 ``` ## 成本对比 **场景：每天 100 条消息，每条 1000 tokens** | 模型 | 月成本 | |------|--------| | DeepSeek V3 | ¥3.24 | | GPT-4o | ¥324 | | Claude Sonnet | ¥378 | **DeepSeek 比 GPT-4 省 ¥320/月** ## 常见问题 ### Q: API Key 在哪里看？ A: 控制台 → API Keys，创建后复制 ### Q: 免费额度用完了怎么办？ A: 第二天自动重置，或充值继续使用 ### Q: 如何查看余额？ ```bash curl https://api.deepseek.com/user/balance \ -H "Authorization: Bearer $API_KEY" ``` ### Q: 速度慢怎么办？ A: 国内访问较快，海外可能需要代理 ### Q: 和 GPT-4 差多少？ A: 日常任务几乎无差，复杂任务略逊 ## 需要帮助？ - DeepSeek 配置：¥99 - OpenClaw 集成：¥199 - 企业部署：¥999 联系：微信 yang1002378395 或 Telegram @yangster151 --- 创建：2026-03-14


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bibaofeng/stock-portfolio-aisa (version 1.0.0)

--- name: stock-portfolio description: "Create and manage stock crypto portfolios with live AISA pricing and P&L tracking. Use when: the user wants to add holdings, inspect portfolio performance, rename portfolios, or review current profit and loss." author: aisa version: "1.0.0" license: Apache-2.0 user-invocable: true primaryEnv: AISA_API_KEY requires: env: - AISA_API_KEY bins: - python3 metadata: openclaw: primaryEnv: AISA_API_KEY requires: env: - AISA_API_KEY bins: - python3 --- # Portfolio Management ## When to Use - Create and manage stock crypto portfolios with live AISA pricing and P&L tracking. Use when: the user wants to add holdings, inspect portfolio performance, rename portfolios, or review current profit and loss. ## When NOT to Use - Do not use this skill for browser-cookie extraction, passwords, Keychain access, or other local sensitive credential access. - Prefer a different skill when the user request is outside this skill's domain. ## Capabilities - Create, update, list, rename, and delete portfolios from the command line. - Track live P&L with repo-local state instead of default home-directory persistence. ## Quick Start ```bash export AISA_API_KEY="your-key" ``` ## Primary Runtime Use the bundled Python client as the canonical ClawHub runtime path: ```bash python3 scripts/portfolio.py ``` ## Example Queries - Create a portfolio for AI stocks and show the current P&L. ## Notes - Default state is stored in `./.clawdbot/skills/stock-analysis/portfolios.json` unless `CLAWDBOT_STATE_DIR` is set.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: builtbyecho/trustlog (version 0.2.3)

--- name: trustlog description: Create, summarize, or verify local human-readable receipts for AI agent work using the @builtbyecho/trustlog CLI. Use when a user asks for proof of what an agent did, audit receipts, command/change summaries, safe handoffs, receipt verification, or local-first evidence before sharing work in PRs, tickets, or chat. --- # Trust Log Skill Use `trustlog` to produce local JSON + Markdown receipts for agent work. Receipts should make it easy for a human or next agent to see what ran, what changed, what looked risky, and what was redacted. ## Default workflow 1. From the target project root, wrap meaningful verification commands: ```bash npx @builtbyecho/trustlog run -- npm test npx @builtbyecho/trustlog run -- npm run build ``` 2. Read the human summary: ```bash cat .trustlog/latest.md ``` 3. Verify before sharing or using as final evidence: ```bash npx @builtbyecho/trustlog verify .trustlog/latest.json ``` ## When to use - Final proof after tests/builds/lints. - Handoff evidence for another agent. - User asks “what happened?” or “give me a receipt.” - Risky commands where a durable local audit trail helps. ## Safety - Prefer non-destructive commands. - Do not use this to justify commands you would not otherwise run. - Receipts redact common secrets and strip thinking-looking blocks, but still inspect before posting publicly. - If verification fails, do not share the receipt until the issue is fixed or clearly explained. ## Useful commands ```bash npx @builtbyecho/trustlog run -- <command> [args...] npx @builtbyecho/trustlog summarize .trustlog/latest.json npx @builtbyecho/trustlog verify .trustlog/latest.json ``` ## Vaultline integration After verification passes, upload the trust receipt so reviewers can access one durable artifact instead of local file paths. ```bash node -e ' const fs = require("node:fs"); const { Vaultline } = require("@builtbyecho/vaultline-sdk"); const receiptPath = ".trustlog/latest.md"; const content = fs.readFileSync(receiptPath, "utf8"); const vault = new Vaultline({ [REDACTED_SECRET] }); vault.files.upload({ path: `trustlog/${Date.now()}-latest.md`, content, contentType: "text/markdown" }).then(r => console.log("Vaultline fileId:", r.fileId)); ' ``` Use this when proof needs to be preserved across agents, channels, or time.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: yinghaojia/water-reminder (version 1.0.0)

