OpenClaw/clawhub-security-signals huggingface dataset:
Skill: g9pedro/loom-workflow (version 1.0.1)

--- name: loom-workflow description: | AI-native workflow analyzer for Loom recordings. Breaks down recorded business processes into structured, automatable workflows. Use when: - Analyzing Loom videos to understand workflows - Extracting steps, tools, and decision points from screen recordings - Generating Lobster workflow files from video walkthroughs - Identifying ambiguities and human intervention points in processes --- # Loom Workflow Analyzer Transforms Loom recordings into structured, automatable workflows. ## Quick Start ```bash # Full pipeline - download, extract, transcribe, analyze {baseDir}/scripts/loom-workflow analyze https://loom.com/share/abc123 # Individual steps {baseDir}/scripts/loom-workflow download https://loom.com/share/abc123 {baseDir}/scripts/loom-workflow extract ./video.mp4 {baseDir}/scripts/loom-workflow generate ./analysis.json ``` ## Pipeline 1. **Download** - Fetches Loom video via yt-dlp 2. **Smart Extract** - Captures frames at scene changes + transcript timing 3. **Transcribe** - Whisper transcription with word-level timestamps 4. **Analyze** - Multimodal AI analysis (requires vision model) 5. **Generate** - Creates Lobster workflow with approval gates ## Smart Frame Extraction Frames are captured when: - **Scene changes** - Significant visual change (ffmpeg scene detection) - **Speech starts** - New narration segment begins - **Combined** - Speech + visual change = high-value moment - **Gap fill** - Max 10s without a frame ## Analysis Output The analyzer produces: - `workflow-analysis.json` - Structured workflow definition - `workflow-summary.md` - Human-readable summary - `*.lobster` - Executable Lobster workflow file ### Ambiguity Detection The analyzer flags: - Unclear mouse movements - Implicit knowledge ("the usual process") - Decision points ("depending on...") - Missing credentials/context - Tool dependencies ## Vision Analysis Step After extraction, use the generated prompt with a vision model: ```bash # The prompt is at: output/workflow-analysis-prompt.md # Attach frames from: output/frames/ # Example with Claude: cat output/workflow-analysis-prompt.md | claude --images output/frames/*.jpg ``` Save the JSON response to `workflow-analysis.json`, then: ```bash {baseDir}/scripts/loom-workflow generate ./output/workflow-analysis.json ``` ## Lobster Integration Generated workflows use: - `approve` gates for destructive/external actions - `llm-task` for classification/decision steps - Resume tokens for interrupted workflows - JSON piping between steps ## Requirements - `yt-dlp` - Video download - `ffmpeg` - Frame extraction + scene detection - `whisper` - Audio transcription - Vision-capable LLM for analysis step ## Multilingual Support Works with any language - Whisper auto-detects and transcribes. Analysis should be prompted in the video's language for best results.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: suspicious | SkillSpector:  ()
Skill: freedompixels/cn-todo-today (version 1.2.4)

slug: cn-todo-today name: 今日待办生成器 description: "cn-todo-today。纯Python标准库，无需API Key。" keywords: todo, today version: "1.0.0" author: 千策 # 今日待办生成器 简单易用的今日待办事项管理工具。 ## 功能 - 添加待办事项 - 标记完成 - 查看今日待办 - 统计完成情况 ## 使用方法 ```bash # 添加待办 python3 cn_todo_today.py add "完成报告" # 列出今日待办 python3 cn_todo_today.py list # 标记完成 python3 cn_todo_today.py done 1 # 删除待办 python3 cn_todo_today.py delete 1 # 统计 python3 cn_todo_today.py stats ``` ## 参数 | 参数 | 说明 | 默认值 | |------|------|--------| | `action` | 操作：add/list/done/delete/stats | 必填 | | `--text` | 待办文本（add时） | 空 | | `--id` | 待办ID（done/delete时） | 空 | ## 数据存储 - 本地JSON文件：`~/.cn_todo_today.json` ## 示例 ```bash # 添加 python3 cn_todo_today.py add "写周报" python3 cn_todo_today.py add "回复邮件" # 查看 python3 cn_todo_today.py list # 完成 python3 cn_todo_today.py done 1 ``` ## 依赖 - Python 3.x（内置json模块） ## 注意事项 - 数据存储在用户主目录 - 每天会自动清理已完成的待办


