Generate photorealistic architectural renders from sketches, floor plans, and text using advanced AI-driven visualization.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install architecture-rendering
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install architecture-rendering using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
Architecture Rendering is a specialized capability within the Openclaw Skills ecosystem designed to empower architects, interior designers, and real estate professionals. By leveraging the each::sense AI, this skill converts conceptual text descriptions and hand-drawn sketches into high-fidelity, photorealistic visualizations. It handles complex lighting, material textures, and environmental contexts to produce professional-grade imagery for client presentations and marketing materials.
These Openclaw Skills bridge the gap between initial ideation and final visual delivery, allowing users to iterate on designs rapidly. Whether you need an interior room view or a massive urban masterplan, the system uses sophisticated algorithms to ensure structural accuracy and aesthetic appeal, significantly reducing the time required for traditional 3D modeling and rendering workflows.
To get started with these Openclaw Skills, you need an API key from eachlabs.ai. Set your environment variable and use the following curl command to generate your first render:
# Set your API Key
export EACHLABS_API_KEY='your_api_key_here'
# Generate a render
curl -X POST https://sense.eachlabs.run/chat \
-H "Content-Type: application/json" \
-H "X-API-Key: $EACHLABS_API_KEY" \
-H "Accept: text/event-stream" \
-d '{
"message": "Create a photorealistic exterior render of a modern minimalist house with floor-to-ceiling glass windows",
"mode": "max"
}'
The Architecture Rendering skill organizes data through a structured prompt hierarchy and specific render specifications. These Openclaw Skills use the following metadata taxonomy:
| Component | Description |
|---|---|
| Building Type | Residential, Commercial, Institutional, or Mixed-use |
| Architectural Style | Modern, Contemporary, Industrial, or Traditional |
| Environment | Urban, Suburban, Rural, or Landscape context |
| Aspect Ratios | 16:9 (Hero), 4:3 (Interior), 9:16 (Social), 1:1 (Site Plans) |
| Mode | max for production quality or eco for concept iteration |
| Persistence | session_id used for tracking multi-step design revisions |
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