Vgl OpenClaw Skill - ClawHub
Do you want your AI agent to automate Vgl workflows? This free skill from ClawHub helps with web & frontend development tasks without building custom tools from scratch.
What this skill does
Maximum control over AI image generation — write structured VGL (Visual Generation Language) JSON that explicitly controls every visual attribute. Define exact object placement, lighting direction, camera angle, lens focal length, composition, color scheme, and artistic style as deterministic JSON instead of ambiguous natural language. Use this skill when you need reproducible image generation, precise control over scene composition, or want to convert a natural language image request into a structured JSON schema for Bria FIBO models. Triggers on requests for structured prompts, controllable generation, VGL JSON, deterministic image descriptions, or Bria/FIBO structured_prompt format.
Install
npx clawhub@latest install vglFull SKILL.md
Open original| name | description | license |
|---|---|---|
| vgl | Maximum control over AI image generation — write structured VGL (Visual Generation Language) JSON that explicitly controls every visual attribute. Define exact object placement, lighting direction, camera angle, lens focal length, composition, color scheme, and artistic style as deterministic JSON instead of ambiguous natural language. Use this skill when you need reproducible image generation, precise control over scene composition, or want to convert a natural language image request into a structured JSON schema for Bria FIBO models. Triggers on requests for structured prompts, controllable generation, VGL JSON, deterministic image descriptions, or Bria/FIBO structured_prompt format. | MIT |
Bria VGL — Full Control Over Image Generation
Define every visual attribute as structured JSON instead of hoping natural language gets it right. VGL (Visual Generation Language) gives you explicit, deterministic control over objects, lighting, camera settings, composition, and style for Bria's FIBO models.
Related Skill: Use bria-ai to execute these VGL prompts via the Bria API. VGL defines the structured control format; bria-ai handles generation, editing, and background removal.
Core Concept
VGL replaces ambiguous natural language prompts with deterministic JSON that explicitly declares every visual attribute: objects, lighting, camera settings, composition, and style. This ensures reproducible, controllable image generation.
Operation Modes
| Mode | Input | Output | Use Case |
|---|---|---|---|
| Generate | Text prompt | VGL JSON | Create new image from description |
| Edit | Image + instruction | VGL JSON | Modify reference image |
| Edit_with_Mask | Masked image + instruction | VGL JSON | Fill grey masked regions |
| Caption | Image only | VGL JSON | Describe existing image |
| Refine | Existing JSON + edit | Updated VGL JSON | Modify existing prompt |
JSON Schema
Output a single valid JSON object with these required keys:
1. short_description (String)
Concise summary of image content, max 200 words. Include key subjects, actions, setting, and mood.
2. objects (Array, max 5 items)
Each object requires:
{
"description": "Detailed description, max 100 words",
"location": "center | top-left | bottom-right foreground | etc.",
"relative_size": "small | medium | large within frame",
"shape_and_color": "Basic shape and dominant color",
"texture": "smooth | rough | metallic | furry | fabric | etc.",
"appearance_details": "Notable visual details",
"relationship": "Relationship to other objects",
"orientation": "upright | tilted 45 degrees | facing left | horizontal | etc."
}
Human subjects add:
{
"pose": "Body position description",
"expression": "winking | joyful | serious | surprised | calm",
"clothing": "Attire description",
"action": "What the person is doing",
"gender": "Gender description",
"skin_tone_and_texture": "Skin appearance"
}
Object clusters add:
{
"number_of_objects": 3
}
Size guidance: If a person is the main subject, use "medium-to-large" or "large within frame".
3. background_setting (String)
Overall environment, setting, and background elements not in objects.
4. lighting (Object)
{
"conditions": "bright daylight | dim indoor | studio lighting | golden hour | blue hour | overcast",
"direction": "front-lit | backlit | side-lit from left | top-down",
"shadows": "long, soft shadows | sharp, defined shadows | minimal shadows"
}
5. aesthetics (Object)
{
"composition": "rule of thirds | symmetrical | centered | leading lines | medium shot | close-up",
"color_scheme": "monochromatic blue | warm complementary | high contrast | pastel",
"mood_atmosphere": "serene | energetic | mysterious | joyful | dramatic | peaceful"
}
For people as main subject, specify shot type in composition: "medium shot", "close-up", "portrait composition".
6. photographic_characteristics (Object)
{
"depth_of_field": "shallow | deep | bokeh background",
"focus": "sharp focus on subject | soft focus | motion blur",
"camera_angle": "eye-level | low angle | high angle | dutch angle | bird's-eye",
"lens_focal_length": "wide-angle | 50mm standard | 85mm portrait | telephoto | macro"
}
For people: Prefer "standard lens (35mm-50mm)" or "portrait lens (50mm-85mm)". Avoid wide-angle unless specified.
7. style_medium (String)
"photograph" | "oil painting" | "watercolor" | "3D render" | "digital illustration" | "pencil sketch"
Default to "photograph" unless explicitly requested otherwise.
8. artistic_style (String)
If not photograph, describe characteristics in max 3 words: "impressionistic, vibrant, textured"
For photographs, use "realistic" or similar.
9. context (String)
Describe the image type/purpose:
"High-fashion editorial photograph for magazine spread""Concept art for fantasy video game""Commercial product photography for e-commerce"
10. text_render (Array)
Default: empty array []
Only populate if user explicitly provides exact text content:
{
"text": "Exact text from user (never placeholder)",
"location": "center | top-left | bottom",
"size": "small | medium | large",
"color": "white | red | blue",
"font": "serif typeface | sans-serif | handwritten | bold impact",
"appearance_details": "Metallic finish | 3D effect | etc."
