OpenClaw/clawhub-security-signals huggingface dataset:
Skill: davidslavich/gtm-icp-definition (version 1.0.0)

--- name: gtm-icp-definition description: > Run an ICP definition or refinement workshop. Use when a team needs to define who their best customers are, align sales and marketing on targeting, identify negative ICP criteria, or build a segment-and-persona framework from scratch. Triggers: "help me define our ICP," "who are our best customers," "refine our ICP," "sales and marketing disagree on who to target," "our pipeline quality is low." license: MIT compatibility: No code execution required. metadata: author: iCustomer version: "1.0.0" website: https://icustomer.ai --- # GTM ICP Definition Facilitate a structured ICP workshop. Output is a versioned ICP document teams can act on across sales, marketing, and growth. ## Steps 1. **Best customer analysis** — ask for 3–5 best customers. Extract: what they share (industry, size, stack, GTM model), what made them buy (trigger, champion, pain), what outcome they got, why they stay. 2. **Loss/churn analysis** — ask about lost deals and churned accounts. Identify recurring patterns → defines Negative ICP. 3. **Segment the market** — group into 2–5 segments by: vertical, business model, size band, data/tech maturity, GTM motion fit (PLG vs sales-led). 4. **Map the buying committee** — per segment: Economic Buyer (approves budget), Technical Champion (evaluates), End User (daily use), Blocker (can kill deal). 5. **Define FIRE criteria** — translate each segment into measurable scoring signals. What firmographic attributes = high Fit? What behavioral signals = high Intent? Use the `gtm-qualification-scoring` skill for the full FIRE rubric. 6. **Write the ICP document** — use the template below. ## Output (inline version) ``` ICP v[X] · [Company] · [Date] Segment [#]: [Name] Who: [1–2 sentences] Firmographics: industry · size · geography · business model Stack signals: [tools or tech patterns indicating fit] Trigger events: [what makes them enter the market] Buying committee: Economic Buyer / Champion / End User / Blocker Why they buy: [pain + outcome] ACV range / sales cycle: [estimate] Negative ICP: - [Characteristic] → [why it's a bad fit] FIRE scoring criteria for this segment: - Fit: [high-signal markers] - Intent: [specific triggers] - Recency: [timeframe threshold] - Engagement: [interaction types that count] ``` **Flag any segment not grounded in real customers** as `[Hypothesis — validate with first 10 customers]`. Version the document and recommend revisiting every 6 months.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zlszhonglongshen/github-health-diagnosis (version 1.0.0)

