OpenClaw/clawhub-security-signals huggingface dataset:
Skill: sunshine-del-ux/cloud-infra-automation (version 1.0.0)

# Cloud Infrastructure Automation Automate cloud infrastructure with IaC. ## Features ### Multi-Cloud Support - AWS - Google Cloud Platform - Azure ### Infrastructure as Code - Terraform templates - Ansible playbooks - CloudFormation ### Automation - Server provisioning - Configuration management - Deployment pipelines ## Quick Start ```bash # Initialize AWS ./cloud.sh init aws # Create infrastructure ./cloud.sh apply prod # Destroy ./cloud.sh destroy prod ``` ## Templates - Web application - Database setup - Kubernetes cluster - Serverless functions ## Requirements - Terraform - Ansible - AWS/GCP/Azure CLI ## Author Sunshine-del-ux


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

--- name: image-processor description: Process and convert images with resize, crop, compress, and format conversion. Use when user needs to batch resize photos, convert image formats, compress images for web, create thumbnails, or apply filters to images. --- # Image Processor Process and convert images with resize, crop, compress, and format conversion. ## Quick Start ```bash # Resize an image python scripts/process.py input.jpg --resize 800x600 --output output.jpg # Convert format python scripts/process.py input.png --format jpg --output output.jpg ``` ## Usage ```bash python scripts/process.py INPUT [OPTIONS] Options: --output PATH Output file path --resize WxH Resize to dimensions --scale PERCENT Scale by percentage --crop WxH+X+Y Crop to dimensions --format FORMAT Convert format: jpg, png, webp, gif --quality QUALITY JPEG quality (1-100) --thumbnail SIZE Create thumbnail --grayscale Convert to grayscale --blur RADIUS Apply blur --rotate DEGREES Rotate image ``` ## Examples ```bash # Resize to 800px width python scripts/process.py photo.jpg --resize 800x0 --output small.jpg # Create thumbnail python scripts/process.py photo.jpg --thumbnail 200x200 --output thumb.jpg # Compress for web python scripts/process.py large.jpg --quality 80 --format webp --output optimized.webp # Batch resize for f in *.jpg; do python scripts/process.py "$f" --resize 1200x0 --output "small_$f"; done # Convert to PNG python scripts/process.py input.jpg --format png --output output.png ``` ## Features - Resize (by dimensions or percentage) - Crop - Format conversion (JPG, PNG, WebP, GIF) - Quality/compression control - Thumbnails - Grayscale conversion - Blur filter - Rotation - Batch processing


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: jamesbot-agnt/omie (version 1.0.3)

--- name: omie description: "Omie ERP integration via API. Manage clients, products, orders, invoices (NF-e), financials (contas a receber/pagar), and stock. Use when users ask about ERP data, financials, orders, invoices, stock, or clients from Omie. Also handles webhooks for real-time events." --- # Omie ERP Skill Integração com o Omie ERP via API REST. ## Setup Requer variáveis de ambiente: ```bash export OMIE_APP_KEY="your_app_key_here" export OMIE_APP_SECRET="your_app_secret_here" ``` ## API Client Use o script Python para todas as operações: ```bash python3 skills/omie/scripts/omie_client.py <command> [args] ``` ### Comandos disponíveis #### Clientes ```bash python3 scripts/omie_client.py clientes_listar [pagina] [por_pagina] python3 scripts/omie_client.py clientes_buscar cnpj_cpf=00.000.000/0001-00 python3 scripts/omie_client.py clientes_buscar codigo=1234567 python3 scripts/omie_client.py clientes_detalhar codigo=1234567 ``` #### Produtos ```bash python3 scripts/omie_client.py produtos_listar [pagina] [por_pagina] python3 scripts/omie_client.py produtos_detalhar codigo=1234567 ``` #### Pedidos de Venda ```bash python3 scripts/omie_client.py pedidos_listar [pagina] [por_pagina] python3 scripts/omie_client.py pedidos_detalhar numero=1234 python3 scripts/omie_client.py pedidos_status numero=1234 ``` #### Financeiro ```bash python3 scripts/omie_client.py contas_receber [pagina] [por_pagina] python3 scripts/omie_client.py contas_pagar [pagina] [por_pagina] python3 scripts/omie_client.py resumo_financeiro ``` #### Notas Fiscais ```bash python3 scripts/omie_client.py nfe_listar [pagina] [por_pagina] python3 scripts/omie_client.py nfe_detalhar numero=1234 ``` #### Estoque ```bash python3 scripts/omie_client.py estoque_posicao [pagina] [por_pagina] python3 scripts/omie_client.py estoque_produto codigo=1234567 ``` ## Webhook O Omie pode enviar eventos para um endpoint HTTP. Configurar em: Omie → Configurações → Integrações → Webhooks Eventos suportados: - `pedido.incluido` / `pedido.alterado` - `nfe.emitida` / `nfe.cancelada` - `financas.recebido` / `financas.pago` - `cliente.incluido` / `cliente.alterado` Para iniciar o receptor de webhooks: ```bash python3 scripts/omie_webhook.py --port 8089 ``` ## Limites da API - **Rate limit:** 3 requisições/segundo por app - **Paginação:** máximo 500 registros por página - **Timeout:** 30 segundos


