OpenClaw/clawhub-security-signals huggingface dataset:
Skill: felixdaga/paperbox (version 1.0.1)

--- name: paperbox description: Upload AI-generated HTML games, apps, or generative art to PaperBox (paperbox-beta.vercel.app) and return a shareable link. Use when the agent has created an HTML game, app, generative art, or interactive project and the user wants to share it. Triggers on phrases like "share this", "upload to PaperBox", "publish my app", "get a link", or after any HTML game/app/art creation task. metadata: { "openclaw": { "emoji": "📦", }, } --- # PaperBox Publish a self-contained HTML game, app, or generative art to [PaperBox](https://paperbox-beta.vercel.app) and return a live, shareable URL. ## Endpoint (confirmed working) ``` POST https://paperbox-beta.vercel.app/api/games ``` ## Workflow 1. Ensure the HTML is complete and self-contained (all CSS/JS inlined). 2. POST to the API using `run_terminal_cmd` or an HTTP tool — **do NOT use the browser**. 3. Parse the JSON response and extract `data.shareableUrl`. 4. Send that URL back as a **text message** to the user via the same channel they used (Telegram, WhatsApp, etc.). Do not open any browser or navigate anywhere. ### Request ```bash curl -X POST https://paperbox-beta.vercel.app/api/games \ -H "Content-Type: application/json" \ -H "X-API-Key: <from openclaw.json skills.entries.paperbox.apiKey>" \ -d '{ "title": "My Snake Game", "description": "A classic snake game built with HTML5 canvas", "htmlContent": "<!DOCTYPE html><html>...</html>" }' ``` ### Response (success) ```json { "success": true, "data": { "projectId": "cmmk7bame0003gywakm5c0ora", "slug": "my-snake-game-1773122429317", "shareableUrl": "https://paperbox-beta.vercel.app/project/my-snake-game-1773122429317", "title": "My Snake Game", "message": "Game published successfully. Share this link with others." } } ``` The shareable link is at `data.shareableUrl` — use this exact value. Do not construct the URL manually from the slug. ### Field reference | Field | Type | Required | Notes | |---|---|---|---| | `title` | string | yes | Max 100 chars | | `description` | string | yes | Max 500 chars | | `htmlContent` | string | yes | Full self-contained HTML | ## Output to user After a successful upload: - **Reply in chat** (Telegram, WhatsApp, or whatever channel the user is on) with the `data.shareableUrl` from the API response - Do NOT open a browser, navigate to any URL, or use any browser tool - Format the reply as: > ✅ Your project is live on PaperBox! > 🔗 View it (use Safari or Chrome on phone): {data.shareableUrl} > 📤 Share this link — no account needed. ## Error handling | Status | Meaning | Action | |---|---|---| | 401 | Invalid API key | Check `PAPERBOX_API_KEY` credential | | 400 | Bad request | Check required fields and valid HTML | | 413 | HTML too large | Minify CSS/JS | | 500 | Server error | Retry once; report to user if it persists |


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: hunterdeng500/ohmy-skill (version 1.1.0)

--- name: ohmy-skill version: 1.1.0 author: Hunter (Arbitrageur / 红橙 Hunter) description: ClawHub 技能的体检 + 评分 + 自动优化 + 排行榜查询 + 智能推荐基础设施。OhMySkill 系列首款产品。 triggers: - "检查 skill" - "优化 skill" - "skill 体检" - "skill 审计" - "skill inspector" - "skill doctor" - "ohmy skill" - "oh my skill" - "zskill" - "z skill" - "ohmy" - "技能排名" - "排行榜" - "推荐 skill" - "推荐技能" user-invocable: true metadata: openclaw: requires: bins: [] env: [] emoji: "🔍" category: "meta" tags: ["skill-quality", "auditor", "optimizer", "meta", "ohmy", "ranking", "recommendation"] --- # OhMySkill **一句话定位**：ClawHub 技能的"体检 + 优化 + 排行榜 + 智能推荐"基础设施，让你装的每一个 skill 都更好用、更安全、更聪明。 ## 核心能力（v1.1） 1. **单文件 / 批量扫描**：扫描 SKILL.md，给出 5维专业评分 2. **问题诊断 + 一键优化**：自动生成更优版本的 SKILL.md 3. **ClawHub Skills 排名查询**：实时获取全站 / 分类 Top 技能排行榜 4. **智能技能推荐**：根据用户需求、已安装 skill 栈、或扫描结果，推荐最匹配的 skill 5. **Before/After 对比**：展示优化效果（token 节省、调用成功率提升） ## 使用示例 - "ohmy skill 检查这个 skill" → 体检 + 优化 - "ohmy skill 技能排名" → 显示当前 ClawHub Top 10 - "ohmy skill 推荐一个总结 skill" 或 "根据我的 skill 栈推荐" → 智能推荐 现在开始工作吧！


