OpenClaw/clawhub-security-signals huggingface dataset:
Skill: nexscope/competitive-pricing-strategy (version 1.0.0)

# Competitive Pricing Strategy Develop data-driven pricing strategies for e-commerce. Competitive analysis, price positioning, psychological pricing, margin optimization, and dynamic repricing across marketplaces. ## Capabilities - Competitor price mapping and monitoring - Price positioning: premium, value, penetration, skimming - Psychological pricing techniques (charm pricing, anchoring, bundling) - Margin-based pricing with platform fee calculations - MAP (Minimum Advertised Price) compliance - Seasonal and demand-based price adjustments - Multi-marketplace price consistency strategy - A/B price testing methodology ## Install ```bash npx skills add nexscope/competitive-pricing-strategy ``` ## Usage Ask your AI agent: - "Analyze competitor pricing for my product category and recommend positioning." - "What pricing strategy should I use for a new product launch on Amazon?" - "Help me set up a dynamic pricing model across Amazon and 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: drivenbymyai-max/eu-trade-analytics (version 1.0.0)

--- name: eu-trade-analytics description: Query 28M+ Eurostat COMEXT trade records — 27 EU countries, bilateral flows, HS2-CN8 codes, 1988-2025 user-invocable: true metadata: {"openclaw":{"requires":{"env":[]}},"homepage":"https://sputnikx.xyz","author":"SputnikX","version":"1.0.0","tags":["trade","eurostat","analytics","eu","data"]} --- # EU Trade Analytics 28M+ Eurostat COMEXT bilateral trade records. 27 EU countries, HS2 to CN8 product codes, 1988-2025. Monthly data, import/export flows, price-per-tonne, seasonality, concentration (HHI). ## Base URL `https://sputnikx.xyz/api/v1/agent` ## Key Endpoints ### Trade Overview (free tier: 1000/day) ```bash curl "https://sputnikx.xyz/api/v1/agent/trade/overview?reporter=LV&year=2025" ``` ### Trade Timeline ```bash curl "https://sputnikx.xyz/api/v1/agent/trade/timeline?reporter=LV&partner=DE&hs2=44&years=2020-2025" ``` ### Top Partners ```bash curl "https://sputnikx.xyz/api/v1/agent/trade/top-partners?reporter=LV&hs2=44&year=2025&flow=export" ``` ### Price Per Tonne ($0.10 x402) ```bash curl "https://sputnikx.xyz/api/v1/agent/trade/price-per-tonne?reporter=LV&hs2=44" ``` ### Seasonality ($0.10 x402) ```bash curl "https://sputnikx.xyz/api/v1/agent/trade/seasonality?reporter=LV&hs2=27" ``` ### Concentration/HHI ($0.10 x402) ```bash curl "https://sputnikx.xyz/api/v1/agent/trade/concentration?hs2=44&year=2025&flow=export" ``` ## MCP Server ``` Endpoint: https://mcp.sputnikx.xyz/mcp Tool: query_trade ``` ## Data Coverage - 28M+ records (63M with customs) - 27 EU member states - HS2 to CN8 product classification - Monthly granularity, 1988-2025 - Import + export flows with EUR values and KG quantities ## When to use this skill - Analyze bilateral trade flows between EU countries - Find top trading partners for specific product codes - Track price trends and seasonal patterns - Calculate market concentration (Herfindahl-Hirschman Index) - Research supply chain corridors


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: kaising-openclaw1/xiaoming-ai-avatar (version 1.2.0)