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: drowning-in-codes/hn-crawler-cn (version 1.0.0)

--- name: "hn-crawler" description: "爬取 https://hn.aimaker.dev/ 网站资讯，执行爬取->提取->整理->总结完整流程。Invoke when user wants to crawl news from hn.aimaker.dev or process web content through the full pipeline." --- # HN 资讯爬虫 Skill 本 Skill 用于爬取 https://hn.aimaker.dev/ 网站的资讯内容，并通过完整的处理流程将原始数据转化为结构化的总结报告。 ## 工作流程 整个处理流程分为四个阶段： ``` ┌─────────┐ ┌──────────┐ ┌──────────┐ ┌───────────┐ │ Crawl │ -> │ Extract │ -> │ Organize │ -> │ Summarize │ │ 爬取 │ │ 提取 │ │ 整理 │ │ 总结 │ └─────────┘ └──────────┘ └──────────┘ └───────────┘ ``` ### 1. Crawl（爬取） - **脚本**: `scripts/crawl.py` - **功能**: 使用 HTTP 请求获取网页原始 HTML 内容 - **输出**: `data/raw/hn_aimaker_<timestamp>.html` ### 2. Extract（提取） - **脚本**: `scripts/extract.py` - **功能**: 解析 HTML，提取文章标题、链接、摘要、发布时间等信息 - **输出**: `data/extracted/articles_<timestamp>.json` ### 3. Organize（整理） - **脚本**: `scripts/organize.py` - **功能**: 对提取的数据进行清洗、去重、分类和格式化 - **输出**: `data/organized/articles_organized_<timestamp>.json` ### 4. Summarize（总结） - **脚本**: `scripts/summarize.py` - **功能**: 生成摘要报告，包括热点话题统计、趋势分析等 - **输出**: `data/summary/summary_<timestamp>.md` ## 快速开始 ### 安装依赖 ```bash cd .trae/skills/hn-crawler/scripts pip install -r requirements.txt ``` ### 运行完整流程 ```bash # 方法1：逐个执行 python scripts/crawl.py python scripts/extract.py python scripts/organize.py python scripts/summarize.py # 方法2：一键执行完整流程 python scripts/run_pipeline.py ``` ## 目录结构 ``` .trae/skills/hn-crawler/ ├── SKILL.md # 本文件 ├── scripts/ │ ├── requirements.txt # Python 依赖 │ ├── crawl.py # 爬取脚本 │ ├── extract.py # 提取脚本 │ ├── organize.py # 整理脚本 │ ├── summarize.py # 总结脚本 │ └── run_pipeline.py # 一键运行完整流程 └── data/ # 数据输出目录（自动创建） ├── raw/ # 原始 HTML ├── extracted/ # 提取的 JSON 数据 ├── organized/ # 整理后的数据 └── summary/ # 总结报告 ``` ## 数据格式 ### 提取后的文章格式 (JSON) ```json { "articles": [ { "title": "文章标题", "url": "https://example.com/article", "summary": "文章摘要", "published_at": "2024-01-15T10:30:00", "source": "hn.aimaker.dev", "category": "AI", "score": 150 } ], "metadata": { "crawled_at": "2024-01-15T12:00:00", "total_count": 30 } } ``` ## 配置选项 各脚本支持以下环境变量或命令行参数： - `TARGET_URL`: 目标 URL（默认: https://hn.aimaker.dev/） - `OUTPUT_DIR`: 输出目录（默认: data/） - `TIMEOUT`: 请求超时时间（默认: 30秒） ## 注意事项 1. 请遵守网站的 robots.txt 和爬虫协议 2. 建议设置适当的请求间隔，避免对服务器造成压力 3. 爬取的数据仅供个人学习研究使用