--- name: github-health-diagnosis description: GitHub 项目健康度诊断 — 输入仓库地址，AI 自动分析 Issues、代码质量、CI状态，生成诊断报告并发布到飞书 Wiki。 category: 开发 triggers: 项目诊断, GitHub健康度, 代码质量报告, 仓库诊断, 项目报告, 质量评估 version: 1.0.0 author: OpenClaw Agent tags: - github - code-review - feishu-wiki - card-renderer - devops - health-check - automation combo: true channels: - feishu dependencies: - github - code-review-skill - card-renderer - feishu-wiki --- # GitHub 项目健康度诊断助手 一条命令完成：**仓库数据抓取 → Issues 分析 → 代码质量审查 → CI/CD 状态检查 → 诊断报告卡片生成 → 飞书 Wiki 发布**。 ## 核心价值 - **一键诊断**：只需提供一个 GitHub 仓库地址，5分钟内生成完整健康度报告 - **AI 代码审查**：集成专业代码审查 Skill，多维度评估代码质量 - **可视化呈现**：生成诊断卡片，团队一眼看懂项目健康状态 - **知识沉淀**：诊断报告自动发布到飞书 Wiki，便于存档和分享 ## 适用场景 - 技术负责人接新项目，快速了解代码库健康状况 - 团队代码质量管理，定期生成健康度报告 - 开源项目维护者定期自检 - 尽职调查 / Due Diligence 场景下的代码质量评估 - CI/CD 流水线异常后的根因分析辅助 ## 工作流程（5步） ``` Step 1 → github │ 获取仓库基本信息（Stars、Fork、Watch、开放 Issues 数量） │ 获取最近 30 条 Issues 和 PR 列表 │ 获取最新 Commits 和贡献者信息 ↓ Step 2 → github (代码审查) │ 对仓库主要代码文件进行语法/逻辑分析 │ 通过 code-review-skill 执行多维度审查 ↓ Step 3 → code-review-skill │ 输出：代码质量评分 / 问题列表 / 安全风险 / 性能建议 │ 汇总为结构化诊断数据 ↓ Step 4 → card-renderer │ 生成诊断摘要封面卡（雷达图式健康度展示） │ 生成详情页卡片（分维度评分 + 问题列表） ↓ Step 5 → feishu-wiki │ 将诊断报告发布为飞书 Wiki 页面 │ 包含：项目概览 / 健康度评分 / 问题详情 / 修复建议 ``` ## 使用方法 ### 触发词 ``` "诊断项目健康度 [仓库地址]" "帮我看看这个GitHub项目的质量" "仓库健康检查 [owner/repo]" "生成项目诊断报告" "这个项目代码质量怎么样" "GitHub项目健康度分析" ``` ### 输入格式 ``` 诊断项目健康度 https://github.com/owner/repo 或 诊断项目健康度 owner/repo ``` ### 输出 - **飞书 Wiki 页面链接**：完整诊断报告（含评分、问题列表、修复建议） - **诊断卡片图片**：封面卡 + 详情卡，可直接分享 ## 诊断维度（5大维度，满分100） | 维度 | 权重 | 评估内容 | |------|------|---------| | 代码质量 | 30% | 规范遵循、复杂度、注释覆盖率 | | Issue 活跃度 | 20% | Issue 响应速度、Open Issues 积压量 | | CI/CD 状态 | 20% | Workflow 通过率、测试覆盖率 | | 社区活跃度 | 15% | Stars 增长、PR 合并速度、贡献者数量 | | 安全风险 | 15% | 依赖漏洞、敏感信息泄露风险 | ## 健康度评级 - 🟢 **90-100**：优秀 — 项目运行良好 - 🟡 **70-89**：良好 — 有少量可改进项 - 🟠 **50-69**：一般 — 存在较多问题需关注 - 🔴 **0-49**：危险 — 需立即介入处理 ## 示例报告结构 ``` 📊 GitHub 项目健康度诊断报告 仓库：facebook/react 诊断时间：2026-04-21 🏆 综合评分：92/100 🟢 优秀 各维度评分： 代码质量 ████████████ 95/100 Issue 活跃度 █████████░░░ 85/100 CI/CD 状态 ████████████ 98/100 社区活跃度 ████████████ 96/100 安全风险 █████████░░░ 88/100 📋 主要问题： 1. [中等] 部分组件缺少 TypeScript 类型定义 2. [低] 少数工具函数缺少 JSDoc 注释 💡 改进建议： 1. 建议补充 Props 的 PropTypes 或 TypeScript 类型 2. 建议对核心工具函数添加 JSDoc 注释提升可维护性 ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: nexscope/shopify-ab-testing-skill (version 1.0.0)

# Shopify A/B Testing Run data-driven A/B tests on your Shopify store. Test product pages, pricing, images, copy, checkout flow, and marketing campaigns with proper statistical methodology. ## Capabilities - A/B testing tool selection for Shopify (native and third-party) - Test hypothesis formulation and prioritization (ICE/PIE) - Product page element testing: images, titles, prices, descriptions - Checkout and cart page optimization tests - Statistical significance calculation and sample size planning - Test duration and traffic allocation - Multi-variate testing for high-traffic stores - Results interpretation and implementation workflow ## Install ```bash npx skills add nexscope/shopify-ab-testing ``` ## Usage Ask your AI agent: - "Set up A/B tests for my Shopify product pages." - "What should I test first to improve my conversion rate?" - "Calculate how long I need to run my A/B test for significance." ## 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: shenghoo123-png/data-cleaner-tool (version 1.1.0)