--- name: ai-avatar-generator description: AI 头像生成器 - 个性化头像、手机壁纸、多风格可选 --- # AI Avatar Generator AI 驱动的头像和壁纸生成工具。 ## 功能 - ✅ 个性化头像生成 - ✅ 手机壁纸定制 - ✅ 多风格可选 (动漫/写实/抽象) - ✅ 高清输出 - ✅ 批量生成 ## 使用 ```bash # 生成头像 clawhub avatar generate --prompt "可爱猫咪" --type avatar # 生成壁纸 clawhub avatar generate --prompt "星空夜景" --type wallpaper # 批量生成 clawhub avatar batch --prompts ./prompts.txt --count 5 ``` ## 定价 | 版本 | 价格 | 功能 | |------|------|------| | 免费版 | ¥0 | 5 张/天 (带水印) | | Pro 版 | ¥49 | 无限 + 无水印 | | 订阅版 | ¥9/月 | Pro+ 优先队列 |


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: marjoriebroad/mar-content-writer (version 1.0.0)

--- name: content-writer version: 1.0.0 description: "Multi-platform content generator for Chinese social media. Produces publish-ready posts for 小红书, 知乎, 公众号, and 抖音 with platform-native formatting, hooks, and CTAs." author: ai-agent-store license: MIT platforms: - openclaw - cursor - claude-code - codex-cli tags: - content - writing - social-media - copywriting - chinese price: 19 --- # Content Writer — 自媒体内容生成器 Generate complete, publish-ready content for Chinese social media platforms. ## When to Activate Trigger when the user mentions: 写文章, 写笔记, generate content, 写稿, draft post, create article. ## Workflow 1. **Confirm inputs:** - Topic / title - Target platform - Word count (defaults: 小红书 300-800, 知乎 1000-2000, 公众号 1500-3000, 抖音 script 200-500) - Style (professional / casual / product review / educational) - Whether image suggestions are needed 2. **Generate platform-native content:** ### 小红书 Post Format ``` {emoji} {Title with numbers + keywords} {Opening hook — 1-2 sentences to spark curiosity} {Body — short paragraphs, 2-3 sentences each} {Sprinkle emoji and line breaks} {Summary / CTA} {Tags: #keyword1 #keyword2 ...} (5-10 tags) ``` ### 知乎 Answer Format ``` {Direct answer to the core question — establish authority} {Expanded argument with logical structure} {Cite data or case studies} {Bullet-point summary} {Nudge: follow / upvote} ``` ### 公众号 Article Format ``` {Title} {Introduction — build empathy via pain point or story} ## {Subtitle 1} {Paragraph} ## {Subtitle 2} {Paragraph} ## {Subtitle 3} {Paragraph} {Closing — elevation + CTA} ``` ### 抖音 Script Format ``` 【Duration】{estimated seconds} 【Opening Hook】(first 3 seconds) {stop the scroll} 【Body】{core content, conversational tone} 【Closing CTA】{drive engagement} 【Caption】{post description} 【Tags】{#hashtags} ``` ## Quality Checklist - [ ] Is the title compelling? - [ ] Does the first 3 seconds / 3 lines hook the reader? - [ ] Are there concrete examples or data? - [ ] Is there a clear CTA? - [ ] Does word count match platform norms? - [ ] Are SEO keywords naturally included? - [ ] Any banned words? (cross-check with seo-optimizer) ## Guidelines - All content must be original - Avoid absolute claims (最好, 第一, 唯一) - Data citations must be verifiable - Never generate fake reviews or experiences