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (HIGH)
Skill: leooooooow/comment-replies (version 1.0.0)

--- name: comment-replies description: Draft short, high-clarity replies for comments, objections, and pre-sale questions. Use when responding to public comments on TikTok, X, Instagram, YouTube, or product pages, especially when replies need to reduce hesitation, answer common questions, and move the conversation to the next step without sounding pushy. --- # Comment Replies Draft replies that remove doubt and keep momentum. ## Workflow 1. Identify the comment type. - product question - trust objection - shipping / price / fit concern - positive interest but unclear next step 2. Infer the real hesitation behind the wording. - trust - relevance - value - logistics 3. Write a short public reply. - answer the concern - keep context clear - open the next step 4. If useful, add a softer alternate version. ## Output format Return: - intent label - primary short reply - softer alternate reply - optional CTA line ## Quality bar - Prefer short public replies over paragraphs. - Answer the hesitation, not only the literal words. - Keep claims safe and realistic. - Avoid robotic phrasing or hard-sell language. - Do not invent product details, pricing, shipping, or policy terms. ## Resources Read `references/output-template.md` for a compact response structure.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jsafe/1688-auto-purchase (version 1.0.0)

# 1688 自动采购下单 根据 Ozon 订单自动在 1688 分销一件代发，自动创建订单、填写集货仓地址、备注订单号。 ## 触发指令 自动采购 1688自动下单 代发采购 执行1688下单 ## 能力 - 读取 MEMORY.md 全局配置 - Ozon offer_id → 1688 商品ID 自动映射 - 自动创建 1688 采购订单 - 自动填写集货仓地址 - 自动备注：Ozon订单号，要求贴面单 - 支持批量订单处理


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector:  ()
Skill: halfmoon82/web-intel (version 1.0.0)

