muapi-floor-plan-rendering — Claude Code skill guide
Generates 2D architectural floor plans from text descriptions and converts them into realistic 3D isometric renderings. Useful for quick interior prototyping.
npx skills add SamurAIGPT/Generative-Media-Skills --skill muapi-floor-plan-rendering -a claude-code
npx skills add SamurAIGPT/Generative-Media-Skills --skill floor-plan-rendering -a claude-codeWhat muapi-floor-plan-rendering does
The workflow runs in two phases. First, it takes a text description and calls muapi image generate using the nano-banana-2 model. This creates a black-and-white 2D floor plan with labeled rooms. If you already have a diagram, supply it via base_plan_image to skip the drawing step.
Next, Phase B converts that 2D layout into an isometric 3D cutaway. The agent runs muapi image edit with the nano-banana-2-edit model, adding wooden flooring, modern furniture, and natural window lighting in 4:3 or 1:1 aspect ratio.
The agent relies directly on the muapi CLI. Without an active MUAPI_API_KEY set up through muapi auth configure, every image call will fail.
What it helps with
- generate a labeled 2D architectural blueprint from a text prompt
- transform a 2D floor plan image into a 3D isometric cutaway rendering
- visualize room layouts with furniture and lighting without CAD software
Example prompts for the agent
- Design a 2-bedroom modern apartment with an open kitchen and render it in 3D
- Convert my floor plan image into a realistic 3D architectural rendering
- Generate a 2D house blueprint in 4:3 ratio and produce the cutaway visualization
How to install muapi-floor-plan-rendering
1Skills CLI (Vercel)
npx skills add SamurAIGPT/Generative-Media-Skills --skill muapi-floor-plan-rendering -a claude-codenpx skills add SamurAIGPT/Generative-Media-Skills --skill floor-plan-rendering -a claude-code2Manually: put the files in place
~/.claude/skills/floor-plan-rendering/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/floor-plan-rendering/
1Skills CLI (Vercel)
npx skills add SamurAIGPT/Generative-Media-Skills --skill floor-plan-rendering -a codex2Manually: put the files in place
.agents/skills/floor-plan-rendering/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add SamurAIGPT/Generative-Media-Skills --skill floor-plan-rendering -a cursor2Manually: put the files in place
.cursor/skills/floor-plan-rendering/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install SamurAIGPT/Generative-Media-Skills floor-plan-rendering2Manually: put the files in place
.github/skills/floor-plan-rendering/SKILL.md1Skills CLI (Vercel)
npx skills add SamurAIGPT/Generative-Media-Skills --skill floor-plan-rendering -a gemini-cli2Platform CLI
gemini skills install https://github.com/SamurAIGPT/Generative-Media-Skills --path library/visual/floor-plan-renderingManually: put the files in place
.devin/skills/floor-plan-rendering/SKILL.mdThe legacy .windsurf/skills/ path still works
Skills CLI (Vercel)
npx skills add SamurAIGPT/Generative-Media-Skills --skill floor-plan-rendering -a opencodeClaude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
Step by step, with commands for each platform: How to install skills in Claude Code: five ways
Questions about muapi-floor-plan-rendering
How do I install muapi-floor-plan-rendering in Claude Code?
Run npx skills add SamurAIGPT/Generative-Media-Skills --skill muapi-floor-plan-rendering -a claude-code.
What does muapi-floor-plan-rendering do?
It automates floor plan creation by generating a 2D blueprint with muapi and converting it into a textured 3D isometric cutaway view.
What prerequisites are needed to run this skill?
You need the muapi CLI installed and configured with your MUAPI_API_KEY via muapi auth configure.
Source text
SKILL.md · MIT
---
slug: muapi-floor-plan-rendering
name: muapi-floor-plan-rendering
version: "1.0.0"
description: Design a 2D floor plan and convert it into a realistic, high-quality 3D architectural rendering.
acceptLicenseTerms: true
---
# Floor Plan Rendering
**Design a 2D floor plan and convert it into a realistic, high-quality 3D architectural rendering.**
## Inputs
| Name | Type | Required | Default | Description |
|:---|:---|:---|:---|:---|
| `floor_plan_description` | text | yes | — | Description of the floor plan (e.g. "a modern 2-bedroom apartment with a balcony and open kitchen"). |
| `base_plan_image` | image_url | no | — | Optional 2D floor plan image to use as a starting point. |
## Steps
### Phase A — 2D Floor Plan Design
If `{{base_plan_image}}` is not provided, submit the plan with ONE step to create the 2D blueprint:
1. **Floor Plan Generation** — `muapi image generate` (model=`nano-banana-2`):
- Prompt: `A professional, clean 2D architectural floor plan of {{floor_plan_description}}. Top-down view, technical drawing style, white background, black lines, labeled rooms (Living Room, Kitchen, Bedroom, etc.), high contrast, minimalist design.`
- Aspect ratio: 4:3 or 1:1
Present the 2D plan to the user for approval.
### Phase B — 3D Rendering
Once the 2D plan is ready, submit the plan to convert it into a realistic 3D visualization:
1. **3D Conversion** — `muapi image edit` (model=`nano-banana-2-edit`):
- Reference Image: The 2D plan from Phase A.
- Prompt: `A stunning, realistic 3D isometric cutaway rendering of the architectural floor plan. Photorealistic textures, warm wooden flooring, modern furniture, soft natural sunlight coming from windows, realistic shadows. High-end architectural visualization, cinematic look, 8k resolution, clean white studio background.`
- Aspect ratio: 4:3 or 1:1
After generation, present the final 3D rendering to the user.
## Trigger Keywords
`3d floor plan`, `architectural rendering`, `2d to 3d plan`, `house design`, `interior plan`
---
## Notes for the Executing Agent
- This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call `muapi` CLI commands. Use `muapi auth configure` first if `MUAPI_API_KEY` is unset.
- For model IDs without a CLI alias yet, fall back to the raw endpoint via `curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}'` and poll with `muapi predict wait <request_id>`.
- Substitute `{{input_name}}` placeholders with the user's actual inputs before issuing each call.
© SamurAIGPT · MIT · SamurAIGPT/Generative-Media-Skills