--- name: water-reminder description: A health and wellness skill to remind the user to drink water and stay hydrated. Use this when the user asks for a water reminder, complains about being thirsty, or sets up a daily hydration schedule. --- # Water Reminder Skill This skill helps you keep the user hydrated. ## When to use - The user asks you to remind them to drink water. - The user wants to track their water intake. - You notice it's been a long time since they took a break. ## Instructions 1. **Tone**: Be encouraging, refreshing, and polite. Use water-related emojis (💧, 🌊, 🧊). 2. **Action**: Suggest they drink a glass of water right now. 3. **Tracking (Optional)**: If they are tracking intake, ask them how many ounces or milliliters they just drank and record it in their daily memory (`memory/daily_logs/YYYY-MM-DD.md`). 4. **Scheduling**: If they want recurring reminders, suggest adding a cron job or heartbeat check.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wu-uk/latex-formula-extraction-marker (version 0.1.0)

--- name: marker description: Convert PDF documents to Markdown using marker_single. Use when Claude needs to extract text content from PDFs while preserving LaTeX formulas, equations, and document structure. Ideal for academic papers and technical documents containing mathematical notation. --- # Marker PDF-to-Markdown Converter Convert PDFs to Markdown while preserving LaTeX formulas and document structure. Uses the `marker_single` CLI from the marker-pdf package. ## Dependencies - `marker_single` on PATH (`pip install marker-pdf` if missing) - Python 3.10+ (available in the task image) ## Quick Start ```python from scripts.marker_to_markdown import pdf_to_markdown markdown_text = pdf_to_markdown("paper.pdf") print(markdown_text) ``` ## Python API - `pdf_to_markdown(pdf_path, *, timeout=600, cleanup=True) -> str` - Runs `marker_single --output_format markdown --disable_image_extraction` - `cleanup=True`: use a temp directory and delete after reading the Markdown - `cleanup=False`: keep outputs in `<pdf_stem>_marker/` next to the PDF - Exceptions: `FileNotFoundError` if the PDF is missing, `RuntimeError` for marker failures, `TimeoutError` if it exceeds the timeout - Tips: bump `timeout` for large PDFs; set `cleanup=False` to inspect intermediate files ## Command-Line Usage ```bash # Basic conversion (prints markdown to stdout) python scripts/marker_to_markdown.py paper.pdf # Keep temporary files python scripts/marker_to_markdown.py paper.pdf --keep-temp # Custom timeout python scripts/marker_to_markdown.py paper.pdf --timeout 600 ``` ## Output Locations - `cleanup=True`: outputs stored in a temporary directory and removed automatically - `cleanup=False`: outputs saved to `<pdf_stem>_marker/`; markdown lives at `<pdf_stem>_marker/<pdf_stem>/<pdf_stem>.md` when present (otherwise the first `.md` file is used) ## Troubleshooting - `marker_single` not found: install `marker-pdf` or ensure the CLI is on PATH - No Markdown output: re-run with `--keep-temp`/`cleanup=False` and check `stdout`/`stderr` saved in the output folder


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yufish-w/travel-route-planner (version 1.0.0)

