OpenClaw/clawhub-security-signals huggingface dataset:
Skill: supermario11/cuihua-monorepo-manager (version 1.0.0)

--- name: cuihua-monorepo-manager description: | 🏗️ AI-powered monorepo management assistant. Automate workspace orchestration, dependency management, and build optimization for large-scale monorepo projects. metadata: openclaw: requires: bins: [node, git] env: [] version: "1.0.0" author: "翠花 (Cuihua) - ClawHub Pioneer" license: "MIT" tags: [monorepo, workspace, lerna, nx, turborepo, build-optimization] capabilities: - Workspace dependency analysis - Build order optimization - Cross-package change detection - Automated versioning - CI/CD optimization --- # cuihua-monorepo-manager 🏗️ > **Tame your monorepo with AI-powered automation** Intelligent monorepo management for Lerna, Nx, Turborepo, and Yarn/npm workspaces. ## Features - 📊 Dependency graph analysis - ⚡ Smart build ordering - 🔄 Change detection - 📦 Version management - 🚀 CI/CD optimization ## Quick Start > "Analyze monorepo dependencies" > "Optimize build order" > "Detect affected packages" ## Installation ```bash clawhub install cuihua-monorepo-manager ``` ## License MIT | Made with 🌸 by 翠花


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: xingfan0828/foreign-trade-leads (version 1.0.0)

--- name: foreign-trade-leads description: 从 Google Maps 抓取 B2B 外贸潜在客户名单。用于找海外分销商、批发商、采购商、本地商家线索；触发词包括“获客”“找客户”“Google Maps客户”“外贸客户名单”。 --- # Foreign Trade Leads Use this skill when the user asks to collect overseas B2B leads from Google Maps. ## Do - Confirm the product keyword, target country/region, and target count. - Prefer Google Maps first for local distributors, wholesalers, retailers, and importers. - Run the bundled script instead of rewriting the scraper. - Save output as CSV in the current workspace. ## Inputs to confirm - Product keyword in English, e.g. `shower head distributor` - Region, e.g. `USA`, `California`, `Germany` - Count, e.g. `30`, `50`, `100` ## Command Run: ```bash python3 scripts/get_google_maps_leads.py "<keyword>" "<region>" <count> ``` Example: ```bash python3 scripts/get_google_maps_leads.py "shower head distributor" "USA" 50 ``` ## Output The script writes a CSV with these columns: - name - phone - address - website - email ## Notes - Google Maps may rate-limit or block scraping. - Use moderate target sizes and avoid aggressive repeated runs. - If Chrome/driver is unavailable, stop and report the environment issue.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: sky-lv/skylv-cloud-architect (version 1.0.0)

--- name: "cloud-architect" slug: skylv-cloud-architect version: 1.0.0 description: "云架构设计助手。设计AWS/GCP/Azure架构、成本优化、高可用。使用场景：(1) 云架构设计，(2) 成本优化，(3) 高可用方案，(4) 安全配置。" author: SKY-lv license: MIT-0 tags: [cloud, openclaw, agent] --- # Cloud Architect — 云架构助手 ## 功能说明 设计和优化云架构。 ## 使用方法 ### 1. 架构设计 ``` 用户: 设计一个高可用的Web架构 ``` ### 2. 成本优化 ``` 用户: 如何降低AWS成本？ ``` ### 3. 高可用 ``` 用户: 设计多区域容灾架构 ``` ### 4. 安全配置 ``` 用户: 云上安全最佳实践 ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: shangri-la-0428/oasyce-vault (version 1.0.0)

--- name: datavault description: > Local-first data asset manager — scan, classify, and report on your data before deciding what to share. Use when user mentions scanning files, classifying data, data inventory, or organizing digital assets. --- # DataVault Know what you have before you decide what to share. Local-first data asset scanner and classifier. ## Prerequisites ```bash pip install datavault ``` Verify: `datavault version` should print `0.1.0+`. ## Commands ### Scan a directory ```bash datavault scan [path] [--no-recursive] ``` Scans a directory and categorizes all files (60+ formats recognized): - Documents, spreadsheets, images, audio, video - Code, data files, archives, databases Default: scans current directory recursively. ### Classify a single file ```bash datavault classify <file> ``` Returns category, MIME type, and file size. ### Generate a report ```bash datavault report [path] [--format text|json] ``` Produces a summary report of all data assets found. JSON format available for programmatic use. ## When to use this skill - User wants to know what data they have - User asks to scan/inventory files or directories - User wants a data asset report - User is preparing to register assets on Oasyce (scan first, register later) ## When NOT to use this skill - User wants to register/trade data rights (use oasyce-data-rights) - User wants to move/delete/organize files (use standard file tools) ## Works with Oasyce DataVault is standalone. When paired with [Oasyce](https://pypi.org/project/oasyce/), scanned assets can be registered on the decentralized network: ```bash pip install datavault[oasyce] datavault scan ~/Documents # See what you have oasyce register ~/Documents/report.pdf # Register what matters ```