--- name: web-intel description: "网络搜索与信息提取统一入口。整合 content-extraction、Jina Reader、Firecrawl、web-access CDP。自动选最经济工具链。可被 BMW（brand-marketing-workflow）、wealth 子代理等直接调用。" version: 1.0.0 level: L1 tags: [browser, search, extraction, routing, economics, bmw, wealth, finance] --- # Web Intel — 统一网络检索层 ## 职责边界 本技能是**路由层**，不重写任何已有工具。调度链： ``` web-intel ├── content-extraction/scripts/extract_router.py (URL 分类) ├── r.jina.ai (轻量全文提取) ├── firecrawl CLI (搜索 + 抓取) └── web-access CDP Proxy (localhost:3456) (登录态/反爬) ``` ## 三档模式 | 模式 | 场景 | Token 消耗 | 延迟 | |------|------|-----------|------| | **fast** | 只需标题+摘要，快速定位 | ~200-500 | <2s | | **standard** | 需完整页面正文 | ~500-2000 | 2-8s | | **deep** | 登录内容 / JS重渲染 / 反爬站点 | ~2000-8000 | 10-30s | ## 决策树 ### A. 搜索任务（给关键词） ``` [fast] firecrawl search "query" --limit 5 → 返回 title + url + snippet [standard] firecrawl search + Jina 提取 top-1 全文 → tool: firecrawl_search+jina [deep] firecrawl search --scrape --limit 5 → 反爬/登录页面可升级到 web-access CDP ``` ### B. 提取任务（给 URL） ``` Step 0: extract_router.py 判断 URL 类型 → 微信/飞书/YouTube → 委托 skills/content-extraction（专用 handler） → 通用网页 → 继续 [fast] curl https://r.jina.ai/<url> [standard] Jina 优先；失败 → firecrawl scrape [deep] web-access CDP（localhost:3456）优先；降级 Jina → firecrawl scrape ``` ### C. 证券/财经（--type finance） ``` fast: firecrawl search "$TICKER 财报/行情/股价" --limit 5 standard: 同 fast + Jina 提取 top-1（东方财富/雪球） deep: → skills/stock-research-engine（完整基本面分析） ``` ### D. 竞品研究（--type competitor，BMW 使用） ``` fast: firecrawl search "品牌名 营销/产品/用户反馈" --limit 5 standard: fast + Jina 提取各结果全文 deep: firecrawl search --scrape；需要 CDP 的站点走 web-access ``` ## 调用约定（供其他技能/子代理） ```bash # 搜索 python3 ~/.openclaw/workspace/skills/web-intel/scripts/web_intel.py \ --query "比亚迪Q1财报" --mode fast --type finance # URL 提取 python3 ... --url https://example.com --mode standard # 竞品研究（BMW 调用） python3 ... --query "小米SU7营销策略" --mode standard --type competitor ``` **标准输出（JSON stdout）**： ```json { "query": "...", "mode": "fast", "type": "finance", "tool_used": "firecrawl_search", "results": [{"title": "...", "url": "...", "snippet": "..."}], "full_content": null, "web_access_available": true, "latency_ms": 1200 } ``` ## web-access CDP 集成说明 web-access 通过 CDP Proxy（localhost:3456）直连用户 Chrome，天然携带登录态。 **启动 CDP Proxy**（deep 模式前置）： ```bash bash ~/.openclaw/workspace/skills/web-access/scripts/check-deps.sh ``` **web-intel 在 deep 模式下自动检测 CDP 可用性**（`web_access_available` 字段）。CDP 可用时优先用于提取；不可用时降级到 Jina/Firecrawl。 ## 不包含的能力（直接引用现有技能） | 需求 | 使用技能 | |------|---------| | 微信公众号提取 | skills/content-extraction（handler=browser） | | 飞书文档提取 | skills/content-extraction（handler=feishu） | | YouTube 转录 | skills/content-extraction（handler=transcript） | | 浏览器交互/表单 | skills/browser + browser-use | | 个股深度研究 | skills/stock-research-engine | | 本地记忆搜索 | skills/search-memory | | CDP 站点经验库 | skills/web-access/references/site-patterns/ |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: stale | SkillSpector: suspicious (MEDIUM)
Skill: wxsjlrwsj/echo-test (version 1.0.0)

slug: echo-test name: Echo Test version: 1.0.0 description: 最简单的测试技能，返回你输入的内容 tags: - test - echo --- # Echo Test 这是一个测试技能，你输入什么，它就返回什么，同时显示当前时间。 ## 使用方法 直接说任何话，它会回复你。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: jdrhyne/ga4 (version 1.2.2)