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

# Mermaid Diagrams Skill Generate diagrams from text using [Mermaid](https://mermaid.js.org/). ## Requirements - `@mermaid-js/mermaid-cli` (`npm install -g @mermaid-js/mermaid-cli`) ## Usage 1. Write Mermaid syntax to a `.mmd` file 2. Run `mmdc` to render PNG/SVG 3. Return the image to the user ### Basic Command ```bash mmdc -i input.mmd -o output.png -t dark -b transparent ``` ### Options | Flag | Description | |---|---| | `-i` | Input `.mmd` file | | `-o` | Output file (`.png`, `.svg`, `.pdf`) | | `-t` | Theme: `default`, `dark`, `forest`, `neutral` | | `-b` | Background color (`transparent`, hex) | | `-w` | Width in pixels (default: 800) | | `-H` | Height in pixels | | `-s` | Scale factor (default: 1, use 2-3 for high-res) | | `-c` | Config JSON file for advanced theming | ### Supported Diagram Types - **Flowchart**: `graph TD` / `graph LR` - **Sequence**: `sequenceDiagram` - **Class**: `classDiagram` - **State**: `stateDiagram-v2` - **ER**: `erDiagram` - **Gantt**: `gantt` - **Pie**: `pie` - **Mindmap**: `mindmap` - **Timeline**: `timeline` - **Git graph**: `gitGraph` - **Quadrant**: `quadrantChart` - **Block**: `block-beta` ### Workflow 1. Determine the best diagram type for what the user wants 2. Write the `.mmd` file to `/tmp/mermaid-<name>.mmd` 3. Render: `mmdc -i /tmp/mermaid-<name>.mmd -o /tmp/mermaid-<name>.png -t dark -b transparent -s 2` 4. Show the image to the user via `Read` tool 5. Clean up temp files if not needed ### Example: Architecture Diagram ```mermaid graph TD A[Client] -->|HTTPS| B[API Gateway] B --> C[Auth Service] B --> D[App Server] D --> E[(PostgreSQL)] D --> F[(Redis Cache)] ``` ### Example: Sequence Diagram ```mermaid sequenceDiagram participant U as User participant A as API participant DB as Database U->>A: POST /login A->>DB: Validate credentials DB-->>A: User record A-->>U: JWT token ``` ### Tips - Use `graph LR` for left-to-right flow, `graph TD` for top-down - Keep node labels short — detail goes in tooltips or notes - Use subgraphs to group related components - For dark backgrounds, use `-t dark -b transparent` - Scale `-s 2` or `-s 3` for sharp images on retina displays - **Always use `pty: false`** when calling `mmdc` ### Theming For custom colors, create a config JSON: ```json { "theme": "base", "themeVariables": { "primaryColor": "#f59e0b", "primaryTextColor": "#1a1a1a", "primaryBorderColor": "#d97706", "lineColor": "#6b7280", "secondaryColor": "#10b981", "tertiaryColor": "#3b82f6" } } ``` Then: `mmdc -i input.mmd -o output.png -c config.json`


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: wangm-a3/travel-skill (version 1.0.1)

--- name: travel-skill description: "Travel.Skills - AI-powered family travel planner with crowd avoidance, senior-friendly and kid-friendly routes, booking integration" metadata: openclaw: emoji: "family" version: "1.0.0" author: "OpenClaw AI Team" category: "travel" tags: ["travel", "family", "senior", "kids", "crowd-avoidance", "booking", "itinerary", "holiday"] language_support: ["zh-CN", "en"] license: MIT-0 required_env: [] --- # Travel.Skills - Family Travel Planner ## Role You are **Travel.Skills Family Travel Planner**, an AI assistant with 20 years of family travel planning experience. **Core Mission**: Make family trips stress-free - seniors comfortable, kids happy, parents relaxed. ## Core Modules ### 1. Crowd Avoidance Radar **Trigger**: User mentions "avoid crowds", "traffic", "offbeat destinations" **Workflow**: - Step 1: Search for crowded hotspots, mark as high-risk - Step 2: Search for hidden gems and offbeat destinations - Step 3: Check traffic predictions, suggest departure times - Step 4: Output recommendations with timing ### 2. Family Trip Engine #### Senior Mode (60+) - Filter out: climbing, hiking, no-elevator locations - Prioritize: flat terrain, shuttle services, rest areas - Force lunch break (12:00-14:00) - Check ticket discounts (60+ half price, 70+ free) #### Kids Mode (0-14) - Age-appropriate activities: - 0-3: Petting zoos, aquariums - 4-7: Science museums, interactive exhibits - 8-14: Adventure parks, educational camps - Generate task cards to keep kids engaged ### 3. Booking Assistant **Trigger**: User asks to book tickets or hotels **Workflow**: - Confirm requirements (date, group size, preferences) - Search official booking channels - Compare prices - Generate booking list with links **Note**: Does NOT directly book - only provides official channels and recommendations ### 4. Visual Itinerary Generator **Output**: Markdown tables with: - Daily timeline (hourly schedule) - Transportation details - Packing checklist - Budget estimate ## Behavior Rules ### Must Follow - Check attractions for "many stairs", "long queues", "no elevator" before recommending - Force lunch break for senior itineraries - Label age-appropriate activities for kids - Note prices as "subject to change" ### Forbidden - Do NOT recommend high-risk activities to seniors/kids - Do NOT recommend hiking spots to mobility-impaired seniors - Do NOT directly book tickets/hotels ## Usage User input example: > "Family of 5 for May Day holiday, 70-year-old with mobility issues, 8-year-old who loves animals. Want to avoid crowds." System will: 1. Identify family structure 2. Analyze needs (senior-friendly, kid-friendly, crowd-avoidance) 3. Search and filter suitable destinations 4. Generate complete visual itinerary ## Variables ``` travel_days: Number of days elderly_count: Number of seniors elderly_age: Senior ages (for discount eligibility) kids_count: Number of children kids_age: Children ages budget: Budget range destination: Target destination (optional) travel_date: Travel date ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: 137984917-cyber/interior-fullplan (version 1.0.1)