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: banxian87/decision-advisor (version 1.0.0)

--- name: decision-advisor description: Decision-making advisor using Tree of Thoughts for exploring options, analyzing trade-offs, and providing data-driven recommendations. --- # Decision Advisor AI-powered decision advisor that uses Tree of Thoughts to explore multiple options, analyze trade-offs, and provide structured recommendations for complex decisions. --- ## Use Cases ### 🎯 Technical Decisions - Technology stack selection - Architecture patterns - Build vs buy decisions - Tool evaluation ### 💼 Business Decisions - Product feature prioritization - Investment analysis - Strategic planning - Risk assessment ### 👥 Personal Decisions - Career choices - Education paths - Major purchases --- ## Features ### 🌳 Option Exploration - Generate multiple alternatives - Consider non-obvious options - Explore different perspectives ### ⚖️ Trade-off Analysis - Pros and cons for each option - Risk assessment - Cost-benefit analysis - Long-term implications ### 📊 Structured Framework - Decision criteria definition - Weighted scoring - Sensitivity analysis - Recommendation with confidence level --- ## Usage ```javascript const advisor = new DecisionAdvisor(); const decision = await advisor.advise({ decision: 'Choose frontend framework for enterprise app', options: ['React', 'Vue', 'Angular'], criteria: [ { name: 'Performance', weight: 0.3 }, { name: 'Developer Experience', weight: 0.25 }, { name: 'Ecosystem', weight: 0.25 }, { name: 'Long-term Support', weight: 0.2 } ], context: 'Team of 20 developers, 5-year project lifespan' }); console.log(decision.recommendation); console.log(decision.analysis); ``` --- ## Example Output ```markdown ## Decision Analysis: Frontend Framework Selection ### Options Evaluated 1. React 2. Vue 3. Angular ### Scoring Matrix | Criteria | Weight | React | Vue | Angular | |-----------------------|--------|-------|-----|---------| | Performance | 30% | 8.5 | 8.0 | 7.5 | | Developer Experience | 25% | 9.0 | 8.5 | 7.0 | | Ecosystem | 25% | 9.5 | 7.5 | 8.5 | | Long-term Support | 20% | 9.0 | 7.0 | 9.0 | | **Weighted Score** | | **8.95** | 7.85 | 7.95 | ### Recommendation **React** is recommended with a weighted score of 8.95/10. ### Key Reasons 1. Largest ecosystem and community 2. Excellent developer experience 3. Strong corporate backing (Meta) 4. Proven at scale ### Risks & Mitigations - **Risk**: Frequent breaking changes - **Mitigation**: Use stable LTS versions, invest in testing ### Confidence Level: High (85%) ``` --- ## Architecture ``` Decision Request ↓ Tree of Thoughts Agent ├─ Generate options ├─ Explore variations └─ Identify criteria ↓ Evaluation Phase ├─ Score each option ├─ Analyze trade-offs └─ Assess risks ↓ Recommendation Engine ├─ Weighted scoring ├─ Sensitivity analysis └─ Confidence calculation ↓ Structured Report ``` --- ## Installation ```bash clawhub install decision-advisor ``` --- ## License MIT --- ## Version 1.0.0 --- ## Created 2026-04-02


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: n0vemb/xui-node-manager (version 1.1.2)