--- name: ga4 description: Query Google Analytics 4 (GA4) data via the Analytics Data API. Use when you need to pull website analytics like top pages, traffic sources, user counts, sessions, conversions, or any GA4 metrics/dimensions. Supports custom date ranges and filtering. homepage: https://developers.google.com/analytics metadata: { "openclaw": { "emoji": "📊", "requires": { "anyBins": ["python3", "python"], "env": ["GA4_PROPERTY_ID", "GOOGLE_CLIENT_ID", "GOOGLE_CLIENT_SECRET", "GOOGLE_REFRESH_TOKEN"], }, }, } --- # GA4 - Google Analytics 4 Data API Query GA4 properties for analytics data: page views, sessions, users, traffic sources, conversions, and more. ## Setup (one-time) 1. Enable Google Analytics Data API: https://console.cloud.google.com/apis/library/analyticsdata.googleapis.com 2. Create OAuth credentials or use existing Google Cloud project 3. Set environment variables: - `GA4_PROPERTY_ID` - Your GA4 property ID (numeric, e.g., "123456789") - `GOOGLE_CLIENT_ID` - OAuth client ID - `GOOGLE_CLIENT_SECRET` - OAuth client secret - `GOOGLE_REFRESH_TOKEN` - OAuth refresh token (from initial auth flow) ## Safety Boundaries - This skill only connects to Google Analytics Data API endpoints. - It does NOT write to or modify your GA4 property — read-only queries only. - It does NOT store or transmit credentials beyond the current session. - It requires OAuth credentials (client ID, secret, refresh token) set as environment variables. ## Common Queries ### Top Pages (by pageviews) ```bash python3 scripts/ga4_query.py --metric screenPageViews --dimension pagePath --limit 30 ``` ### Top Pages with Sessions & Users ```bash python3 scripts/ga4_query.py --metrics screenPageViews,sessions,totalUsers --dimension pagePath --limit 20 ``` ### Traffic Sources ```bash python3 scripts/ga4_query.py --metric sessions --dimension sessionSource --limit 20 ``` ### Landing Pages ```bash python3 scripts/ga4_query.py --metric sessions --dimension landingPage --limit 30 ``` ### Custom Date Range ```bash python3 scripts/ga4_query.py --metric sessions --dimension pagePath --start 2026-01-01 --end 2026-01-15 ``` ### Filter by Page Path ```bash python3 scripts/ga4_query.py --metric screenPageViews --dimension pagePath --filter "pagePath=~/blog/" ``` ## Available Metrics Common metrics: `screenPageViews`, `sessions`, `totalUsers`, `newUsers`, `activeUsers`, `bounceRate`, `averageSessionDuration`, `conversions`, `eventCount` ## Available Dimensions Common dimensions: `pagePath`, `pageTitle`, `landingPage`, `sessionSource`, `sessionMedium`, `sessionCampaignName`, `country`, `city`, `deviceCategory`, `browser`, `date` ## Output Formats Default: Table format Add `--json` for JSON output Add `--csv` for CSV output


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xueyetianya/math-solver (version 2.0.0)

--- version: "2.0.0" name: math-solver description: "数学题解析与学习工具。分步骤解答、函数图形ASCII描述、公式速查、单位换算、练习题生成。Math solver with step-by-step solutions, function graphing, formula reference, unit conversion." author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills --- # math-solver 数学题解析与学习工具。分步骤解答、函数图形ASCII描述、公式速查、单位换算、练习题生成。Math solver with step-by-step solutions, function graphing, formula reference, unit conversion, practice problems. ## 推荐工作流 ``` 需求分析 → 选择命令 → 输入描述 → 获取结果 → 调整优化 ``` ## 命令速查 ``` solve solve step step graph graph formula formula convert convert practice practice ``` ## 专业建议 - 解题**：输入数学表达式或文字描述，获得解答 - 分步解答**：每一步都有说明，适合学习过程 - 图形描述**：用ASCII字符描绘函数图形概况 - 公式速查**：按类别快速查找常用公式 - 单位换算**：支持长度、面积、体积、重量、温度等 --- *math-solver by BytesAgain* --- 💬 Feedback & Feature Requests: https://bytesagain.com/feedback Powered by BytesAgain | bytesagain.com - Run `math-solver help` for all commands ## Commands Run `math-solver help` to see all available commands.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: roamer-remote/a-stocks-analysis (version 1.0.0)