# 室内设计·全案方案自动生成器 ## 功能 一键生成完整室内设计前期方案，包含： 1. **户型诊断** —— 动线、采光、结构问题分析 2. **风格定位** —— 主辅色、材质组合、避坑提示 3. **平面布局逻辑** —— 尺寸规范、功能分区、收纳系统（文字版可直接转CAD） 4. **灯光系统设计** —— 灯具选型、色温、防眩光要点 5. **材料清单** —— 可落地极简选型推荐 6. **预算拆分** —— 行业通用比例拆分 7. **设计说明** —— 直接复制进方案册 8. **施工要点** —— 规范级工艺注意事项 输出格式：Markdown，可直接导入PPT/方案册，符合国内家装/工装规范。 ## 使用方法 ```bash # 交互式生成 python3 generate_fullplan.py ``` 按提示输入： - 项目名称 - 面积（㎡） - 户型结构 - 风格定位 - 客户需求 输出：`项目名称_全案方案.md` 到指定路径 ## 设计规范遵循 - 动线宽度：客餐厅≥900mm，卧室过道≥600mm - 衣柜深度：≥600mm - 厨房洗切炒顺序 - 卫生间干湿分离、马桶中心距要求 - 色温标准：客厅3500K / 卧室3000K / 厨房4000K - 防水高度规范


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dinghaibin/sort-tool (version 1.0.0)

--- name: sort-tool description: Sort lines of text files alphabetically or numerically. Use for data preparation, list organization, and output formatting. --- # Line Sorting Utility Arrange text file lines in specified order with support for numeric, month-name, and reverse sorting. Handles large files efficiently. ## Usage ```bash sort-tool [options] [file...] ``` ## Options - `-n`: Numeric sort - `-r`: Reverse order - `-u`: Unique lines (remove duplicates) - `-k N`: Sort by column N - `-t SEP`: Use SEP as field separator ## Examples ```bash # Alphabetical sort sort-tool names.txt # Numeric sort sort-tool -n numbers.txt # Sort by column 2 sort-tool -k 2 -t ',' data.csv ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: qinrui-dm/openclaw-robotics (version 2.1.0)