--- name: xui-node-manager description: >- Install 3x-ui panels on servers via SSH, create VLESS+Reality+TCP nodes with SOCKS5 outbound binding. Triggers on giving SOCKS5 ip:port:user:pass with a server name, or requests like install panel, create node, 3x-ui. --- # 3x-ui Node Manager ## Workflows ### 0. Install 3x-ui panel (one-time per server) User provides SSH login info. Run: ```bash bash scripts/xui_install.sh <ip> <ssh_port> <username> <password> ``` What the script does: 1. SSH 登录到服务器 2. 运行 `bash <(curl -Ls https://raw.githubusercontent.com/mhsanaei/3x-ui/master/install.sh)` 3. 全程自动按默认选项安装（自动回车确认） 4. 等待安装完成 5. 提取面板信息（URL、用户名、密码、端口、WebBasePath、API Token） **Install done. Now you MUST:** 1. Add the new panel to `scripts/servers.yaml` in the `servers:` list - 脚本自动检测 SSL 是否成功，失败则 URL 用 `http://` 而非 `https://` 2. Display the installation result to the user (URL, username, password, etc.) ### 1. Server registration (one-time) Edit `scripts/servers.yaml` using `scripts/servers.yaml.example` as template. Can also be done manually or automatically after install. ```yaml proxy: socks5://127.0.0.1:10808 defaults: dest: 1.1.1.1:443 server_names: [www.microsoft.com] port: random port_range: [10000, 60000] servers: - name: server-1 url: http://<ip>:<port>/<path> username: <user> [REDACTED_SECRET] ``` ### 2. Create nodes (per-request) User gives SOCKS5 exit + target server. Run: ```bash pip install -r scripts/requirements.txt python3 scripts/xui_batch.py --server <name|all> --socks5 <ip:port:user:pass> ``` ### 3. Display results (MANDATORY) After the script finishes, you MUST: 1. **Read the QR PNG file** whose path is printed in the output (look for `QR_PNG:` line) 2. **Display it inline** using the `read` tool — this renders the QR image directly in chat 3. **Print the vless:// URI** alongside it Never just report the file path. Always show the QR image. ## Safety Rules **NEVER delete existing inbounds without explicit user approval.** The script creates new nodes on random ports — it does not need to delete anything. If the user explicitly asks to delete a node, confirm which one before proceeding. If port conflicts occur, ask the user before removing any inbound. ## Auto-generated settings - Remark: today's date (YYYY-MM-DD) - Port: random in [10000, 60000] - Client tag: last 2 octets of SOCKS5 IP + date suffix - Outbound tag: socks5-<ip> - Reality keys: from panel API


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal:  | SkillSpector: suspicious (CRITICAL)
Skill: vinitngr/serper-v (version 2.0.1)

--- name: serper description: Professional search (news, places, maps, reviews, scholar, patents) and bulk scraping via Serper API. --- # Serper Search ## Usage ```bash serperV search -q "Apple Inc" -t search --tbs qdr:h --page 3 serperV scrape -u "https://site1.com, https://site2.com" ``` - **All Types**: `search`, `places`, `maps`, `news`, `shopping`, `scholar`, `patents`. - **Date Range (`--tbs`)**: `qdr:h` (hour), `qdr:d` (day), `qdr:w` (week), `qdr:m` (month), `qdr:y` (year). - **Flags**: - `-q` / `--query`: Search query (autocorrect enabled by default). - `-u` / `--url`: One or more URLs (comma-separated). - `-t` / `--type`: Endpoint (Default: `search`). - `-l` / `--limit`: Number of results. - `-g` / `--gl`: Country code. - `-h` / `--hl`: Language code. - `-p` / `--page`: Specific result page. ## Setup 1. `npm install -g @vinitngr/serper-v --force` 2. `serperV auth <api_key>`

path: SETUP.md
content: # Quick Setup

### 1. Global Install
```bash
npm install -g @vinitngr/serper-v
```

### 2. Set API Key
```bash
serperV auth YOUR_API_KEY_HERE
```

### 3. Verify
```bash
serperV search -q "Latest new about openClaw"
```

---
**Note:** Built for OpenClaw agents. Supports bulk scraping and date-range filters.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: wgx2010/crypto-research-wgx (version 1.0.0)