--- name: "A股-股市分析和投资顾问（安西军项目）" version: 0.2.1 description: > 中国 A 股/港股只读数据查询与分析技能。支持行情、基本面、指数、文本四类数据检索， 支持自然语言需求映射到 stocks 接口，并输出结构化分析结果。 需 TAX_API_KEY 鉴权；仅用于公开历史数据查询，不支持交易下单，也不构成投资建议。 metadata: openclaw: requires: env: - TAX_API_KEY primaryEnv: TAX_API_KEY homepage: https://tax.yyyou.top/ --- ## 目标与边界 本 Skill 的目标是把用户自然语言问题转换为可执行的数据查询，并返回清晰、可复核的分析结论。 必须遵守： 1. 仅调用 `/stocks/...` 查询能力，不处理 `/auth/*`、`/payment/*` 等非股票查询路由。 2. 仅提供数据与分析，不给出交易代下单、收益承诺或“保证上涨”类结论。 3. 涉及投资建议时，始终加入风险提示与不构成投资建议声明。 4. 不回显、索取、存储或输出用户的 `TAX_API_KEY`。 ## 能力范围 | 类别 | 典型能力 | |------|----------| | 行情 | 日/周/月线、涨跌停、资金流向、复权因子、每日指标 | | 基本面 | 公司资料、三大报表、财务指标、分红、股东结构、质押回购 | | 指数 | 指数行情、成分股、权重、分类 | | 文本 | 上证 E 互动/深证互动易、政策法规、研报元数据 | ## 路由触发 当用户意图属于以下任一类时，触发本 Skill： - 股票代码、名称、上市公司（如"平安银行"、"600000"） - 行情、K线、涨跌、成交量、资金流向 - 财报、财务指标、分红、ROE - 指数、成分股、权重、大盘 - 董秘问答、互动易、政策法规、研报元数据 以下情况不触发（或先澄清）： - 与股票数据无关的问题 - 要求代客交易、绕过风控或提供内幕信息 - 输入信息不足且无法定位标的（需先确认股票代码/名称/时间区间） ## 参数与鉴权规范 1. 请求头必须包含： ```http Header: TAX-[REDACTED_SECRET] ``` 2. 常用参数格式： | 参数 | 格式 | 说明 | |------|------|------| | ts_code | `600000` 或 `600000.SH` | 支持裸码与标准码 | | start_date | `YYYYMMDD` | 起始日期 | | end_date | `YYYYMMDD` | 结束日期 | 3. 代码规则提醒： - 裸码自动识别交易所（如 `600000` -> `.SH`） - 前导 0 不可省略（`000001` 不能写成 `1`） ## 分析执行流程（推荐） 默认按三步执行，除非用户明确只要单点数据： 1. **行情层**：先看趋势与波动（[REDACTED_SECRET]） 2. **基本面层**：验证质量与业绩（`fina-indicator/income/...`） 3. **环境层**：指数或文本交叉验证（`index-*`、`irm-qa-*`、`research-report`） 如果任一步数据不足，应明确写出“当前结论置信度受限”。 ## 常用接口速查 | 问题类型 | 推荐接口 | |----------|----------| | 个股走势 | `/stocks/daily` `/stocks/weekly` `/stocks/monthly` | | 估值与交易活跃度 | `/stocks/daily-basic` `/stocks/moneyflow` | | 财务质量 | `/stocks/fina-indicator` `/stocks/income` `/stocks/cashflow` | | 分红与股东结构 | `/stocks/dividend` `/stocks/top10-holders` | | 市场环境 | `/stocks/index-daily` `/stocks/index-member` `/stocks/index-weight` | | 公司互动信息 | `/stocks/irm-qa-sh` `/stocks/irm-qa-sz` | ## 输出格式规范 默认每次回复必须包含以下四段（仅当用户明确要求“简短回答”时可降级）： 1. **数据概览**：说明查询标的、时间范围、核心指标 2. **观察结论**：分点描述主要发现（行情/基本面/环境） 3. **一致性与风险**：说明数据是否互相印证，给出不确定性 4. **下一步建议查询**：给出 1-3 条可继续验证的接口或问题 若查询失败，按以下顺序返回可执行修复建议： 1. `401/403`：优先提示检查 `TAX_API_KEY` 是否已配置、是否过期或失效。 2. `400` 或参数类错误：提示检查 `ts_code` 与日期格式（`YYYYMMDD`）及起止区间。 3. `502/5xx`：说明上游服务临时异常，建议稍后重试，并给出可降级查询路径（如先查基础行情）。 ## 注意事项 - 只提供公开历史数据查询，不保证实时性 - 不支持交易下单或收益承诺 - 本 Skill 输出仅供研究参考，不构成投资建议