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

# SKILL.md # Web Automation Service 自动化 Web 任务执行服务。 ## 能力 - 表单填写 - 数据抓取 - 定时任务 - 自动化测试 - API 测试 - 网站监控 - 自动化提交 ## 使用方式 ```bash # 自动化表单填写 openclaw run web-automation --url "https://example.com/form" --data '{"name": "test"}' # 抓取网页 openclaw run web-automation --action "scrape" --url "https://example.com" # 定时任务 openclaw run web-automation --action "cron" --schedule "0 */6 * * *" --target "monitor" # 自动化测试 openclaw run web-automation --action "test" --url "https://example.com" ``` ## 收费模式 - **单次任务:** $5-20 - **月度订阅:** $50-150 - **企业套餐:** 按需 ## 特性 - ✅ 支持 Selenium/Puppeteer - ✅ 多浏览器支持 - ✅ 自动重试机制 - ✅ 代理池支持 - ✅ 定时任务调度 - ✅ 邮件/通知集成 ## 开发者 OpenClaw AI Agent License: MIT Version: 1.0.0


Security scan verdicts — ClawScan: clean | static analysis:  | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: gu-heping/onebot-adapter (version 1.0.0)

--- name: onebot-adapter description: Connect OpenClaw to OneBot protocol for QQ bot integration. Use when receiving or sending QQ messages via NapCat or other OneBot servers. version: 1.0.0 --- # OneBot Adapter Connect OpenClaw to OneBot protocol servers like NapCat for QQ bot functionality. ## Quick Start ### 1. Configure Connection Set OneBot server URL in environment or config: ```bash export ONEBOT_WS_URL="ws://127.0.0.1:3001" export ONEBOT_HTTP_URL="http://127.0.0.1:3000" export ONEBOT_TOKEN="your-token" ``` ### 2. Receive Messages Use the WebSocket listener script to receive QQ messages: ```bash python scripts/onebot_ws_listener.py ``` ### 3. Send Messages Use HTTP API to send messages: ```python from scripts.onebot_client import OneBotClient client = OneBotClient() client.send_private_msg(user_id=123456, message="Hello!") client.send_group_msg(group_id=789012, message="Group message") ``` ## Connection Modes ### WebSocket (Recommended) - Real-time bidirectional communication - Receives events instantly - Supports both sending and receiving ### HTTP - Request-response model - Good for simple sending - Requires polling for receiving ## Common Tasks ### Get Login Info ```python client.get_login_info() ``` ### Get Friend/Group List ```python client.get_friend_list() client.get_group_list() ``` ### Handle Messages See [references/message-handling.md](references/message-handling.md) for message parsing and response patterns. ## NapCat Specific NapCat is a OneBot11 implementation based on NTQQ. Default ports: - WebSocket: 3001 - HTTP: 3000 - WebUI: 6099 Token authentication is optional but recommended for public deployments. ## Troubleshooting **Connection refused**: Check if OneBot server is running and ports are correct. **Authentication failed**: Verify token matches OneBot server configuration. **Message not delivered**: Check user_id/group_id exists and bot has permission.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: qiji0802/auto-report-generator (version 1.0.2)

# Auto Report Generator Skill ## 功能 上传数据（CSV/Excel）→ AI自动分析 → 生成专业报表（图表+文字分析+格式），一键搞定月报/周报。 ## 核心文件 - `SKILL.md` - 本文件，技能说明 - `scripts/generator.py` - 主生成器脚本（CLI入口） - `core/parser.py` - 数据解析（pandas） - `core/charts.py` - 图表生成（matplotlib/xlsxwriter） - `core/ai_analyzer.py` - AI分析（OpenAI兼容接口） - `core/report_builder.py` - 报表构建（多sheet Excel） - `core/quota.py` - 额度管理（免费5次绝对计数） - `core/templates.py` - 模板系统 - `scripts/quick_report.sh` - 快捷生成脚本 ## 安装依赖 ```bash pip install pandas openpyxl xlsxwriter matplotlib pillow -q ``` ## 使用方式 通过 Skill 系统调用 `scripts/generator.py`，传入参数： - `--file` 数据文件路径 - `--template` 模板类型（月报/财务/销售/对比/自定义） - `--ai-provider` AI提供商（openai/deepseek） - `--ai-model` AI模型 - `--tier` 套餐等级（FREE/STD/PRO/MAX） - `--output` 输出路径 ## 套餐说明 - FREE: 5次绝对计数，1图表 - STD: ¥9.9/月，50次/月，3图表 - PRO: ¥29.9/月，200次/月，不限图表，PDF导出 - MAX: ¥99/月，不限次数，自定义模板 ## Token前缀 REPORT-FREE / REPORT-STD / REPORT-PRO / REPORT-MAX


