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ar-vr-design增强现实设计

Agent Skill

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

总安装

392

周安装

16

GitHub Stars

4

下载量

127
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:ar-vr-design(增强现实设计)
来源仓库:https://github.com/alphaonedev/openclaw-graph
仓库路径:skills/ar-vr-design
安装命令:
npx skills add https://github.com/alphaonedev/openclaw-graph --skill ar-vr-design
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/alphaonedev/openclaw-graph --skill ar-vr-design

简介

专注于增强现实与虚拟现实交互体验设计。ar-vr-design 属于开发类 Skill,可作为该场景下的辅助能力补充。

  • 支持 3D 模型导入导出及空间计算任务处理。
  • 适用于博物馆导览、电商商品可视化等沉浸式场景开发。
  • 需配合 GLTF/OBJ 格式解析器使用并验证运行环境依赖。
  • 涉及真实部署时应测试设备兼容性与性能表现。

SKILL.md

ar-vr-design

Purpose

This skill designs interactive AR/VR experiences by integrating 3D modeling, spatial computing, and UI optimization, enabling creation of immersive environments for applications like virtual training or augmented overlays.

When to Use

Use this skill for projects requiring 3D asset manipulation, spatial interactions, or VR-specific UI tweaks, such as developing a virtual museum tour or AR product visualization in e-commerce apps.

Key Capabilities

  • Import and export 3D models in formats like GLTF or OBJ using built-in parsers.
  • Perform spatial computing tasks, such as room-scale mapping with algorithms for occlusion and collision detection.
  • Optimize UI for AR/VR devices, including rendering adjustments for headsets like Oculus or HoloLens to reduce latency below 20ms.
  • Simulate user interactions in a virtual environment to test gesture controls or haptic feedback.

Usage Patterns

To accomplish tasks, follow these steps: First, initialize a project with required configs; then, build and manipulate 3D assets; next, apply spatial computing for interactions; finally, optimize and simulate. Always set environment variables for authentication, e.g., export SERVICE_API_KEY=your_key before running commands. For integration, wrap skill outputs in a main application loop.

Common Commands/API

Use the arvr-cli tool for core operations. Authenticate via $ARVR_API_KEY environment variable.

  • Command: arvr-cli init --project myvrapp --type vr

- Initializes a new VR project; add --ar flag for AR mode. - Example snippet: export ARVR_API_KEY=abc123 arvr-cli init --project myvrapp

  • API Endpoint: POST /api/vr/models

- Uploads a 3D model; requires JSON payload with {"model": "path/to/model.gltf", "scale": 1.5}. - Example snippet: curl -H "Authorization: Bearer $ARVR_API_KEY" -X POST -d '{"model": "asset.gltf"}' https://api.openclaw.com/api/vr/models

  • Command: arvr-cli optimize --input model.obj --device oculus

- Optimizes model for specific devices; outputs optimized file. - Example snippet: arvr-cli optimize --input scene.glb --device hololens

  • API Endpoint: GET /api/ar/spatial-map

- Retrieves spatial data; query with parameters like?roomSize=10x10. - Example snippet: curl -H "Authorization: Bearer $ARVR_API_KEY" https://api.openclaw.com/api/ar/spatial-map?roomSize=5x5

Config formats: Use JSON for project configs, e.g., {"assets": ["model1.obj"], "spatialSettings": {"gravity": 9.8}}.

Integration Notes

Integrate this skill into workflows by importing outputs into engines like Unity or Unreal. For example, after running arvr-cli init, copy generated files to a Unity project and reference them in scripts. Use $ARVR_API_KEY for API calls in custom code. To chain with other skills, pipe outputs via stdin/stdout, e.g., output from a 3D modeling skill into this one's input. Ensure compatibility by matching formats: always convert models to GLTF before integration.

Error Handling

Handle errors by checking exit codes from commands; for API calls, parse HTTP responses. Common issues:

  • Authentication failure: If $ARVR_API_KEY is invalid, commands return code 401—fix by verifying and exporting the correct key.
  • Invalid model format: Use arvr-cli validate --file model.obj; if it fails with code 400, convert the file using a tool like Blender.
  • Example snippet for error checking: response=$(curl...); if [$? -ne 0]; then echo "API error: $response"; fi

Always wrap API calls in try-catch blocks in scripts, e.g., in Python: try: requests.post(url) except Exception as e: log_error(e).

Concrete Usage Examples

  1. Design a simple AR overlay for a mobile app: First, run arvr-cli init --project ar-overlay --type ar. Then, upload a 3D model with curl -X POST -d '{"model": "overlay.glb"}' https://api.openclaw.com/api/vr/models. Optimize for mobile: arvr-cli optimize --input overlay.glb --device android. Finally, integrate the output into an Android app using Unity's AR Foundation.
  2. Create a VR simulation for training: Initialize with arvr-cli init --project vr-training --type vr. Add spatial mapping: curl https://api.openclaw.com/api/ar/spatial-map?roomSize=10x10. Build interactions: Use the API to simulate gestures, then test with arvr-cli simulate --project vr-training. Export and import into Unreal Engine for full deployment.

Graph Relationships

  • Related to cluster: ar-vr (e.g., shares tags with skills like ar-vr-development).
  • Connected via tags: ["ar-vr"] links to other AR/VR skills; ["design"] connects to ui-design and 3d-modeling skills.
  • Dependencies: Requires outputs from 3d-modeling skills as inputs.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.36%
按下载量换算45

Claude

27.68%
按下载量换算35

Cursor

20.55%
按下载量换算26

Gemini CLI

10.19%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

未通过

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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