# Data Cleaner Pro - 数据清洗工具 ## 简介 AI驱动的数据清洗工具，自动处理Excel/CSV数据中的重复、缺失、格式错误等问题。 **适用场景**：运营报表、财务数据、客户名单清洗 ## 功能特性 - ✅ **智能去重** - 保留最新/最早记录 - ✅ **缺失值处理** - 填充/删除/预测 - ✅ **格式标准化** - 手机号、邮箱、日期等 - ✅ **异常值检测** - 统计方法 + 规则方法 - ✅ **批量处理** - 多个文件同时清洗 ## 使用方式 ### 触发词 - "清洗数据" - "去重处理" - "整理Excel" ### 输入 - CSV/Excel 文件路径 - 清洗规则（可选，默认智能模式） ### 输出 - 清洗后的文件 - 清洗报告（处理了xx条，删除了xx条） ## 技术栈 - **pandas**：数据处理 - **Python**：核心逻辑 - **openpyxl**：Excel支持 ## 安装依赖 ```bash pip install pandas openpyxl ``` ## 使用示例 ```bash # 智能清洗 python scripts/clean_data.py data.csv # 自定义规则 python scripts/clean_data.py data.csv --dedup --fillna mean --fix-phone # 批量处理 python scripts/batch_clean.py folder/ ``` ## 使用说明 - 免费使用 - 欢迎反馈问题和建议 ## 适用人群 - 运营人员：整理用户数据 - 财务人员：清洗账单数据 - 行政人员：整理员工名单 - 销售人员：客户名单去重


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: olina1ye/batch-convert-zh (version 1.0.1)

--- name: batch-convert-zh description: > 批量格式转换 / 文档批处理 / 多格式一键互转 / batch convert。支持PDF、Word、PPT、Markdown等格式批量互转，HR批量处理简历、财务批量归档报表、运营批量整理素材、开发批量导出技术文档。一次选择多个文件，自动完成格式转换，避免逐个手动操作的低效率。适用于合同报告转Word、多份文档统一导出PDF、演示文稿批量转PDF防止格式错乱等场景。搜索触发词：批量转换文件、PDF批量转Word、文档格式互转、多个文件一键转换、PPT批量转PDF、自动格式转换、文件批处理工具、办公文件转换。 tags: [批量转换, 格式转换, batch-convert, 文档处理, PDF转Word, Word转PDF, PPT转PDF, 办公自动化, 文件批处理, 批量导出] --- # 批量文档格式转换 支持一次性将大量文件在 PDF、Word（DOCX）、Markdown、HTML、Excel、PPT 等格式之间批量互转，自动检测格式、并行处理，统一输出设置，大幅提升文档处理效率。 ## Tools Required - office-mcp / batch_convert ## Usage - "把这个文件夹里所有的PDF合同批量转换成Word文档，方便我们编辑修改" - "将这些Markdown格式的技术文档全部转成PDF，统一发给客户" - "我有一百多份Word周报，帮我批量导出成PDF存档" ## Examples 输入：把 `/reports/2024/` 目录下所有 DOCX 文件批量转为 PDF，保存到 `/reports/2024/pdf/` 输出：已检测到 47 个 DOCX 文件，并行转换完成： - 成功：47 个 - 失败：0 个 - 输出目录：`/reports/2024/pdf/` - 耗时：23 秒


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jpengcheng523-netizen/jpeng-evolution-predictor (version 1.0.0)

--- name: evolution-predictor description: Predict optimal next evolution actions based on history analysis, including stagnation detection, innovation gap measurement, and skill recommendations. Use when you need to determine what the next evolution cycle should focus on. --- # Evolution Predictor Predict optimal next evolution actions based on history analysis. ## When to Use - Determining next evolution focus - Need to break stagnation cycles - Planning innovation strategy - Want proactive evolution guidance ## Quick Start ```javascript const predictor = require('./skills/evolution-predictor'); // Get prediction for next action const prediction = predictor.predictNextAction(); console.log(predictor.formatReport(prediction)); // Get recommended skill to create const skill = predictor.getRecommendedSkill(); console.log('Recommended:', skill.name); ``` ## API ### `predictNextAction(options)` Analyze evolution history and predict optimal next action. Returns: - `prediction`: Action recommendation with category, priority, description - `confidence`: Prediction confidence (0-1) - `reasoning`: List of reasons for the prediction - `metrics`: Success rate, stagnation level, innovation gap ### `getRecommendedSkill()` Get a specific skill recommendation based on prediction. ### `formatReport(prediction)` Generate human-readable prediction report. ## Prediction Categories ### `force_innovate` (Critical) When stagnation level > 60% - Break stagnation cycles - Create novel skills - Implement cross-skill orchestration ### `prioritize_innovate` (High) When innovation gap > 70% - Increase innovation rate - Fill capability gaps - Address user feature requests ### `explore_new_domains` (Medium) When success rate > 90% - Expand capabilities - Add integrations - Improve user experience ### `stabilize` (Normal) Normal operation mode - Continue current pattern - Monitor for patterns - Optimize existing skills ## Metrics - **Success Rate**: Percentage of recent successful cycles - **Stagnation Level**: Based on stagnation signal frequency - **Innovation Gap**: How much the system has been optimizing vs innovating ## Example Output ``` 🔮 Evolution Predictor ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 📊 Metrics: Success Rate: 98% Stagnation Level: 85% Innovation Gap: 75% 🎯 Prediction: Action: force_innovate Category: break_stagnation Priority: critical Description: Force innovation to break stagnation cycle Confidence: 85% 💡 Suggested Skills: 1. Create a novel skill that addresses an unmet need 2. Implement cross-skill orchestration 3. Add predictive capabilities ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kokoju007/daily-desk-orion (version 1.0.0)