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: malicious | SkillSpector: suspicious (HIGH)
Skill: modestyrichards/modesty-create-volunteer-orientation-voice-script (version 1.0.0)

--- name: "Create Volunteer Orientation Voice Script" description: "Write a volunteer onboarding script designed for audio or live orientation. Use when working on volunteer onboarding for development teams, nonprofit..." homepage: "https://www.skillboss.co/skills/create-volunteer-orientation-voice-script" metadata: {"category":"nonprofit-growth","subcategory":"volunteer-onboarding","skill_id":[REDACTED_SECRET],"generated_day":"","seo_keywords":["volunteer orientation script", "nonprofit onboarding voiceover", "volunteer training AI", "community program introduction"]} --- # Create Volunteer Orientation Voice Script Write a volunteer onboarding script designed for audio or live orientation. Use when working on volunteer onboarding for development teams, nonprofit... ## Use When Use this skill for volunteer onboarding work for development teams, nonprofit marketers, executive directors. ## Workflow 1. Clarify the audience, business goal, constraints, and deliverable. 2. Produce the strongest first draft for the target use case. 3. Use the relevant SkillBoss capabilities to enrich assets or supporting data. 4. Refine the output for accuracy, readability, and actionability before delivery. ## SEO / GEO - Primary keywords: volunteer orientation script, nonprofit onboarding voiceover, volunteer training AI, community program introduction - Search intent: volunteer onboarding - Canonical slug: `create-volunteer-orientation-voice-script` - Install query: Install Create Volunteer Orientation Voice Script with SkillBoss ## APIs Used - `chat` - `tts` ## Suggested Prompt [Create Volunteer Orientation Voice Script] for my nonprofit-growth business ## Notes - Write a volunteer onboarding script designed for audio or live orientation - Review outputs before external publication or automated execution. ## SEO Keywords - volunteer orientation script - nonprofit onboarding voiceover - volunteer training AI - community program introduction


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: pipi6688/passive-income-claw (version 0.7.0)

--- name: passive-income-claw version: 0.1.0 description: | Binance passive income AI assistant. Automatically scans Binance earn opportunities, pushes matching opportunities based on user preferences, and executes subscriptions within authorized limits. Use when user mentions "passive income", "earn", "yield", "scan opportunities", "buy earn product", "what opportunities suit me". After install, tell the user: "Run /passive-income to get started, or just say 'help me set up passive income'." user-invocable: true metadata: '{"openclaw":{"requires":{"env":["BINANCE_API_KEY","BINANCE_API_SECRET"]}}}' --- # Passive Income Claw ## Tools This skill includes TypeScript scripts in `{baseDir}/bin/` for all deterministic operations. **Always use these via `node {baseDir}/bin/<script>.ts` instead of doing arithmetic, file parsing, or API calls manually.** | Script | Purpose | |--------|---------| | `bin/earn-api.ts` | Binance Earn API + **账户资产明细查询** (`balance` 命令) | | `bin/margin-api.ts` | Binance Cross Margin API (借贷、还款、账户状态、利率) | | `bin/profile.ts` | User profile read/write/daily-reset | | `bin/auth-check.ts` | 5-step authorization validation | | `bin/snapshot.ts` | Snapshot diff & update | | `bin/log.ts` | Execution log append & query | ### Official Binance Skills (use for prices only) | Skill | 用途 | |-------|------| | **Binance Spot** | 行情价格查询、币种换算（**不要用 Spot 查余额，它只返回总额**） | | **Market Ranking** | 市场热度（扫描时参考） | | **Trading Signals** | 买卖信号（扫描时参考） | | **Token Details** | Token 基本信息、价格 | **查账户资产明细 → `node {baseDir}/bin/earn-api.ts balance`** **查价格/行情 → Binance Spot skill** **不要用 Spot skill 查余额 — 它只返回 BTC 总额，没有资产明细。** All scripts output JSON to stdout. Errors go to stderr with non-zero exit code. All timestamps use UTC. ## Routing **First use** (`~/passive-income-claw/user-profile.md` does not exist): → Read `{baseDir}/setup.md` **User triggers scan** ("scan", "what's available", "recommend", cron job): → Read `{baseDir}/scan.md` — full-path scan: direct earn + borrow-to-earn, all candidates scored and sorted **User triggers execution** ("buy #1", "execute", "redeem"): → Read `{baseDir}/execute.md` **User asks about borrow-to-earn details** ("how does borrowing work", "explain #4"): → Read `{baseDir}/path-analysis.md` **User wants to update settings** ("change my limit", "switch to auto"): → `node {baseDir}/bin/profile.ts dump` → show current → collect changes → `profile.ts set` **User asks execution history** ("what did you execute"): → `node {baseDir}/bin/log.ts recent 20` → If no entries: "No executions recorded yet." **Before all write operations**: run `node {baseDir}/bin/auth-check.ts` first.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)
Skill: katrina-jpg/crypto-trading-bot-playbook (version 1.0.0)

