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Cad Agent 1.0.0

作者 zhangyingzhuangk · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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版本数
在 OpenClaw 中安装
/install cad-agent-1-0-0
功能描述
Run build123d CAD code inside a container to create, render, and iteratively modify 3D models via HTTP with returned rendered images for visual feedback.
使用说明 (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

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: application/json" \
  -d '{
    "name": "my_part",
    "code": "from build123d import *\
result = Box(60, 40, 30)"
  }'

2. Render & View

# Get multi-view (front/right/top/iso)
curl -X POST http://localhost:8123/render/multiview \
  -d '{"model_name": "my_part"}' -o views.png

# Or 3D isometric
curl -X POST http://localhost:8123/render/3d \
  -d '{"model_name": "my_part", "view": "isometric"}' -o iso.png

Look at the image. Does it look right? If not, modify and re-render.

3. Iterate

curl -X POST http://localhost:8123/model/modify \
  -d '{
    "name": "my_part", 
    "code": "result = result - Cylinder(5, 50).locate(Pos(20, 10, 0))"
  }'

# Re-render to check
curl -X POST http://localhost:8123/render/3d \
  -d '{"model_name": "my_part"}' -o updated.png

4. Export

curl -X POST http://localhost:8123/export \
  -d '{"model_name": "my_part", "format": "stl"}' -o part.stl

Endpoints

Endpoint What it does
POST /model/create Run build123d code, create model
POST /model/modify Modify existing model
GET /model/list List models in session
GET /model/{name}/measure Get dimensions
POST /render/3d 3D shaded render (VTK)
POST /render/2d 2D technical drawing
POST /render/multiview 4-view composite
POST /export Export STL/STEP/3MF
POST /analyze/printability Check if printable

build123d Cheatsheet

from build123d import *

# Primitives
Box(width, depth, height)
Cylinder(radius, height)
Sphere(radius)

# Boolean
a + b   # union
a - b   # subtract
a & b   # intersect

# Position
part.locate(Pos(x, y, z))
part.rotate(Axis.Z, 45)

# Edges
fillet(part.edges(), radius)
chamfer(part.edges(), length)

Important

  • Don't bypass the container. No matplotlib, no external STL libraries, no mesh hacking.
  • Renders are your eyes. Always request a render after changes.
  • Iterate visually. The whole point is you can see what you're building.

Design File Safety

The project has safeguards against accidentally committing CAD outputs:

  • .gitignore blocks *.stl, *.step, *.3mf, etc.
  • Pre-commit hook rejects design files
  • User's designs stay local, never versioned

Links

安全使用建议
Before installing/running this skill, review the GitHub repository and Dockerfile it asks you to build. Confirm the server implementation: does it execute received Python code directly? Does the container drop privileges, disable or restrict network access, and avoid mounting sensitive host paths? Run the image in an isolated VM or sandbox, avoid binding to public interfaces, and do not run it as root or with host networking unless you understand the risks. If you cannot inspect the repo or Dockerfile, treat the service as untrusted: run it in disposable infrastructure only and do not provide any secrets or mount sensitive volumes.
功能分析
Type: OpenClaw Skill Name: cad-agent-1-0-0 Version: 1.0.0 The skill bundle describes a CAD rendering server that facilitates Remote Code Execution (RCE) by design, instructing the agent to send and execute arbitrary Python code (build123d) within a Docker container. While this behavior is aligned with the stated purpose of 3D modeling, the requirement to clone a remote repository (github.com/clawd-maf/cad-agent) and run a container that executes code strings via HTTP POST requests (/model/create) constitutes a high-risk capability. No explicit evidence of malicious intent, such as data exfiltration or backdoors, was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
Name/description (CAD rendering server for build123d) align with the runtime instructions: the SKILL.md tells you to build a Docker image and run an HTTP service that accepts build123d code and returns renders.
Instruction Scope
The service endpoints accept and execute arbitrary build123d Python code (POST /model/create and /model/modify). That is necessary for the stated purpose, but it means untrusted code will run inside the container. SKILL.md does not provide the server implementation or security guarantees (e.g., sandboxing, no-network, non-root user), so you cannot verify that the container prevents host compromise, network exfiltration, or file access.
Install Mechanism
There is no formal install spec in the skill bundle (instruction-only). The instructions direct you to clone and docker-build a GitHub repository (https://github.com/clawd-maf/cad-agent). Because the actual server code / Dockerfile are not included in the skill bundle here, you must inspect that external repository before building/running it.
Credentials
The skill requests no environment variables, credentials, or config paths — which is proportionate. However, lack of declared credentials doesn't remove risk: the running container could still access host resources or external networks depending on how you run it.
Persistence & Privilege
The skill isn't marked always:true and doesn't request persistent platform privileges. It does instruct creating and running a container bound to host port 8123, which is normal for a local service but could expose the server if misconfigured.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install cad-agent-1-0-0
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /cad-agent-1-0-0 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
CAD Agent 1.0.0: Initial release – AI agents can visually iterate on 3D CAD models via a rendering server. - Provides HTTP endpoints for model creation, modification, multi-view/image rendering, export, and printability analysis - All CAD logic and rendering handled securely inside the container; agents use only build123d code and view images - Supports iterated visual workflow: send modeling commands, see results as images, modify as needed - Export models in common formats (STL, STEP, 3MF); design safety tools prevent accidental versioning of outputs - Full setup and usage instructions included for Docker and docker-compose environments
元数据
Slug cad-agent-1-0-0
版本 1.0.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Cad Agent 1.0.0 是什么?

Run build123d CAD code inside a container to create, render, and iteratively modify 3D models via HTTP with returned rendered images for visual feedback. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 74 次。

如何安装 Cad Agent 1.0.0?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install cad-agent-1-0-0」即可一键安装,无需额外配置。

Cad Agent 1.0.0 是免费的吗?

是的,Cad Agent 1.0.0 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Cad Agent 1.0.0 支持哪些平台?

Cad Agent 1.0.0 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Cad Agent 1.0.0?

由 zhangyingzhuangk(@zhangyingzhuangk)开发并维护,当前版本 v1.0.0。

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