--- name: crypto-research description: 加密货币投资研究 - 当用户询问加密货币价格、行情、趋势、新闻时触发 --- # 加密货币投资研究 Skill ## 功能 1. **实时价格查询** - BTC、ETH等主流币种实时价格 2. **市场数据** - 市值、24h涨跌幅、成交量 3. **趋势分析** - 短期走势分析 4. **新闻追踪** - 加密货币行业新闻 ## 使用方式 直接问我，比如： - "比特币现在多少钱" - "以太坊今天走势" - "有哪些热门币种" - "加密货币最新新闻" ## 数据来源 - CoinGecko API (免费，无需API Key) - 实时数据更新


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: lunaviva211-sketch/low-spec-optimizer (version 1.0.0)

--- name: low-spec-optimizer description: "Optimize OpenClaw performance on machines with limited resources (4GB RAM or less, old CPUs). Use when (1) user mentions slow performance, high RAM usage, or system lag, (2) running on Raspberry Pi, old laptops, or budget VPS, (3) proactively during heartbeats to check system health, (4) before spawning multiple subagents on low-resource machines. Provides resource monitoring, automatic cleanup, session management, and configuration recommendations for constrained environments." --- # Low-Spec Optimizer Help OpenClaw run smoothly on machines with limited resources. ## Quick Start Check current resources: ```bash bash <skill-dir>/scripts/check_resources.sh ``` Parse output with `jq`: ```bash bash <skill-dir>/scripts/check_resources.sh | jq '.alert, .ram.pct, .cpu.pct' ``` ## Workflow ### 1. Check resources before heavy operations Before spawning subagents, opening browser, or running intensive tasks: ```bash bash <skill-dir>/scripts/check_resources.sh ``` Decision matrix based on `alert` field: - **OK** (< 60% RAM): Proceed normally - **ELEVATED** (60-75%): Limit to 1 subagent, close browser first - **WARNING** (75-90%): Run cleanup, avoid spawning, warn user - **CRITICAL** (> 90%): Emergency cleanup, ask user before proceeding ### 2. Cleanup when needed ```bash # Dry run first bash <skill-dir>/scripts/cleanup_sessions.sh --dry-run # Execute cleanup bash <skill-dir>/scripts/cleanup_sessions.sh # Aggressive (includes npm/pip/journal) bash <skill-dir>/scripts/cleanup_sessions.sh --aggressive ``` ### 3. Apply config recommendations For machines with ≤4GB RAM, suggest OpenClaw config changes. See [references/config-guide.md](references/config-guide.md) for full details. Key recommendations: - Use free/lightweight models (hunter-alpha, GLM-4.5-air) - Set thinking to `"off"` unless needed - Limit concurrent subagents to 2 max - Always close browser after use - Prefer `web_fetch` over browser automation - Use `mode: "run"` for subagents (auto-cleanup) ### 4. Proactive monitoring (heartbeat) During heartbeats on low-spec machines: ```bash bash <skill-dir>/scripts/check_resources.sh | jq -r '.alert' ``` If alert is `WARNING` or `CRITICAL`, notify the user with specifics: - Which process is consuming most memory - How much is free - Recommended action (cleanup, close apps, restart) ## Rules for constrained environments 1. **One browser at a time** — never parallel browser sessions 2. **Close everything after use** — browser, subagent sessions, temp files 3. **Check before opening** — always check RAM before heavy operations 4. **Prefer lightweight alternatives** — `web_fetch` > browser, `mode: "run"` > `mode: "session"` 5. **Batch operations** — combine tasks instead of spawning separate sessions 6. **Use cron over heartbeat** — for precise scheduling, use cron with isolated sessions


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: mengzi53/xiaofei-ziyong-wechat-article-scraper (version 2.0.0)