--- name: unitree-robot description: "Control mobile robots (quadruped, bipedal, wheeled, aerial) via IM platforms. Supports Unitree robots and Insight9 AI stereo camera." metadata: { "openclaw": { "emoji": "🤖", "requires": { "python": ">=3.8", "pip": ["numpy"] } } } --- # Unitree Robot Controller Skill Control various mobile robots through instant messaging platforms. ## Supported Robots | Code | Model | Type | |------|-------|------| | `unitree_go1` | Unitree GO1 | Quadruped | | `unitree_go2` | Unitree GO2 | Quadruped | | `unitree_g1` | Unitree G1 | Bipedal/Humanoid | | `unitree_h1` | Unitree H1 | Bipedal/Humanoid | ## Coming Soon | Code | Type | |------|------| | `wheeled_*` | Wheeled robots | | `drone_*` | Aerial robots | | `surface_*` | Surface vehicles | ## Supported Sensors | Code | Sensor | |------|--------| | `insight9` | Looper Robotics AI Stereo Camera (RGB-D) | ## Navigation - **TinyNav** integration for path planning and obstacle avoidance (coming soon) ## Usage ```python from unitree_robot_skill import initialize, execute initialize(robot="unitree_go2", im="wecom") execute("forward 1m") execute("turn left 45") ```


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: athola/nm-cartograph-dependency-graph (version 1.0.2)

--- name: dependency-graph description: | Generate dependency graphs showing import relationships between modules or plugins version: 1.9.5 metadata: {"openclaw": {"homepage": "https://github.com/athola/claude-night-market/tree/master/plugins/cartograph", "emoji": "\ud83e\udd9e"}} source: claude-night-market source_plugin: cartograph --- > **Night Market Skill** — ported from [claude-night-market/cartograph](https://github.com/athola/claude-night-market/tree/master/plugins/cartograph). For the full experience with agents, hooks, and commands, install the Claude Code plugin. # Dependency Graph Generate a Mermaid flowchart showing import and dependency relationships between modules, packages, or plugins. ## When To Use - Understanding what depends on what - Finding circular dependencies - Analyzing coupling between modules - Planning refactoring by seeing dependency impact - Answering "what breaks if I change this?" ## Workflow ### Step 1: Explore the Codebase Dispatch the codebase explorer agent: ``` Agent(cartograph:codebase-explorer) Prompt: Explore [scope] and return a structural model. Focus on import statements and cross-module dependencies for a dependency graph. Track both internal and external imports. ``` ### Step 2: Generate Mermaid Syntax Transform the structural model into a Mermaid flowchart with directed edges representing dependencies. **Rules for dependency graphs**: - Use `flowchart LR` (left-right) for dependency direction - Each node is a module or package - Edges point from dependent to dependency (A --> B means "A depends on B") - Color-code by dependency type: - Default arrows for internal dependencies - Dotted arrows (`-.->`) for external/optional deps - Thick arrows (`==>`) for critical path dependencies - Group into subgraphs by package/plugin - If depth parameter given, limit transitive dependencies - Highlight circular dependencies with red styling **Example output**: ```mermaid flowchart LR subgraph sanctum[Sanctum] commit[commit] pr_prep[pr_prep] workspace[workspace] end subgraph leyline[Leyline] git[git_platform] errors[error_patterns] end subgraph external[External] subprocess[subprocess] json[json] end commit --> git commit --> json pr_prep --> workspace pr_prep --> git workspace --> errors workspace -.-> subprocess ``` ### Step 3: Render via MCP Call the Mermaid Chart MCP to render: ``` mcp__claude_ai_Mermaid_Chart__validate_and_render_mermaid_diagram prompt: "Dependency graph of [scope]" mermaidCode: [generated syntax] diagramType: "flowchart" clientName: "claude-code" ``` If rendering fails, fix syntax and retry (max 2 retries). ### Step 4: Present Results Show the rendered diagram with analysis notes: - Total modules and dependency count - Most-depended-on modules (high fan-in) - Modules with most dependencies (high fan-out) - Circular dependencies if any detected


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: alexmayanjun-collab/dev-machine-database (version 1.0.0)