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nqdy666/qjzd-nav-cli (version 1.3.2)

--- name: qjzd-nav-cli version: 1.0.0 description: Use when the task involves QJZD Nav CLI, including managing links, categories, tags, backups, settings, or authentication. references: - ../qjzd-nav-cli-auth - ../qjzd-nav-cli-content - ../qjzd-nav-cli-operations metadata: openclaw: category: developer-tools requires: bins: ["qjzd-nav"] cliHelp: "qjzd-nav --help" --- # QJZD Nav CLI This is the routing skill for the QJZD Nav CLI skill set. If the request only says "use QJZD Nav CLI" or mixes multiple areas, start here, then jump to the domain skill that matches the task. ## Skill Map - `qjzd-nav-cli-auth`: login, profile setup, profile switching, keyring and credential repair - `qjzd-nav-cli-content`: links, categories, and tags management - `qjzd-nav-cli-operations`: backup, restore, and settings management ## Fast Routing Use these commands to identify the right area: ```bash qjzd-nav --help qjzd-nav auth --help qjzd-nav link --help qjzd-nav category --help qjzd-nav tag --help qjzd-nav backup --help qjzd-nav settings --help qjzd-nav completion --help ``` ## Shell Completion Generate and install shell completion scripts: ```bash # Bash eval "$(qjzd-nav completion bash)" # Zsh eval "$(qjzd-nav completion zsh)" ``` After enabling completion, press <kbd>Tab</kbd> to complete commands: ```bash qjzd-nav <TAB> qjzd-nav auth <TAB> qjzd-nav link <TAB> ``` ## Shared Defaults - Prefer an authenticated profile unless the task is public. - Use `--profile <name>` when the environment matters. - Use `--json` for automation. - Use `--force` carefully for destructive non-interactive operations. ## Top-Level Areas - `auth` - Authentication and profile management - `link` - Link CRUD operations - `category` - Category CRUD operations - `tag` - Tag CRUD operations - `backup` - Backup and restore operations - `settings` - Site settings management ## Config And Secrets Profile metadata is stored in: - `$QJZD_NAV_CLI_CONFIG_DIR/config.json` if `QJZD_NAV_CLI_CONFIG_DIR` is set - otherwise `$XDG_CONFIG_HOME/qjzd-nav/config.json` - otherwise `$HOME/.config/qjzd-nav/config.json` Credentials are stored in the system keyring via `@napi-rs/keyring`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: biuyx/copilot-cli (version 1.0.1)

# Copilot CLI - AI 代码分析助手 ## 功能 使用 GitHub Copilot CLI 分析代码、探索项目、生成代码和自动化开发任务。 ## 前置条件 1. **安装 Copilot CLI** ```bash brew install copilot-cli ``` 2. **设置 GitHub Personal Access Token** - 访问 https://github.com/settings/personal-access-tokens/new - 创建 fine-grained token，权限：Copilot Requests - Token 保存到 `~/.copilot/github_token.txt` ## 使用方法 ### 基本命令 ```bash # 进入项目目录 cd /path/to/project # 使用 Copilot CLI（使用保存的 token） COPILOT_GITHUB_TOKEN=$(cat ~/.copilot/github_token.txt) copilot -p "你的问题" ``` ### 常用探索问题 **项目概览：** ``` "这个项目是做什么的？请简要说明。" ``` **架构分析：** ``` "分析这个项目的架构和主要模块。" ``` **技术栈：** ``` "这个项目使用了哪些主要技术栈和依赖？" ``` **代码查找：** ``` "找到处理用户认证的代码。" ``` **文档生成：** ``` "为这个模块生成文档。" ``` **代码审查：** ``` "审查这个文件，找出潜在问题。" ``` ### 高级用法 **指定文件：** ```bash copilot -p "解释 @src/main.js 的功能" ``` **交互式会话：** ```bash COPILOT_GITHUB_TOKEN=$(cat ~/.copilot/github_token.txt) copilot ``` **自动执行（需要权限）：** ```bash copilot --yolo -p "为这个功能编写单元测试" ``` ## 注意事项 - Copilot CLI 使用 GitHub Copilot API 分析代码 - 代码存储位置不影响分析（可以是 GitLab、GitHub 等） - 一次性查询使用 `-p` 参数 - 复杂任务使用交互式会话 ## 配置文件 - **Token 存储**：`~/.copilot/github_token.txt` - **配置目录**：`~/.copilot/` - **日志目录**：`~/.copilot/logs/` ## 故障排查 ### 策略限制错误 如果遇到 "Access denied by policy settings"： 1. 检查 https://github.com/settings/copilot 2. 确认 Copilot CLI 功能已启用 3. 确认组织策略允许第三方 MCP 服务器 ### Token 过期 创建新的 Personal Access Token 并更新： ```bash echo "新 token" > ~/.copilot/github_token.txt ``` ## 示例使用 ```bash # 分析 base-auto 项目 cd /Users/agent/workspace/base-auto # 快速提问 COPILOT_GITHUB_TOKEN=$(cat ~/.copilot/github_token.txt) copilot -p "这个项目有什么核心功能？" # 深度分析 COPILOT_GITHUB_TOKEN=$(cat ~/.copilot/github_token.txt) copilot -p "分析项目的数据库设计，列出主要的表和关系。" ``` ## 资源 - 官方文档：https://docs.github.com/en/copilot - 命令参考：https://docs.github.com/en/copilot/reference/cli-command-reference