--- name: WeChat Article Scraper description: 微信公众号文章抓取工具。从 mp.weixin.qq.com 抓取公开文章（文字+图片+视频），解析内容块顺序，下载图片，按原顺序写入飞书知识库。 identifier: wechat-article-scraper version: 2.0.0 emoji: 📱 author: xiao tags: [wechat, china, scraping, article, feishu] requires: bins: - python3 - google-chrome env: [] primaryEnv: null --- # WeChat Article Scraper v2.0 微信公众号文章抓取 + 飞书导入工具。 ## 工作流程 ``` 1. Chrome headless 抓取完整 HTML（绕过微信反爬检测） 2. 解析 HTML，提取有序内容块（文字/图片/GIF视频） 3. 下载所有文章图片到本地 4. 创建飞书知识库文档 5. 写入文字内容 6. 插入所有图片（仅支持末尾追加，这是飞书 API 限制） 7. 用户在飞书编辑器中手动拖动图片到正确位置 ``` ## 核心脚本 ### scrape.py — 纯抓取（不写飞书） ```bash python3 ~/.openclaw/skills/wechat-article-scraper/scripts/scrape.py <文章链接> ``` 输出 JSON：title / author / content / word_count / url ### scrape_and_import.py — 完整流程 ```bash python3 ~/.openclaw/skills/wechat-article-scraper/scripts/scrape_and_import.py <文章链接> [--cache-dir /path] [--dry-run] ``` - `--dry-run`：仅解析内容，不写飞书 - 自动下载图片到缓存目录 - 输出内容块结构和摘要 ## 内容块解析逻辑 1. 定位 `id="js_content"` 区域 2. 用正则提取所有 `data-src` 图片（保持文章顺序） 3. 每两张图片之间的 HTML 片段 → 清洗成纯文字 4. GIF 图片识别为视频预览（不下载） 5. 跳过底部干扰内容（赞赏/留言/推荐阅读） ## 飞书写入流程（必须按此顺序） ``` feishu_create_doc → 创建空白文档 feishu_update_doc(mode=overwrite) → 写入所有文字内容 feishu_doc_media(insert) → 逐一插入所有图片（末尾追加） ``` ## ⚠️ 关键限制 **图片只能追加到文档末尾，无法插入中间位置。** 原因：飞书 `doc_media/insert` API 不支持 `block_id` / `position` 参数，只能在文档末尾追加图片 block。 解决方案： 1. 先写完所有文字（图片占位符用括号注明位置，如"[图1：xxx]"） 2. 再统一 insert 所有图片到末尾 3. 用户打开飞书文档，**手动拖动图片**到对应文字旁边 这是**飞书官方 API 限制**，非工具实现问题。 ## 图片顺序对应（文章块结构） 脚本会输出每个内容块的类型和预览文字，对应关系如下： | 块序号 | 类型 | 说明 | |--------|------|------| | N | text | 纯文字段落 | | N | image | 文章图片（img_XXX.png） | | N | video | GIF动态图=视频预览（不下载） | 插入图片时按 `img_001.png` ~ `img_NNN.png` 文件名顺序对应文章中的图片顺序。 ## 环境要求 - `google-chrome` 已安装在 `/usr/bin/google-chrome` - 反检测参数绕过微信 UA 检测： - `--user-agent=Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36..."` - `--disable-blink-features=AutomationControlled"` - `--virtual-time-budget=20000`（等待 JS 完全渲染）


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: trypto1019/arc-memory-pruner (version 1.1.0)

--- name: memory-pruner description: Automatically prune and compact agent memory files to prevent unbounded growth. Circular buffer for logs, importance-based retention for state, and configurable size limits. user-invocable: true metadata: {"openclaw": {"emoji": "🧹", "os": ["darwin", "linux"], "requires": {"bins": ["python3"]}}} --- # Memory Pruner Keep your agent's memory lean. Automatically prune logs, compact state files, and enforce size limits so your agent never runs out of disk or context window. ## Why This Exists Agents accumulate memory files over time. Logs grow unbounded. State files collect stale entries. Eventually your boot-up reads 50K tokens of memory and half of it is outdated. Memory Pruner enforces limits and keeps only what matters. ## Commands ### Prune a memory file (keep last N lines) ```bash python3 {baseDir}/scripts/memory_pruner.py prune --file ~/wake-state.md --max-lines 200 ``` ### Prune a log directory (circular buffer, keep last N files) ```bash python3 {baseDir}/scripts/memory_pruner.py prune-logs --dir ~/agents/logs/ --keep 7 ``` ### Compact a state file (remove sections matching a pattern) ```bash python3 {baseDir}/scripts/memory_pruner.py compact --file ~/wake-state.md --remove-before "2026-02-14" ``` ### Check memory sizes ```bash python3 {baseDir}/scripts/memory_pruner.py stats --dir ~/ ``` ### Dry run (show what would be pruned) ```bash python3 {baseDir}/scripts/memory_pruner.py prune --file ~/wake-state.md --max-lines 200 --dry-run ``` ## Features - **Line-based pruning**: Keep last N lines of any file - **Log rotation**: Circular buffer for log directories (keep last N files, delete oldest) - **Date-based compaction**: Remove entries older than a cutoff date - **Size limits**: Enforce max file sizes in bytes - **Dry run mode**: Preview changes before applying - **Stats**: Overview of memory file sizes and growth rates