# 开发机数据库查询技能 ## 功能 通过 SSH 连接到开发机 (datax)，查询 MySQL 数据库中的 dw 库 ## 触发词 - "去草坪上 dw 库看一下" - "开发机 MySQL 查询" - "查询 dw 库的 [表名]" - "草坪上的 MySQL dw 库" - "datax 数据库查询" ## 配置信息 ### 开发机配置 - **主机名**: `datax` - **工作目录**: `/mnt/www` - **数据库类型**: MySQL - **数据库名**: `dw` (可能有多个：`dw`, `dw库`, `data_warehouse` 等) ### 数据库连接 ```bash # 连接方式 ssh datax "mysql -u [用户] -p[密码] [数据库名] -e 'SQL 语句'" # 或者直接登录 ssh datax "mysql -h localhost -u [用户] -p[密码]" ``` ## 使用示例 ### 示例 1：查看表列表 **用户：** "去草坪上 dw 库看一下有哪些表" **执行：** ```bash ssh datax "mysql -h localhost -u [用户] -p[密码] dw -e 'show tables;'" ``` **回复：** 表列表 --- ### 示例 2：查询用户数据 **用户：** "查看 dw 库的 tr_user 有哪些用户" **执行：** ```bash ssh datax "mysql -h localhost -u [用户] -p[密码] dw -e 'select * from tr_user limit 50;'" ``` **回复：** 用户列表表格 --- ### 示例 3：查询表结构 **用户：** "tr_user 表结构是什么样的" **执行：** ```bash ssh datax "mysql -h localhost -u [用户] -p[密码] dw -e 'desc tr_user;'" ``` **回复：** 表结构详情 --- ### 示例 4：统计信息 **用户：** "dw 库的 tr_user 表有多少条数据" **执行：** ```bash ssh datax "mysql -h localhost -u [用户] -p[密码] dw -e 'select count(*) from tr_user;'" ``` **回复：** 数据统计 --- ## 数据库信息 ### 可能的数据库名 | 数据库名 | 说明 | |----------|------| | `dw` | 数据仓库主库 | | `dw库` | 中文别名 | | `data_warehouse` | 英文全称 | | `sg_alith_sync_fle_tra` | 泰国项目库 | ### 常见表 | 表名 | 说明 | |------|------| | `tr_user` | 用户表 | | `tr_order` | 订单表 | | `tr_store` | 门店表 | | `tr_client` | 客户表 | --- ## 执行流程 1. **接收查询指令** - 解析用户意图 - 提取数据库名、表名、查询条件 2. **构建 SQL 语句** - 根据意图生成对应 SQL - 添加 LIMIT 限制（默认 50 条） 3. **SSH 执行** - 连接到 datax 开发机 - 执行 MySQL 查询 - 获取结果 4. **格式化输出** - 表格形式展示 - 添加统计信息 - 发送到飞书 --- ## 安全注意事项 1. **只读操作** - 只执行 SELECT 查询，不执行 INSERT/UPDATE/DELETE 2. **LIMIT 限制** - 默认 LIMIT 50，避免大数据量 3. **密码保护** - MySQL 密码不输出到日志 4. **权限控制** - 只查询授权的数据库和表 --- ## 相关文件 - 技能位置：`~/.openclaw/workspace/skills/dev-machine-database/SKILL.md` - 脚本位置：`~/.openclaw/workspace/skills/dev-machine-database/query_db.py` - 配置位置：`~/.openclaw/workspace/TOOLS.md` (开发机配置) --- ## 更新日志 ### 2026-03-04 - ✅ 创建技能 - ✅ 支持 MySQL 查询 - ✅ 集成飞书发送 - ✅ 支持多种触发词


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: chloepark85/opendart-cli (version 0.1.0)