}
Exception: Universal text integral to objects (e.g., "STOP" on stop sign).
11. edit_instruction (String)
Single imperative command describing the edit/generation.
Edit Instruction Formats
For Standard Edits (no mask)
Start with action verb, describe changes, never reference "original image":
| Category | Rewritten Instruction |
|---|---|
| Style change | Turn the image into the cartoon style. |
| Object attribute | Change the dog's color to black and white. |
| Add element | Add a wide-brimmed felt hat to the subject. |
| Remove object | Remove the book from the subject's hands. |
| Replace object | Change the rose to a bright yellow sunflower. |
| Lighting | Change the lighting from dark and moody to bright and vibrant. |
| Composition | Change the perspective to a wider shot. |
| Text change | Change the text "Happy Anniversary" to "Hello". |
| Quality | Refine the image to obtain increased clarity and sharpness. |
For Masked Region Edits
Reference "masked regions" or "masked area" as target:
| Intent | Rewritten Instruction |
|---|---|
| Object generation | Generate a white rose with a blue center in the masked region. |
| Extension | Extend the image into the masked region to create a scene featuring... |
| Background fill | Create the following background in the masked region: A vast ocean extending to horizon. |
| Atmospheric fill | Fill the background masked area with a clear, bright blue sky with wispy clouds. |
| Subject restoration | Restore the area in the mask with a young woman. |
| Environment infill | Create inside the masked area: a greenhouse with rows of plants under glass ceiling. |
Fidelity Rules
Standard Edit Mode
Preserve ALL visual properties unless explicitly changed by instruction:
- Subject identity, pose, appearance
- Object existence, location, size, orientation
- Composition, camera angle, lens characteristics
- Style/medium
Only change what the edit strictly requires.
Masked Edit Mode
- Preserve all visible (non-masked) portions exactly
- Fill grey masked regions to blend seamlessly with unmasked areas
- Match existing style, lighting, and subject matter
- Never describe grey masks—describe content that fills them
Example Output
{
"short_description": "A professional businesswoman in a navy blazer stands confidently in a modern glass office, holding a tablet. Natural daylight streams through floor-to-ceiling windows, creating a warm, productive atmosphere.",
"objects": [
{
"description": "A confident businesswoman in her 30s with shoulder-length dark hair, wearing a tailored navy blazer over a white blouse. She holds a tablet in her left hand while gesturing naturally with her right.",
"location": "center-right",
"relative_size": "large within frame",
"shape_and_color": "Human figure, navy and white clothing",
"texture": "smooth fabric, professional attire",
"appearance_details": "Minimal jewelry, well-groomed professional appearance",
"relationship": "Main subject, interacting with tablet",
"orientation": "facing slightly left, three-quarter view",
"pose": "Standing upright, relaxed professional stance",
"expression": "confident, approachable smile",
"clothing": "Tailored navy blazer, white silk blouse, dark trousers",
"action": "Presenting or reviewing information on tablet",
"gender": "female",
"skin_tone_and_texture": "Medium warm skin tone, healthy smooth complexion"
},
{
"description": "A modern tablet device with a bright display showing charts and graphs",
"location": "center, held by subject",
"relative_size": "small",
"shape_and_color": "Rectangular, silver frame with illuminated screen",
"texture": "smooth glass and metal",
"appearance_details": "Thin profile, business application visible on screen",
"relationship": "Held by businesswoman, focus of her attention",
"orientation": "vertical, screen facing viewer at slight angle",
"pose": null,
"expression": null,
"clothing": null,
"action": null,
"gender": null,
"skin_tone_and_texture": null,
"number_of_objects": null
}
],
"background_setting": "Modern corporate office interior with floor-to-ceiling windows overlooking a city skyline. Minimalist furniture in neutral tones, potted plants adding touches of green.",
"lighting": {
"conditions": "bright natural daylight",
"direction": "side-lit from left through windows",
"shadows": "soft, natural shadows"
},
"aesthetics": {
"composition": "rule of thirds, medium shot",
"color_scheme": "professional blues and neutral whites with warm accents",
"mood_atmosphere": "confident, professional, welcoming"
},
"photographic_characteristics": {
"depth_of_field": "shallow, background slightly soft",
"focus": "sharp focus on subject's face and upper body",
"camera_angle": "eye-level",
"lens_focal_length": "portrait lens (85mm)"
},
"style_medium": "photograph",
"artistic_style": "realistic",
"context": "Corporate portrait photography for company website or LinkedIn professional profile.",
"text_render": [],
"edit_instruction": "Generate a professional businesswoman in a modern office environment holding a tablet."
}
Common Pitfalls
- Don't invent text - Keep
text_renderempty unless user provides exact text - Don't over-describe - Max 5 objects, prioritize most important
- Match the mode - Use correct
edit_instructionformat for masked vs standard edits - Preserve fidelity - Only change what's explicitly requested
- Be specific - Use concrete values ("85mm portrait lens") not vague terms ("nice camera")
- Null for irrelevant - Human-specific fields should be
nullfor non-human objects
curl Example
curl -X POST "https://engine.prod.bria-api.com/v2/image/generate" \
-H "api_token: $BRIA_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"structured_prompt": "{\"short_description\": \"...\", ...}",
"prompt": "Generate this scene",
"aspect_ratio": "16:9"
}'
References
- Schema Reference - Complete JSON schema with all parameter values
- bria-ai - API client and endpoint documentation for executing VGL prompts