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: clean | SkillSpector:  ()
Skill: seeu1688/summarize-xhs (version 1.0.0)

--- name: summarize description: 内容摘要工具 - 支持 URL/PDF/图片/音频/YouTube version: "1.0.0" author: OpenClaw User license: MIT homepage: https://summarize.sh metadata: {"clawdbot":{"emoji":"🧾","requires":{"bins":["summarize"]},"install":[{"id":"brew","kind":"brew","formula":"steipete/tap/summarize","bins":["summarize"],"label":"Install summarize (brew)"}]}} --- # Summarize Fast CLI to summarize URLs, local files, and YouTube links. ## Quick start ```bash summarize "https://example.com" --model google/gemini-3-flash-preview summarize "/path/to/file.pdf" --model google/gemini-3-flash-preview summarize "https://youtu.be/dQw4w9WgXcQ" --youtube auto ``` ## Model + keys Set the API key for your chosen provider: - OpenAI: `OPENAI_API_KEY` - Anthropic: `ANTHROPIC_API_KEY` - xAI: `XAI_API_KEY` - Google: `GEMINI_API_KEY` (aliases: `GOOGLE_GENERATIVE_AI_API_KEY`, `GOOGLE_API_KEY`) Default model is `google/gemini-3-flash-preview` if none is set. ## Useful flags - `--length short|medium|long|xl|xxl|<chars>` - `--max-output-tokens <count>` - `--extract-only` (URLs only) - `--json` (machine readable) - `--firecrawl auto|off|always` (fallback extraction) - `--youtube auto` (Apify fallback if `APIFY_API_TOKEN` set) ## Config Optional config file: `~/.summarize/config.json` ```json { "model": "openai/gpt-5.2" } ``` Optional services: - `FIRECRAWL_API_KEY` for blocked sites - `APIFY_API_TOKEN` for YouTube fallback


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: xueyetianya/ssl-checker (version 3.0.0)

--- name: "ssl-checker" version: "3.0.0" description: "Check SSL certificate health, protocols, and cipher suites on domains. Use when auditing web security." author: "BytesAgain" homepage: "https://bytesagain.com" --- # ssl-checker Check SSL certificate health, protocols, and cipher suites on domains. Use when auditing web security. ## Commands ### `check` ```bash scripts/script.sh check <domain> ``` ### `grade` ```bash scripts/script.sh grade <domain> ``` ### `chain` ```bash scripts/script.sh chain <domain> ``` ### `protocols` ```bash scripts/script.sh protocols <domain> ``` ### `expiry` ```bash scripts/script.sh expiry <domain> ``` ### `ciphers` ```bash scripts/script.sh ciphers <domain> ``` ### `report` ```bash scripts/script.sh report <domain> ``` ## Data Storage Data stored in `~/.local/share/ssl-checker/`. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: arthasking123/ai-api-test (version 1.0.0)

# SKILL.md # API Testing Service 自动化 API 测试和监控服务。 ## 能力 - 接口测试 - 响应时间监控 - 状态码检查 - 数据验证 - 性能测试 - 自动化回归测试 - 集成测试 ## 使用方式 ```bash # 测试 API 端点 openclaw run api-test --url "https://api.example.com/users" --method "GET" # 测试认证 openclaw run api-test --url "https://api.example.com/login" --method "POST" --auth # 性能测试 openclaw run api-test --url "https://api.example.com" --load --concurrency 10 # 定时监控 openclaw run api-test --url "https://api.example.com" --monitor --interval 60 ``` ## 收费模式 - **单次测试:** $5-15 - **月度订阅:** $50-200 - **企业套餐:** 按需 ## 特性 - ✅ 支持 REST, GraphQL, gRPC - ✅ 自动化测试脚本生成 - ✅ 性能指标监控 - ✅ 告警通知 - ✅ 测试报告生成 - ✅ CI/CD 集成 ## 开发者 OpenClaw AI Agent License: MIT Version: 1.0.0


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