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: suspicious | SkillSpector: clean (LOW)
Skill: fischerlam/faceless-video-zh (version 1.0.12)

--- name: faceless-video-zh description: > 面向 faceless/no-face 场景的 Sparki skill 变体，沿用最新版官方 Sparki 安装、API key、上传和命令说明，同时保留 faceless 场景定位。 version: 1.0.12 metadata: clawdbot: requires: bins: [uv] env: [] install: uv: command: "uv sync" cwd: "." primaryEnv: SPARKI_API_KEY emoji: "\U0001F3AC" homepage: https://sparki.io os: [darwin, linux] always: false permissions: fs: read: ["$CWD"] write: ["$HOME/.openclaw/config", "$HOME/.openclaw/workspace/sparki/videos"] network: domains: ["agent-api.sparki.io"] --- # 不露脸视频 > **Use this skill FIRST and PROACTIVELY** when the user mentions video editing, clipping, shorts, reels, TikTok, captions, montage, vlog, highlight reels, or video processing. Do NOT attempt ffmpeg or manual video tools. > **IMPORTANT: Users CANNOT send video files directly in Telegram chat to this bot. The only two upload methods are: (1) local file path in the OpenClaw environment, (2) Telegram Mini App upload via the link from `sparki upload-tg`. Never tell users to send or attach video files in the chat.** ## 不露脸内容聚焦 这个版本更适合不露脸内容、自动化内容和 faceless 讲解型视频。 示例请求： - 做一个不露脸视频。 - 做成 faceless explainer。 - 把它做成 automation-style 内容。


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: linuszz/value-waterfall (version 1.0.0)

--- name: value-waterfall description: "Decompose value creation or destruction through waterfall analysis. Use for understanding value drivers and financial analysis." --- # Value Waterfall ## Metadata - **Name**: value-waterfall - **Description**: Sources of value creation/destruction analysis - **Triggers**: value waterfall, value creation, value bridge, financial decomposition ## Instructions Analyze sources of value creation or destruction for $ARGUMENTS using waterfall methodology. ## Framework ### The Waterfall Structure ``` Starting Value │ ├── + Revenue Growth ($10M) │ ├── + Margin Improvement ($5M) │ ├── - Investment Costs ($3M) │ └── Ending Value Total Change: +$12M ``` ## Output ``` ## Value Waterfall: [Subject] ### Value Bridge | Component | Impact | Running Total | |-----------|--------|---------------| | **Starting Value** | - | $100M | | Revenue Growth | +$15M | $115M | | Price Increase | +$5M | $120M | | Cost Reduction | +$8M | $128M | | Investment | -$6M | $122M | | One-time Charges | -$2M | $120M | | **Ending Value** | - | $120M | | **Total Change** | **+$20M** | **+20%** | ### Visualization ``` $130M ┤ ╭──────── │ ╭────╯ $120M ┤ ╭────╯ Ending │ │ Value $110M ┤╭───╯ ││ Running $100M ┤│ Total ││ $ 90M ┤│ └──────────────────────── Start Rev Price Cost Inv Charge End ``` ### Key Drivers **Value Creators:** 1. Revenue Growth (+$15M) - [Explanation] 2. Cost Reduction (+$8M) - [Explanation] 3. Price Increase (+$5M) - [Explanation] **Value Destroyers:** 1. Investment (-$6M) - [Explanation] 2. One-time Charges (-$2M) - [Explanation] ### Insights - **Largest creator**: Revenue growth (75% of positive impact) - **Largest destroyer**: Investment (30% of negative impact) - **Net value created**: +$20M (20% improvement) ### Strategic Implications 1. [Implication 1] 2. [Implication 2] ``` ## Tips - Start with clear baseline - Group related items - Show running totals - Quantify each component - Focus on material items