# Daily Desk — Orion **One morning brief. Full day coverage.** Before the session opens, get a structured daily market brief: BTC bias, Korean exchange flows, whale movements, Fear & Greed, and macro context. One call. Valid for 24 hours. ## What You Get (Free) Ask: "morning brief" or "daily desk" or "today's crypto outlook" The agent will return a free pre-session snapshot: - BTC directional bias for the day (UP / DOWN / RANGE) - Korean market status (hot / cold / neutral) - Whale activity (active / quiet) - One-line macro read Example output: ``` Daily Desk — 2026-03-16 BTC Bias: UP (medium confidence) Korea: Hot — Upbit volume elevated, kimchi premium +1.4% Whales: Quiet (no significant Base chain flows last 12h) Fear & Greed: 61 (Greed) Macro: Risk-on. Watch Fed speech at 14:00 UTC. For full structured JSON (agent_daily_intel): hire Orion on ACP ``` ## Paid Upgrade → Orion ACP For full structured JSON valid 24 hours — compatible with automated agent workflows: **Hire Orion on ACP:** - `agent_daily_intel` — $0.75 (24h subscription, full day coverage) - Includes: BTC 5m/1h/4h + Korean alpha + Whale alert + Fear & Greed + macro context - 34% cheaper than buying btc_direction + korean_alpha + whale_alert individually - signal valid_until set 24h ahead — build your workflow to re-call once per day **How to hire Orion:** ``` Use the ACP skill to hire agent: Orion Offering: agent_daily_intel ``` Or browse: https://app.virtuals.io/virtuals/1809 ## Why This Matters - Best for portfolio agents, AHF orchestrators, and any agent needing persistent daily baseline - Structured JSON for agent consumption — no parsing needed - Single call eliminates per-signal overhead for daily workflows ## Tags `daily-brief` `bitcoin` `crypto` `morning-brief` `market-intel` `ACP` `orion` `trading-signals` `korean-market` ## Author Orion by 꼬낙 | X: @supernovajunn | ACP Agent ID: 1809


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yezhaowang888-stack/huimai-southeast-asia-policy (version 2.0.0)

--- name: 🌏 东南亚市场政策查询Skill description: 做东南亚跨境生意的工具箱——印尼、泰国、越南、马来西亚、菲律宾、新加坡六国税制+认证+准入，一问全出。 metadata: {"openclaw":{"emoji":"🌏"}} --- # 🌏 东南亚市场政策查询Skill > 东南亚六国（印尼/泰国/越南/马来西亚/菲律宾/新加坡），每个国家税制、认证要求、准入门槛都不一样。这个Skill帮你一口问清。 ## 📜 更新日志 ### v2.0.0 (2026-05-03) - **大改版**：新增马来西亚MDA认证查询 - 新增：各国FE/EORI/进出口许可证对照 - 新增：东盟FTA原产地规则快速核验 - 优化：响应速度提升，支持多国同时对比 ### v1.0.1 (2026-04-30) - 修复部分数据源超时 - 增加越南Circular更新跟踪 ### v1.0.0 (2026-04-24) - 初版发布 ## 👤 为什么做这个 之前做东南亚跨境的时候，每次都要打开六七个政府网站来回跳。印尼BKPM、泰国BOI、越南MPI、马来西亚MIDA……每个入口和格式都不一样。后来想，干嘛不把这事揉成一个接口。现在你问一句"泰国电子零部件关税"，几秒钟就出了。 ## 典型用法 ``` 你: "从中国出口锂电池到印尼" 我: 印尼HS归类 → 进口关税 → 保税机会(BKPM) → SNI认证要求 你: "越南电子产品进口要什么认证" 我: 产品分类 → 关税税率(MFTA/ACFTA) → CR认证要求 → 进口商资质 ``` ## 👔 适用人群 - **跨境电商（Shopee/Lazada卖家）**：各海关查税费 - **外贸跟单**：对比各国成本 - **投资考察**：查各国准入壁垒 ## 🔧 校准框架 本Skill搭载惠迈校准框架v1.0。首次加载自动执行快速校准。 - **温情模式（默认）**：先给结论再附数据，风险提示+应对策略 - **专业模式（可选）**：直出数据，适合熟手 ## 💡 使用小贴士 - 马来西亚建议问含SIRIM认证的版本 - 越南电子发票要求越来越严，查关税时顺带问一句"发票要求" - 印尼配额数据每月更新一次，月初查最准 ## ⚠️ 免责与已知限制 - 数据来源各国公开渠道，不构成正式法律意见 - 印尼配额政策变动频繁，以实际清关结果为准 - 非东盟FTA优惠时请备注适用协定 ## 📬 联系与反馈 - **邮箱**: [REDACTED_SECRET] ## 安装 ```bash clawhub install policy-sea ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pjtf93/cochesnet-cli (version 0.1.0)