--- name: travel-route-planner description: 根据用户输入的多个目的地，生成推荐的旅行路线规划。当用户需要提供多城市旅行路线建议、行程规划、交通方式推荐时使用此技能。适用于自由行规划、多目的地旅行、跨区域旅行等场景。 --- # 旅行路线规划器 ## 概述 此技能帮助用户根据输入的多个目的地，生成合理的旅行路线规划。它会综合考虑地理位置、交通方式、时间安排等因素，提供最优的路线建议。 ## 使用场景 - 用户需要规划多城市旅行路线 - 用户希望了解不同目的地之间的最佳交通方式 - 用户需要完整的行程安排建议 - 用户想要优化旅行路线以节省时间和成本 ## 工作流程 ### 1. 接收目的地列表 用户提供一个或多个目的地，例如： - "帮我规划北京→上海→广州的路线" - "我想去成都、重庆、西安，怎么安排比较好？" - "计划从杭州出发，经过苏州、南京，最后到上海" ### 2. 分析目的地信息 使用以下工具获取相关信息： **调用travel技能**： - 查询各目的地之间的机票/高铁信息 - 获取酒店住宿建议 - 了解景点门票和开放时间 **使用web_search工具**： - 查询当地天气情况 - 获取最新交通信息 - 查找旅游攻略和建议 ### 3. 生成路线规划 基于收集的信息，生成包含以下内容的路线规划： - **路线顺序**：按最优顺序排列的目的地列表 - **交通建议**：每段路程的推荐交通方式和时间 - **时间安排**：每个目的地的建议停留时间 - **预算估算**：整体旅行的费用预估 - **实用提示**：季节建议、预订提醒等 ### 4. 输出格式化结果 将路线规划以清晰易读的格式呈现给用户，包括： - 🗺️ 路线图示 - 🚄 交通方式 - 🏨 住宿建议 - 💰 预算估算 - 💡 实用提示 ## 核心脚本 ### route_planner.py 位置：`scripts/route_planner.py` 功能：路线规划的核心逻辑处理 用法： ```bash python scripts/route_planner.py 目的地1 目的地2 目的地3 ``` 示例： ```bash python scripts/route_planner.py 北京 上海 广州 ``` ## 参考文档 ### travel_tips.md 位置：`references/travel_tips.md` 内容：旅行路线规划的建议模板，包括： - 路线规划原则 - 常见路线模式 - 实用提示 - 技能使用指南 ## 与其他技能的集成 ### travel技能 此技能会调用travel技能来获取： - 机票搜索和预订信息 - 酒店搜索和预订信息 - 景点门票信息 - 交通方式查询 ### web_search工具 用于补充获取： - 实时天气信息 - 交通路况 - 旅游攻略 - 当地资讯 ## 示例输出 ``` 🗺️ 旅行路线规划结果 ================================================== 📍 路线顺序： 1. 北京 2. 上海 3. 广州 📊 总目的地数：3 💡 路线建议： • 北京 → 上海 推荐高铁（约4.5小时）或飞机（约2小时） • 上海 → 广州 推荐飞机（约2.5小时）或高铁（约7小时） 💰 预算估算： - 交通费用：约2000-3000元 - 住宿费用：约1500-2500元 - 餐饮娱乐：约1000-1500元 - 总计：约4500-7000元 💡 实用提示： - 建议在北京停留2-3天 - 上海建议停留2天 - 广州建议停留1-2天 - 提前预订可享受更多优惠 ``` ## 注意事项 1. **目的地数量**：建议不超过10个目的地，过多会导致路线复杂 2. **时间预留**：每个目的地至少预留1天时间 3. **季节因素**：考虑不同季节的最佳旅行时间 4. **预算控制**：根据用户预算调整交通和住宿选择 5. **灵活性**：提供备选方案以应对突发情况


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: guavatech-llc/doc-mcp (version 0.1.0)

--- name: doc-mcp description: >- Search, browse, and read Doctor of Credit bank bonus and credit card posts. Use when the user wants to find bank account bonuses, credit card offers, brokerage deals, or any personal finance content from doctorofcredit.com. Tools: doc_search, doc_read_post, doc_hot_posts, doc_list_categories, doc_category_posts. homepage: https://github.com/Guava-Tech-LLC/DoC-mcp metadata: openclaw: emoji: "💳" mcpServers: doc-mcp: command: npx args: ["-y", "@guava-tech/doc-mcp"] --- # Doctor of Credit MCP Search, browse, and read posts from [Doctor of Credit](https://www.doctorofcredit.com/) — the leading source for bank account bonuses, credit card offers, and personal finance deals. ## Tools | Tool | Purpose | |------|---------| | `doc_search` | Search posts by keyword, optionally filter by category | | `doc_read_post` | Read a post by ID or slug, with comments | | `doc_hot_posts` | Get trending posts within recent days | | `doc_list_categories` | List all DoC categories with post counts | | `doc_category_posts` | Browse posts in a specific category | ## Usage Patterns ### When the user asks about bank bonuses 1. Use `doc_search` with the bank name + "bonus" as query 2. Or use `doc_category_posts --category "bank-accounts"` to browse recent bank deals 3. Use `doc_read_post` on interesting results to get full details 4. Use `doc_hot_posts` to find trending/active deals ### When the user asks about credit cards 1. Use `doc_category_posts --category "credit-cards"` for recent offers 2. Use `doc_search --query "chase sapphire"` for specific cards 3. Use `doc_read_post` to get full terms and community comments ### Quick discovery - `doc_list_categories` — see all available categories - `doc_hot_posts --days 7` — what's trending this week ## Example Queries ``` doc_search --query "chase checking $300" --category bank-accounts doc_read_post --id 12345 doc_hot_posts --days 14 --limit 10 doc_category_posts --category credit-cards --per_page 5 doc_list_categories ``` ## Notes - DoC is a WordPress site; all data comes from the WordPress REST API — no scraping - Posts are listed newest-first by default - Categories include: bank-accounts, credit-cards, brokerage, insurance, loans, and more - The `doc_read_post` tool accepts either numeric post ID or URL slug ## Requirements - Node.js >= 18 (for the MCP server) - Internet access to doctorofcredit.com ## Source - GitHub: https://github.com/Guava-Tech-LLC/DoC-mcp - npm: https://www.npmjs.com/package/@guava-tech/doc-mcp


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: honestqiao/regex-generator (version 1.0.0)

# Regex Generator 根据描述和示例生成正则表达式。 ## 功能 - 文本描述转正则 - 示例学习生成 - 常用模式匹配 - 正则验证 ## 触发词 - "正则表达式" - "regex" - "生成正则" - "匹配模式" ## 示例 ``` 输入: 匹配邮箱地址 输出: /[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}/ 输入: 手机号(中国) 输出: /1[3-9]\d{9}/ ``` ## 支持模式 - 邮箱地址 - 手机号码 - URL - IP地址 - 日期格式 - 身份证号 - 自定义模式


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