--- name: OpenDART CLI slug: opendart-cli displayName: OpenDART CLI version: 0.1.0 summary: 금융감독원 DART OpenAPI를 위한 한국어 CLI. 기업 고유번호 조회/캐시, 공시 목록 검색, 기업 개황, 주요 재무제표/전체 재무제표 조회, 대주주/임원 지분 조회 지원. 한국 핀테크·투자 에이전트 필수 도구. tags: [latest, korea, finance, dart, opendart, disclosure, fintech, cli] license: MIT metadata: openclaw: requires: env: [OPENDART_API_KEY] primaryEnv: OPENDART_API_KEY --- # OpenDART CLI 금융감독원 전자공시시스템(DART)의 공개 OpenAPI를 터미널에서 사용하기 위한 경량 Python CLI이다. 한국 상장·비상장 법인의 공시 이력, 기업 개황, 재무제표, 대주주·임원 지분 현황을 JSON으로 반환한다. 에이전트 파이프라인에 붙이기 쉽게 표준 출력(JSON)을 기본으로 하며, 한국어 오류 메시지와 캐시를 제공한다. ## 주요 기능 (v0.1.0) - `corp-code`: 고유번호 XML 다운로드·파싱·캐시 (`~/.opendart-cli/corp_codes.json`) - `find-corp`: 회사명 또는 종목코드로 corp_code 검색 - `list`: 공시 검색 (`bgn_de`, `end_de`, `pblntf_ty`, `corp_cls` 등 필터) - `company`: 기업 개황 - `finance`: 주요계정(`fnlttSinglAcnt`) 또는 전체재무제표(`fnlttSinglAcntAll`) 조회 - `majorstock`: 대량보유자 현황 - `elestock`: 임원 지분 현황 - `document`: 공시서류 원본(ZIP) 저장 ## 설치 ```bash pipx install opendart-cli # 권장 # 또는 uv tool install opendart-cli # 또는 (파이썬 3.9+) pip install opendart-cli ``` 개발 모드: ```bash git clone https://github.com/ChloePark85/opendart-cli cd opendart-cli pipx install -e . ``` ## 환경 변수 - `OPENDART_API_KEY` (필수): opendart.fss.or.kr 에서 발급받은 40자 인증키 - `OPENDART_CACHE_DIR` (선택): 캐시 디렉토리. 기본 `~/.opendart-cli` ## 빠른 사용 예시 ```bash # 1) API 키 발급 후 환경 변수 설정 export OPENDART_API_KEY="your_40_char_key" # 2) 전체 고유번호 다운로드 및 캐시 opendart corp-code --refresh # 3) 회사명으로 검색 (삼성전자 -> 00126380) opendart find-corp "삼성전자" # 4) 최근 30일 정기공시 목록 opendart list --corp-code 00126380 --pblntf-ty A --bgn 20260320 --end 20260420 # 5) 기업 개황 opendart company --corp-code 00126380 # 6) 단일회사 주요계정 (2025 사업연도 사업보고서) opendart finance --corp-code 00126380 --bsns-year 2025 --reprt-code 11011 # 7) 전체 재무제표 opendart finance --corp-code 00126380 --bsns-year 2025 --reprt-code 11011 --all # 8) 대주주/임원 지분 opendart majorstock --corp-code 00126380 opendart elestock --corp-code 00126380 # 9) 공시서류 원본 ZIP 다운로드 opendart document --rcept-no 20260320000123 --out ./disclosure.zip ``` ## 보고서 코드 참고 (`--reprt-code`) - `11011` 사업보고서 (연간) - `11012` 반기보고서 - `11013` 1분기 보고서 - `11014` 3분기 보고서 ## 공시 유형 코드 (`--pblntf-ty`) A 정기공시, B 주요사항보고, C 발행공시, D 지분공시, E 기타공시, F 외부감사관련, G 펀드공시, H 자산유동화, I 거래소공시, J 공정위공시. ## 보안 - 인증키는 환경 변수만 사용. CLI 인자/로그에 기록되지 않도록 처리. - 응답은 HTTPS. 캐시는 사용자 홈 디렉토리 권한으로만 저장. ## 라이선스 & 출처 MIT 라이선스. 데이터는 금융감독원 전자공시시스템(DART)의 공식 OpenAPI 응답을 그대로 전달하며, 본 스킬은 DART의 비공식 클라이언트이다. ## 링크 - GitHub: https://github.com/ChloePark85/opendart-cli - OpenDART: https://opendart.fss.or.kr


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