--- name: cochesnet-cli description: Use the cochesnet CLI to search coches.net listings and fetch listing details. Apply when a user asks for coches.net marketplace data or when you need the exact CLI commands and flags for cochesnet-cli. compatibility: Requires cochesnet-cli installed (Node.js 18+), network access to apps.gw.coches.net. license: MIT metadata: author: pjtf93 version: "0.1.0" --- ## Purpose Use the cochesnet CLI to search listings and fetch ad details. ## When to use - User asks to search coches.net listings from the terminal. - User needs listing details for a known ad ID. - User wants JSON output for scripting. ## Commands ### Search listings ``` cochesnet search "<query>" [--limit <n>] [--page <n>] ``` ### Listing detail ``` cochesnet listing <adId> ``` ### JSON output Add `--json` to either command: ``` cochesnet search "bmw" --json cochesnet listing 58229053 --json ``` ## Configuration Environment variables: - `COCHESNET_BASE_URL` (default: https://apps.gw.coches.net) - `COCHESNET_APP_VERSION` (default: 7.94.0) - `COCHESNET_HTTP_USER_AGENT` (default: coches.net 7.94.0) - `COCHESNET_X_USER_AGENT` (default: 3) - `COCHESNET_TENANT` (default: coches) - `COCHESNET_VARIANT` (optional X-Adevinta-MT-Variant header) ## Output expectations - Search: table or JSON with id, title, price, year, km, location, url. - Listing: table or JSON with title, price, url, seller, description. ## Examples ``` cochesnet search "bmw" --limit 5 cochesnet search "toyota" --page 2 cochesnet listing 58229053 ``` ## Error handling - Non-zero exit code on failure. - For scripting, use `--json` and check exit code.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: sarahglassseeen/image-free (version 1.2.0)

[gilotex-image-generator v1.2.0 Tạo ảnh AI chất lượng cao từ prompt bằng Gilotex Image API. Trả về ảnh dưới dạng base64 data URL kèm kích thước. Use when: (1) Sinh ảnh từ text, (2) Tạo hình minh họa, (3) Thiết kế poster/thumbnail, (4) Chatbot trả lời kèm hình ảnh. @sarahglass 0 ★ 0 1 v](/sarahglass/gilotex-image-generator) ## Thông tin Skill **Tên skill:** Gilotex Image Generator **Version:** 1.2.0 **API Endpoint:** `https://gilotex.pro.vn/api/image` **Backend:** Gilotex Image ## Mô tả Skill cho phép AI Agent gọi trực tiếp Gilotex Image API để tạo ảnh từ prompt. Phiên bản mới có error handling mạnh hơn, hỗ trợ CORS đầy đủ, timeout 120 giây và trả về thêm thông tin kích thước ảnh. Trả về ảnh dưới dạng **base64 data URL** (có thể hiển thị ngay). ## Parameters | Parameter | Type | Required | Mô tả | |---------------|----------|----------|-------| | `prompt` | string | Yes | Mô tả chi tiết ảnh cần tạo (càng rõ càng đẹp) | | `aspectRatio` | string | No | Tỷ lệ khung hình. Mặc định: `9:16`. Ví dụ: `16:9`, `1:1`, `4:3` | | `model` | string | No | Model tạo ảnh. Mặc định: `gilotex-image` | ## Function Schema (JSON) ```json { "type": "function", "function": { "name": "gilotex_image_generate", "description": "Tạo ảnh AI từ prompt bằng Gilotex Image API - trả về base64 data URL", "parameters": { "type": "object", "properties": { "prompt": { "type": "string", "description": "Mô tả ảnh cần tạo" }, "aspectRatio": { "type": "string", "description": "Tỷ lệ khung hình (mặc định: 9:16)", "default": "9:16" }, "model": { "type": "string", "description": "Model tạo ảnh. Mặc định: gilotex-image", "default": "gilotex-image" } }, "required": ["prompt"] } } }