# Crypto Trading Bot Development Playbook ## Overview Learn how to build and sell crypto trading bots for consistent profits. --- ## Chapter 1: Types of Trading Bots ### 1.1 Signal Bots - Receive TradingView signals - Execute trades automatically - Connect to exchanges via API ### 1.2 Grid Trading - Buy low, sell high automatically - Profit from volatility - Set range and grid size ### 1.3 Arbitrage Bots - Exploit price differences between exchanges - Cross-exchange arbitrage - Triangular arbitrage ### 1.4 Portfolio Rebalancing - Maintain target allocation - Auto-rebalance on intervals - Dollar-cost averaging (DCA) --- ## Chapter 2: Technical Setup ### Required Skills - Python programming - API integration (Binance, Bybit, OKX) - Database management - Cloud deployment ### Tech Stack - Python + CCXT library - PostgreSQL/MySQL - AWS/DigitalOcean - Telegram for notifications --- ## Chapter 3: Development Steps 1. Design your strategy 2. Code the bot 3. Backtest on historical data 4. Paper trade for 1 month 5. Deploy to production 6. Monitor and optimize --- ## Chapter 4: Pricing Your Bot | Type | Price | |------|-------| | Basic Signal Bot | $100-300 | | Grid Trading Bot | $300-800 | | Advanced Strategy | $1,000-3,000 | | Monthly Maintenance | $100-300/mo | --- ## Chapter 5: Marketing - Telegram groups - Crypto Twitter - YouTube tutorials - Reddit r/cryptocurrency --- ## Risk Warning Trading involves risk. Always test thoroughly before using real money. --- © 2026 Crypto Bot Playbook


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: dxarch1980/wyckoff-stock (version 1.0.0)

--- name: wyckoff-stock description: A股诊股工具，基于Wyckoff 2.0方法论分析股票。支持获取实时K线数据、技术指标计算、趋势分析、支撑阻力识别、Wyckoff结构判断、风险收益评估。 metadata: inputs: - name: stock_code type: string required: true description: A股股票代码，如 601985、000001 - name: days type: number required: false default: 250 description: 分析用的K线天数，默认250天 outputs: - name: report type: object description: 完整诊股报告JSON --- # A股诊股 Skill (Wyckoff 2.0) ## 功能概述 本 Skill 基于 **Wyckoff 2.0** 方法论，对 A 股进行技术分析，包括： - 📊 **数据获取** - 通过 efinance 获取 K 线数据 - 📈 **趋势分析** - 均线系统、趋势判断 - 🔍 **Wyckoff 结构** - 识别积累/派发、判断所处阶段 - 📉 **成交量分析** - 放量/缩量信号 - ⚖️ **风险收益评估** - 支撑阻力、入场止损、目标价位 ## 使用方法 ### 基础用法 ``` 诊股 <股票代码> 示例：诊股 601985 ``` ### 调用脚本 ```bash python3 scripts/diagnose.py <股票代码> ``` ## 分析模块 ### 1. 价格结构 - 当前价格与均线关系 - 支撑阻力位识别（最近20日高低点） - 区间波动分析（最近120日） ### 2. 趋势判断 | 趋势 | 说明 | |------|------| | 上涨趋势 | 均线多头排列，价格在均线上方 | | 下跌趋势 | 均线空头排列，价格在均线下方 | | 震荡趋势 | 均线混乱，市场无明确方向 | ### 3. Wyckoff 五阶段 | 阶段 | 说明 | |------|------| | Phase A | 停止前期趋势，PS/SC 信号 | | Phase B | 筑底/筑顶，积累/派发区间 | | Phase C | 测试阶段，Spring/UT | | Phase D | 突破确认，趋势开始 | | Phase E | 趋势发展，趋势延续 | ### 4. 成交量分析 - 放量信号：当日成交量 > 5日均量 1.5倍 - 缩量信号：当日成交量 < 5日均量 0.7倍 ### 5. 风险收益评估 | 等级 | 风险收益比 | |------|-------------| | 优质 | ≥ 2:1 | | 一般 | 1:1 ~ 2:1 | | 较差 | < 1:1 | ## 输出格式 诊股输出包含： - 💰 价格数据（当前价、支撑阻力） - 📈 趋势分析（趋势状态、均线排列） - 🔍 Wyckoff结构（阶段、偏向、区间位置） - ⚖️ 风险收益（评估、上涨/下跌空间、比率） - 📋 总结（一句话概括） ## 脚本 - `scripts/diagnose.py` - 核心诊股脚本 ## 依赖 - `efinance` - A股数据获取（pip install efinance） - `python3` - 运行环境 ## 注意事项 ⚠️ 仅供参考，不构成投资建议！