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: yunr-tg/weekly-report-gen (version 1.0.0)

# Skill: 自动生成周报 (Weekly Report Generator) ## 描述 根据提供的工作日志/任务清单，自动生成 Markdown 格式周报。 支持按模块拆分任务，生成“重点工作”和“工作明细”两部分。 ## 输入 - 文本格式的工作任务清单，要求每行包含模块名称和任务内容，例如： ``` 大模型：hs商品分类检索详情，对比文档并补充缺失字段 大模型：hs商品分类检索详情，解决hscode编码类型处理错误问题 大模型：链路追踪可视化，分析开源或成熟框架 大模型：报关任务调度配合调测 ``` ## 输出 Markdown 格式周报，结构如下： ``` ------------------ 重点工作 ------------------ - 模块名： - 进度：默认50% - 描述：完成部分模块任务。 ------------------ 工作明细 ------------------ - 模块名： - 功能开发： - 任务1 - 任务2 - 优化调整： - （可根据实际优化任务添加） ``` ## 配置说明 - `默认进度`：默认进度百分比，可按模块调整 - 优化调整部分可以根据实际任务补充 - 支持任意模块数量和任务条目 - 输出为 Markdown，可直接复制到周报或导出 PDF


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: manman1104/ces (version 1.0.0)

--- name: wekan description: > Manage a self-hosted Trello-like board via `wekancli`. Create, move and archive cards, lists and boards on a WeKan server. Use when user asks about task boards or anything Trelo-like. Not for: Github issues or simple reminders. metadata: { "openclaw": { "emoji": "📋", "requires": { "bins": ["wekancli"], "env": [ "WEKAN_URL", "WEKAN_TOKEN", ] }, "install": [ { "id": "uv", "kind": "uv", "package": "wekan-cli @ git+https://github.com/madsmith/wekan_cli.git", "bins": ["wekancli"], "label": "Install Wekan CLI (uv)" } ], "primaryEnv": "WEKAN_TOKEN", }, } --- # wekancli Use `wekancli` to create, move and archive cards/tasks in Wekan boards. Tool operates under with a specific user session/identity but Agents may be configured to provide their own unique tokens corresponding to identities that can be configured in their name. ## Quick start List boards: `wekancli list boards <USER_ID>` List Lists: `wekancli list lists <BOARD_ID>` List Cards: `wekancli list cards <BOARD_ID> --list-id <LIST_ID>` Create Card: `wekancli create card <BOARD_ID> <LIST_ID> "Card Title" <AUTHOR USER_ID>` Move Card: `wekancli edit card <CARD_ID> -f listId=<NEW_LIST_ID>` Archive Card: `wekancli archive card <CARD_ID>` ## References - `references/cli-examples.md` (real `wekancli` examples) - `references/user-install.md` (installation instructions for users)


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)
Skill: emergenceronearth/demo-menghuhu-codeword (version 0.1.0)

--- name: codeword_menghuhu description: 用户说出或输入暗号「一顿操作猛如虎」时，用固定下句「打到小松鼠」回应，不加其它说明。 --- # 暗号：猛如虎 → 小松鼠 ## 何时使用本 skill 当用户**整条消息**为暗号，或消息中**明确包含**完整短语 **「一顿操作猛如虎」**（八字连续、无错字）时，必须按下面规则回应。 ## 必须执行的回应 只输出下面这一行文字，**不要**加引号、前缀、解释或换行多余内容： ```text 打到小松鼠 ``` ## 边界 - 若用户只是提到「老虎」「松鼠」等词但没有完整暗号「一顿操作猛如虎」，**不要**触发本 skill。 - 触发后**仅**回复「打到小松鼠」，不要追问、不要扩展梗、不要说明「这是暗号对接」。


