SKILL·81C738

vgl

Bria-AI
Updated Today
63
5
63
View on GitHub
Metaaidesign

About

The vgl skill converts natural language image requests into structured VGL JSON for deterministic AI image generation. It provides explicit control over attributes like object placement, lighting, camera angles, and artistic style, ensuring reproducible outputs. Use it when you need precise scene composition for Bria FIBO models instead of relying on ambiguous prompts.

Quick Install

Claude Code

Recommended
Primary
npx skills add Bria-AI/bria-skill -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/Bria-AI/bria-skill
Git CloneAlternative
git clone https://github.com/Bria-AI/bria-skill.git ~/.claude/skills/vgl

Copy and paste this command in Claude Code to install this skill

Documentation

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

ModeInputOutputUse Case
GenerateText promptVGL JSONCreate new image from description
EditImage + instructionVGL JSONModify reference image
Edit_with_MaskMasked image + instructionVGL JSONFill grey masked regions
CaptionImage onlyVGL JSONDescribe existing image
RefineExisting JSON + editUpdated VGL JSONModify 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":

CategoryRewritten Instruction
Style changeTurn the image into the cartoon style.
Object attributeChange the dog's color to black and white.
Add elementAdd a wide-brimmed felt hat to the subject.
Remove objectRemove the book from the subject's hands.
Replace objectChange the rose to a bright yellow sunflower.
LightingChange the lighting from dark and moody to bright and vibrant.
CompositionChange the perspective to a wider shot.
Text changeChange the text "Happy Anniversary" to "Hello".
QualityRefine the image to obtain increased clarity and sharpness.

For Masked Region Edits

Reference "masked regions" or "masked area" as target:

IntentRewritten Instruction
Object generationGenerate a white rose with a blue center in the masked region.
ExtensionExtend the image into the masked region to create a scene featuring...
Background fillCreate the following background in the masked region: A vast ocean extending to horizon.
Atmospheric fillFill the background masked area with a clear, bright blue sky with wispy clouds.
Subject restorationRestore the area in the mask with a young woman.
Environment infillCreate 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

  1. Don't invent text - Keep text_render empty unless user provides exact text
  2. Don't over-describe - Max 5 objects, prioritize most important
  3. Match the mode - Use correct edit_instruction format for masked vs standard edits
  4. Preserve fidelity - Only change what's explicitly requested
  5. Be specific - Use concrete values ("85mm portrait lens") not vague terms ("nice camera")
  6. Null for irrelevant - Human-specific fields should be null for 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" \
  -H "User-Agent: BriaSkills/1.3.4" \
  -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

GitHub Repository

Bria-AI/bria-skill
Path: skills/vgl
0
agenagent-skillagent-skillsaiai-agentsclaude-code-skill
FAQ

Frequently asked questions

What is the vgl skill?

vgl is a Claude Skill by Bria-AI. Skills package instructions and resources that Claude loads on demand, so Claude can perform vgl-related tasks without extra prompting.

How do I install vgl?

Use the install commands on this page: add vgl to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.

What category does vgl belong to?

vgl is in the Meta category, tagged ai and design.

Is vgl free to use?

Yes. vgl is listed on AIMCP and free to install.

Related Skills

content-collections
Meta

This skill provides a production-tested setup for Content Collections, a TypeScript-first tool that transforms Markdown/MDX files into type-safe data collections with Zod validation. Use it when building blogs, documentation sites, or content-heavy Vite + React applications to ensure type safety and automatic content validation. It covers everything from Vite plugin configuration and MDX compilation to deployment optimization and schema validation.

View skill
polymarket
Meta

This skill enables developers to build applications with the Polymarket prediction markets platform, including API integration for trading and market data. It also provides real-time data streaming via WebSocket to monitor live trades and market activity. Use it for implementing trading strategies or creating tools that process live market updates.

View skill
creating-opencode-plugins
Meta

This skill helps developers create OpenCode plugins that hook into 25+ event types like commands, files, and LSP operations. It provides the plugin structure, event API specifications, and implementation patterns for JavaScript/TypeScript modules. Use it when you need to intercept, monitor, or extend the OpenCode AI assistant's lifecycle with custom event-driven logic.

View skill
sglang
Meta

SGLang is a high-performance LLM serving framework that specializes in fast, structured generation for JSON, regex, and agentic workflows using its RadixAttention prefix caching. It delivers significantly faster inference, especially for tasks with repeated prefixes, making it ideal for complex, structured outputs and multi-turn conversations. Choose SGLang over alternatives like vLLM when you need constrained decoding or are building applications with extensive prefix sharing.

View skill