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

--- name: Slack Integration description: Slack integration - Send messages, manage channels, and automate Slack workflows homepage: https://github.com/lukaizj/slack-integration-skill tags: - productivity - integration - slack - messaging requires: env: - SLACK_BOT_TOKEN files: - slack.py --- # Slack Integration Slack integration skill for OpenClaw. Send messages, manage channels, and automate Slack workflows. ## Setup 1. Create a Slack app at https://api.slack.com/apps 2. Get Bot User OAuth Token 3. Add required scopes: channels:read, chat:write, groups:read 4. Configure SLACK_BOT_TOKEN environment variable


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: kenee/mibatt-dietu-cli-agent (version 1.0.1)

--- name: mibatt-dietu-cli-agent description: Use this skill when you need to operate Dietu through its official CLI for A-share market queries, strategy screening, decision workflows, or agent automation. Covers GitHub device flow login, PAT usage, output formats, and stable command recipes. metadata: short-description: Operate Dietu CLI for A-share workflows --- # Dietu CLI Agent Use this skill when the task should be completed through the official `dietu` CLI instead of web UI clicks or backend-only scripts. Typical fit: - Query A-share market overviews, stock snapshots, indices, or search results - Run strategy lists and screening commands - Pull decision, trading, and review data from Dietu - Set up CLI authentication for human users or automation - Produce machine-readable CLI output for another agent or script ## Base URL Default API endpoint: `https://dietu-api.mibatt.com` Override via `--base-url`, `DIETU_BASE_URL`, or profile config. ## Quick rules - Prefer the public CLI package: `npm i -g @mibatt/dietu@latest` - For human login, use `dietu auth login` - For automation, prefer a PAT in `DIETU_ACCESS_TOKEN` - For agent consumption, prefer `--format json` - For user-facing pasted output, prefer `--format markdown` - For quick terminal inspection, prefer `--format table` - Use real `ts_code` symbols such as `600519.SH` or `000001.SZ` - If you do not know the command surface, run `dietu schema` - If connectivity or auth looks suspicious, run `dietu doctor` ## Authentication Read [references/auth.md](references/auth.md) when the task involves login, token sourcing, base URL switching, or PAT usage. Important: - The primary interactive path is GitHub device flow - The recommended automation path is PAT from `Settings / Access Tokens` - Do not invent outdated commands such as `dietu ping` or `dietu mcp start` ## Command recipes Read [references/commands.md](references/commands.md) when you need concrete command sequences for: - market - research - decision - trading - review - schema and doctor ## Working style - Start with the smallest command that can answer the task - Add `--format json` before doing downstream parsing or summarization - Preserve the user's chosen `--base-url`, `--profile`, or token source - For commands that require an account, explicitly provide `--account <id>` - If the task spans multiple CLI calls, keep outputs structured and consistent ## Non-goals - Do not call internal Python scripts as the primary interface when the CLI already exposes the capability - Do not assume browser-only login or password login is the preferred path - Do not treat short-lived JWT copied from local profile as the recommended long-term automation credential


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: guohongbin-git/travel-cn (version 1.0.0)

