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Cad Agent

CAD Agent

clawd-maf0 来源安装数☆ 0 仓库 Stars

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install clawd-maf/cad-agent

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

CAD Agent

Give your AI agent eyes for CAD work.

Description

CAD Agent is a rendering server that lets AI agents see what they're building. Send modeling commands → receive rendered images → iterate visually.

Use when: designing 3D-printable parts, parametric CAD, mechanical design, build123d modeling

Architecture

Critical: All CAD logic runs inside the container. You (the agent) only:

  1. Send commands via HTTP
  2. View the returned images
  3. Decide what to do next
YOU (agent)                     CAD AGENT CONTAINER
─────────────                   ───────────────────
Send build123d code      →      Executes modeling
                         ←      Returns JSON status
Request render           →      VTK renders the model
                         ←      Returns PNG image
*Look at the image*
Decide: iterate or done

Never do STL manipulation, mesh processing, or rendering outside the container. The container handles everything — you just command and observe.

Setup

1. Clone the Repository
git clone https://github.com/clawd-maf/cad-agent.git
cd cad-agent
2. Build the Docker Image
docker build -t cad-agent:latest .

Or using docker-compose:

docker-compose build
3. Run the Server
# Using docker-compose (recommended)
docker-compose up -d

# Or using docker directly
docker run -d --name cad-agent -p 8123:8123 cad-agent:latest serve
4. Verify Installation
curl http://localhost:8123/health
# Should return: {"status": "healthy", ...}

Docker-in-Docker caveat: In nested container environments (e.g., Clawdbot sandbox), host networking may not work—curl localhost:8123 will fail even though the server binds to 0.0.0.0:8123. Use docker exec cad-agent python3 -c "..." commands instead. On a normal Docker host, localhost access works fine.

Workflow

1. Create Model
curl -X POST http://localhost:8123/model/create \
  -H "Content-Type:...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/clawd-maf/cad-agent
Version
—
Commit
6d213ded98117e4a609b3ef296a48d25bb263a1c
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

来源内容

SKILL.md
# CAD Agent

> Give your AI agent eyes for CAD work.

## Description

CAD Agent is a rendering server that lets AI agents see what they're building. Send modeling commands → receive rendered images → iterate visually.

**Use when:** designing 3D-printable parts, parametric CAD, mechanical design, build123d modeling

## Architecture

**Critical:** All CAD logic runs inside the container. You (the agent) only:
1. Send commands via HTTP
2. View the returned images
3. Decide what to do next

```
YOU (agent)                     CAD AGENT CONTAINER
─────────────                   ───────────────────
Send build123d code      →      Executes modeling
                         ←      Returns JSON status
Request render           →      VTK renders the model
                         ←      Returns PNG image
*Look at the image*
Decide: iterate or done
```

**Never** do STL manipulation, mesh processing, or rendering outside the container. The container handles everything — you just command and observe.

## Setup

### 1. Clone the Repository

```bash
git clone https://github.com/clawd-maf/cad-agent.git
cd cad-agent
```

### 2. Build the Docker Image

```bash
docker build -t cad-agent:latest .
```

Or using docker-compose:

```bash
docker-compose build
```

### 3. Run the Server

```bash
# Using docker-compose (recommended)
docker-compose up -d

# Or using docker directly
docker run -d --name cad-agent -p 8123:8123 cad-agent:latest serve
```

### 4. Verify Installation

```bash
curl http://localhost:8123/health
# Should return: {"status": "healthy", ...}
```

> **Docker-in-Docker caveat:** In nested container environments (e.g., Clawdbot sandbox), host networking may not work—`curl localhost:8123` will fail even though the server binds to `0.0.0.0:8123`. Use `docker exec cad-agent python3 -c "..."` commands instead. On a normal Docker host, localhost access works fine.

## Workflow

### 1. Create Model

```bash
curl -X POST http://localhost:8123/model/create \
  -H "Content-Type:...

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