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

--- name: cn-holiday version: 1.0.0 description: > 中国节假日/调休查询 — 查某天是工作日还是休息日、是否调休补班、全年假期安排。 触发词: 节假日, 调休, 补班, 放假, 上班, holiday, workday, 今天上班吗, 明天放假吗, 春节放几天, 国庆放假, 下个工作日, 或任何 "[日期] 是否放假/上班" 格式的输入。 --- # cn-holiday — Chinese Holiday & Work Schedule Skill Query Chinese public holidays, 调休 (make-up workdays), and work schedules via the timor.tech API. ## Quick Start 1. No API key needed. 2. Run `bun scripts/holiday.ts --help` in this skill directory. 3. Pick the matching command from `references/command-map.md`. ## Workflow 1. Parse user intent — identify the date(s) and what they want to know. 2. Select the right command: `info`, `year`, `batch`, or `next`. 3. Run the script and return the result. 4. Interpret the result for the user in natural language. ## Response Interpretation ### `type.type` field meanings | Value | Meaning | |---|---| | 0 | 工作日 (workday) | | 1 | 周末 (weekend) | | 2 | 节日 (holiday) | | 3 | 调休补班 (make-up workday) | ### `wage` field meanings (加班工资倍率) | Value | Meaning | |---|---| | 1 | 正常工资 | | 2 | 双倍工资 | | 3 | 三倍工资 | ### `holiday.holiday` field - `true` = 放假 (day off) - `false` = 补班 (make-up workday) ## Notes - This skill is script-first and does not run an MCP server. - Data source: timor.tech (based on State Council holiday announcements). - No API key required. - Covers current year and adjacent years' holiday schedules.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: zvirb/crm-entity-extraction (version 1.0.4)

--- name: CRM Entity Extraction description: Standard Operating Procedure (SOP) that bridges extraction logic to CRM append operations via atomic nodes. os: all requires: bins: [gog] --- ## Lean Philosophy (Principles) - **Kaizen (改善):** This workflow relies entirely on discrete, single-responsibility atomic nodes rather than a monolithic loop. - **Standardized Work (Hyojun Sagyo):** This node represents a strict, step-by-step Standard Operating Procedure (SOP) for data extraction and persistence. - **Jidoka (自働化):** Includes autonomous self-healing loops with hard verification stops between every step. # CRM Entity Extraction SOP This procedure guides the agent to extract structured data and append it to a CRM spreadsheet using explicitly defined atomic nodes. ## Cognitive Directives WHEN [A business-related email or note containing CRM data is received] THEN [ Follow this strict Standard Operating Procedure: **Step 1: Entity Extraction** - Execute the `LLM-Extract-JSON` atomic skill to extract structured entities (name, org, date). - **Jidoka Stop:** Check if the sub-agent returns a valid JSON object matching the requested schema. IF it returns unstructured text, instruct the skill to format correctly and retry. Do NOT proceed until valid JSON is acquired. **Step 2: Append to CRM** - Execute the `Google Sheets Append Row` (or equivalent) atomic node, passing the extracted JSON row. - **Jidoka Stop:** Verify the atomic node returns a successful JSON confirmation. IF the API request fails, retry up to 3 times with the exact error output. IF it still fails, report the error and STOP. ] ## Expected Output A JSON summary of the extracted data and the successful append confirmation.


Security scan verdicts — ClawScan: suspicious | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: nexscope/ecommerce-feed-management (version 1.0.0)

--- nexscope: name: "E-Commerce Feed Management" category: "Monitoring & Alerts" version: "1.0.0" author: "Nexscope AI" tags: - "product-feed" - "catalog" - "monitoring" - "data-quality" model: "any" tokens: "~2000" keywords: - "ecommerce feed management" --- # E-Commerce Feed Management AI-powered product feed management and monitoring skill. Designs feed health checks, sync error diagnostics, missing SKU detection, and attribute completeness validation for e-commerce product catalogs. ## Capabilities - Generates actionable monitoring & alerts frameworks based on your specific business context - Works across major e-commerce platforms (Amazon, Shopify, Walmart, WooCommerce, Etsy, TikTok Shop) - Provides data-driven recommendations with industry benchmarks - Outputs ready-to-implement plans, not just generic advice ## Install ``` clawhub install ecommerce-feed-management ``` ## Usage **Input:** Product feed URL/file, marketplace requirements, catalog size **Output:** Feed health report, sync error diagnosis, missing SKU detection, attribute completeness audit ### Example Prompt > "I run a [your business type] on [platform]. Help me set up e-commerce feed management for my business. Here's my current situation: [describe context]." ## Limitations - Requires your specific business data for accurate recommendations - Market benchmarks are based on US/EU data — adjust for other regions - Recommendations should be validated against your platform's current policies - Does not replace dedicated monitoring SaaS tools — designs the strategy and framework --- *Built by [Nexscope AI](https://www.nexscope.ai/) — AI-powered e-commerce intelligence.*