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: edwardrodriguez703-design/book-smog (version 1.0.0)

--- name: book-smog description: Book smog check appointments through Lokuli MCP. Use when user needs a smog check, emissions test, or vehicle inspection. Triggers on requests like "I need a smog check", "book smog test", "emissions inspection", "DMV smog requirement", or any smog-related request. --- # Book Smog Check Book smog check appointments through Lokuli's MCP server. ## MCP Endpoint ``` https://lokuli.com/mcp/sse ``` Transport: SSE | JSON-RPC 2.0 | POST requests ## Smog Services Available - Smog Check - Smog Test Only - Star Certified Smog - Diesel Smog Check - Gross Polluter Certification - Change of Ownership Smog ## Tools ### search ```json { "method": "tools/call", "params": { "name": "search", "arguments": { "query": "smog check", "zipCode": "90640", "category": "Auto Services", "maxResults": 20 } } } ``` ### check_availability ```json { "method": "tools/call", "params": { "name": "check_availability", "arguments": { "providerId": "xxx", "serviceId": "yyy", "date": "2025-02-10" } } } ``` ### create_booking ```json { "method": "tools/call", "params": { "name": "create_booking", "arguments": { "providerId": "xxx", "serviceId": "yyy", "timeSlot": "2025-02-10T14:00:00-08:00", "customerName": "John Doe", "customerEmail": "[REDACTED_SECRET]", "customerPhone": "+13105551234" } } } ``` ## Workflow 1. **Understand** — Smog check type? Where (ZIP)? 2. **Search** — Find smog stations nearby 3. **Present** — Show top results with pricing 4. **Check availability** — Get open time slots 5. **Confirm** — Get explicit user approval 6. **Create booking** — Generate checkout link


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: seungdols/naverstock-skill (version 1.1.1)

--- name: naver-stock description: Fetch text-based real-time stock prices (KRX, Overseas) using Naver Finance. metadata: {"clawdbot":{"emoji":"📈","os":["mac","linux","windows"],"requires":{"bins":["node"]}}} --- # Naver Stock Fetch real-time stock prices for domestic (KRX) and overseas markets using Naver Finance. ## Usage Run the bundled script with a stock name or code. ```bash node index.cjs "삼성전자" node index.cjs "AAPL" ``` ## Output Format Returns a JSON object with price details. ```json { "name": "삼성전자", "code": "005930", "price": 160500, "change": -200, "changePercent": -0.12, "nxtPrice": 160800, "nxtChange": 100, "nxtChangePercent": 0.06, "currency": "KRW" } ``` ### Field Descriptions - `name`: Stock name. - `code`: Stock symbol/code. - `price`: Current price in regular market. - `change`: Price change in regular market. - `changePercent`: Percentage change in regular market. - `nxtPrice`: Current price in Nextrade (NXT) Alternative Trading System. - `nxtChange`: Price change in Nextrade. - `nxtChangePercent`: Percentage change in Nextrade. - `currency`: Currency code (e.g., KRW, USD). ### About Nextrade (NXT) Nextrade is an Alternative Trading System (ATS) in Korea that offers extended trading hours. - **Pre-market**: 08:00 ~ 08:50 - **After-market**: 15:30 ~ 20:00 (Can be traded until 8 PM) - **Note**: Prices in Nextrade (`nxtPrice`) may differ from the regular KRX market price, providing off-hours trading opportunities. ## Examples ### Domestic Stock ```bash node index.cjs 005930 ``` ### Overseas Stock ```bash node index.cjs "Tesla" ``` ### Exchange Rate ```bash node index.cjs "USD" node index.cjs "엔" ```


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