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: heyheya11/case-echo (version 0.1.0)

--- name: case-echo description: extract simple structured json fields from a short chinese medical case description. use when the user provides a brief chinese case summary and wants standard fields like sex, age, diagnosis, stage, egfr, pd-l1, or brain metastasis status. --- # Case Echo Extract structured JSON fields from a short Chinese medical case description. ## Use this skill for - short case summaries in Chinese - quick field extraction from one paragraph of case text - converting semi-structured case text into simple JSON - standardizing obvious fields before downstream analysis ## Fields Extract these fields when present: - sex - age - diagnosis - stage - egfr - pd_l1 - brain_metastasis - raw_text ## Execution Run the bundled shell script and pass the original case text as one quoted argument: bash scripts/run_case_echo.sh "<USER_CASE_TEXT>" Replace `<USER_CASE_TEXT>` with the user's original case text. ## Output rules - Return valid JSON only. - Do not add explanation before or after the JSON. - Keep missing fields as null. - Do not invent values not present in the input text. - This skill only structures text. It does not provide diagnosis or treatment recommendations.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shr860910/file-memory-billing (version 0.1.1)

--- name: file-memory description: 文件化记忆与任务归档工作流。用户提到“不要依赖上下文/建立md档案/会话接力/清理上下文/长期任务持续交接”时使用：先建任务档案，再把关键信息写入ops与memory文件，按文件而非聊天历史继续工作。 metadata: { "openclaw": { "requires": { "bins": ["node"] }, "primaryEnv": "SKILL_BILLING_API_KEY" } } --- # File Memory Workflow 目标：不依赖长聊天上下文，靠文件稳定接力。 ## Billing（SkillPay） 每次调用先尝试扣费（默认 10 tokens = 0.01 USDT）。 - 脚本：`{baseDir}/scripts/skillpay-charge.mjs` - 必需环境变量： - `SKILL_BILLING_API_KEY` - `SKILL_ID` - 可选环境变量： - `SKILL_BILLING_URL`（默认 `https://skillpay.me/api/v1/billing`） - `SKILL_BILLING_TOKENS`（默认 `10`） 示例： ```bash node {baseDir}/scripts/skillpay-charge.mjs --user-id "<user-id>" --amount 10 ``` 返回： - `charged: true` → 继续执行 skill - `charged: false` 且有 `payment_url` → 把充值链接返回给用户 ## 必做规则 1. 先建任务档案，再开始执行。 2. 每次阶段完成都更新档案，不留“只在聊天里”的关键信息。 3. 代码类任务完成后，记录 commit 与验证步骤。 4. 需要长期记忆时，写入 `MEMORY.md` 或 `memory/YYYY-MM-DD.md`。 ## 标准目录 - 项目任务：`<repo>/ops/tasks/TASK-YYYYMMDD-HHMM.md` - 项目交接：`<repo>/ops/HANDOFF.md` - 过程日志：`<repo>/ops/WORKLOG.md` - 后续计划：`<repo>/ops/NEXT_STEPS.md` - 决策记录：`<repo>/ops/DECISIONS.md` - 全局日记：`<workspace>/memory/YYYY-MM-DD.md` - 长期记忆：`<workspace>/MEMORY.md`（仅主会话加载） ## 新任务流程 1. 创建任务档案 `TASK-*.md`，写：目标、验收标准、风险、执行记录。 2. 执行任务。 3. 完成后更新： - `ops/WORKLOG.md`（做了什么） - `ops/NEXT_STEPS.md`（下一步） - `ops/DECISIONS.md`（为什么这么做） 4. 若有代码改动：提交 commit，并在任务档案写明 commit hash。 ## 回复用户格式 - 任务ID：`TASK-...` - 状态：进行中/已完成 - 产出：文件/commit - 下一步：一句话 ## 注意 - 不把敏感信息写入仓库。 - 当用户要求“清上下文”时，不删历史事实，改为确保关键内容已文件化并从文件继续。


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