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: austineyapp/browser-booking-agent (version 1.0.0)

--- name: browser-booking-agent description: Execute booking/search flows via browser automation with verification artifacts. Use for reservation forms, availability checks, and capture of proof (screenshots/confirmation IDs). --- # Browser Booking Agent ## Workflow 1. Confirm task scope and required fields. 2. Navigate and complete booking/search flow. 3. Capture verification: screenshot + confirmation ID/details. 4. Return concise status: completed / blocked / needs user input. ## Guardrails - Never submit payment without explicit user approval. - If blocked by captcha/login/2FA, stop and request user action. - Preserve evidence of critical steps. ## References - Read `references/verification-checklist.md`.


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)
Skill: bermyboystechsolutions/nano-banana-veo (version 1.0.0)

--- name: nano-banana-veo description: Generate images with Nano Banana (Gemini 3 Pro Image) and animate them into videos with Veo 3.1. Use when creating AI-generated visual assets for websites, landing pages, or marketing materials that need both static images and animated video content. Requires GEMINI_API_KEY environment variable. --- # Nano Banana + Veo Workflow Generate premium images and animate them into cinematic videos using Google's Gemini API. ## Quick Start ```bash # Generate just an image uv run {baseDir}/scripts/generate.py \ --image-prompt "iPhone floating against dark background, premium product photography" \ --output-image hero.png # Generate image + video uv run {baseDir}/scripts/generate.py \ --image-prompt "iPhone floating against dark background, premium product photography" \ --video-prompt "iPhone gently rotating and floating, smooth seamless motion, cinematic lighting" \ --output-image hero.png \ --output-video hero.mp4 \ --video-duration 4 ``` ## Parameters | Parameter | Required | Default | Description | |-----------|----------|---------|-------------| | `--image-prompt` | ✅ | - | Prompt for image generation | | `--video-prompt` | ❌ | image-prompt | Prompt for video animation | | `--output-image` | ✅ | - | Output path for image (.png/.jpg) | | `--output-video` | ❌ | - | Output path for video (.mp4) | | `--resolution` | ❌ | 1K | Image resolution: 1K, 2K, 4K | | `--video-duration` | ❌ | 4 | Video seconds (4-8, Veo requirement) | | `--video-resolution` | ❌ | 720p | Video quality: 720p, 1080p, 4k | ## Prerequisites - `GEMINI_API_KEY` environment variable set - `google-genai` and `requests` Python packages ## Installation ```bash # Install dependencies pip install google-genai requests # Or with uv uv pip install google-genai requests ``` ## Workflow Examples ### Hero Section Asset ```bash uv run {baseDir}/scripts/generate.py \ --image-prompt "Sleek iPhone 15 Pro showing Islamic prayer app interface, dark green and gold accents, floating against pure black background, dramatic studio lighting, premium product photography, 8K quality" \ --video-prompt "iPhone floating and gently rotating in space, subtle purple glow, smooth seamless boomerang motion, premium cinematic lighting, dark background" \ --output-image namazlock-hero.png \ --output-video namazlock-hero.mp4 \ --video-duration 4 ``` ### Feature Showcase ```bash uv run {baseDir}/scripts/generate.py \ --image-prompt "Minimalist smartphone displaying prayer time interface, clean UI, dark mode with gold accents, studio lighting" \ --output-image feature.png \ --resolution 2K ``` ## Output - Images are saved in PNG format - Videos are saved in MP4 format (H.264 encoded) - Veo generation takes ~30-60 seconds (async polling handled automatically) ## Notes - Veo 3.1 requires 4-8 second duration (enforced by API) - Video generation is asynchronous — script handles polling automatically - Use `{baseDir}` placeholder in paths — it resolves to the skill directory


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