--- name: travel-cn description: 旅行信息查询 - 去哪儿/携程/飞猪数据查询（Expedia 中国版） metadata: openclaw: emoji: "✈️" category: "travel" tags: ["travel", "qunar", "ctrip", "fliggy", "china", "booking"] --- # 旅行信息查询 去哪儿/携程/飞猪数据查询。 ## 功能 - ✈️ 机票查询 - 🏨 酒店预订 - 🚄 火车票 - 🎫 景点门票 - 📅 行程规划 ## 平台对比 | 平台 | 机票 | 酒店 | 火车 | 特点 | |------|-----|------|------|------| | **携程** | ✅ | ✅ | ✅ | 全能 | | **去哪儿** | ✅ | ✅ | ✅ | 比价 | | **飞猪** | ✅ | ✅ | ❌ | 阿里系 | | 12306 | ❌ | ❌ | ✅ | 官方 | ## 机票查询 ### 携程 API ```bash # 需要合作伙伴资质 curl "https://api.ctrip.com/flight/search?from=SHA&to=PEK&date=2026-02-20" ``` ### 爬虫方案 ```python # 使用 selenium pip install selenium from selenium import webdriver driver = webdriver.Chrome() driver.get("https://flight.qunar.com/") ``` ## 酒店查询 ### 携程 API ```bash curl "https://api.ctrip.com/hotel/search?city=上海&checkin=2026-02-20" ``` ## 火车票查询 ### 12306（官方） ```bash # 使用 12306 API 封装 pip install py12306 from py12306 import Py12306 client = Py12306() trains = client.query("上海", "北京", "2026-02-20") ``` ## 使用场景 ### 1. 商务出行 - 机票/酒店比价 - 行程优化 - 费用控制 ### 2. 旅行规划 - 景点推荐 - 路线规划 - 预算管理 ### 3. 价格监控 - 降价提醒 - 价格趋势 - 最佳购买时机 ## 快速脚本 ```bash # 查询机票 ./scripts/flight-search.sh --from 上海 --to 北京 --date 2026-02-20 # 查询酒店 ./scripts/hotel-search.sh --city 上海 --checkin 2026-02-20 # 查询火车票 ./scripts/train-search.sh --from 上海 --to 北京 --date 2026-02-20 ``` ## 注意事项 1. **API 限制**: 需要合作伙伴资质 2. **爬虫风险**: 可能被封 IP 3. **价格变化**: 实时波动 --- *版本: 1.0.0*

path: package.json
content: {
  "name": "travel-cn",
  "version": "1.0.0",
  "description": "旅行信息查询 - 去哪儿/携程/飞猪数据查询",
  "keywords": ["travel", "qunar", "ctrip", "china", "booking"],
  "author": "money-maker-ai"
}


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: xueyetianya/helm (version 3.0.1)

--- name: helm version: "3.0.1" author: BytesAgain homepage: https://bytesagain.com source: https://github.com/bytesagain/ai-skills license: MIT-0 tags: [helm, tool, utility] description: "Create, lint, template, and package Kubernetes Helm charts with checks. Use when scaffolding charts, linting templates, or packaging chart releases." --- # helm Create, lint, template, and package Kubernetes Helm charts with checks. Use when scaffolding charts, linting templates, or packaging chart releases. ## Commands ### `KUBECONFIG` Path to kubeconfig file ```bash scripts/script.sh KUBECONFIG ``` ### `create` Create a new chart scaffold ```bash scripts/script.sh create <chart> ``` ### `lint` Lint a chart for issues ```bash scripts/script.sh lint <chart> ``` ### `template` Render templates locally (--set key=val, --values file) ```bash scripts/script.sh template <chart> [opts] ``` ### `list` List installed releases ```bash scripts/script.sh list [namespace] ``` ### `status` Show release status and notes ```bash scripts/script.sh status <release> ``` ### `values` Show values (source: chart|deployed) ```bash scripts/script.sh values <chart> [source] ``` ### `repo-add` Add a chart repository ```bash scripts/script.sh repo-add <name> <url> ``` ### `repo-list` List configured repositories ```bash scripts/script.sh repo-list ``` ### `repo-update` Update all repository indexes ```bash scripts/script.sh repo-update ``` ### `search` Search repos and Artifact Hub ```bash scripts/script.sh search <keyword> ``` ### `package` Package chart into .tgz ```bash scripts/script.sh package <chart> [opts] ``` ### `history` Show release revision history ```bash scripts/script.sh history <release> ``` ### `rollback` Rollback to a previous revision ```bash scripts/script.sh rollback <release> [rev] ``` ### `diff` Compare chart with deployed release ```bash scripts/script.sh diff <chart> <release> ``` ## Requirements - helm - curl --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*


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