Gal Davidi
作者:Gal Davidi更新日 2026-06-24全 4 バージョン · 最新版の公開日 2026-06-24vgl@clawhub_galbria/vgl
画像生成ビジュアル素材#Image Generation#Json#Prompt

AlphaMoatによると、2026-09時点でVglのダウンロード数は2,484、スター数は4で、AIスキル全体5,078件中4,113位、デザイン・メディアでは512件中401位です。

インストール数
106
ダウンロード数
2484
スター数
4
総合順位
#4,113
全体の上位 81% · デザイン・メディアの上位 79%
プラットフォームインストール数ダウンロード数スター数コメント
ClawHub ↗7424844-
SkillHub ↗10622654—

プラットフォームごとに集計方法と集計時点が異なります。

このスキルでできること

主文では生成、編集、マスク編集、キャプション、調整の各モードと、オブジェクト、背景、照明、美的表現、カメラ、スタイル、編集指示の JSON フィールドを定義しています。これは構造化プロンプトを作成するもので、画像を生成する機能ではありません。API 例と組み合わせるとプロンプト内容が Bria に送信される場合があります。使用前にオブジェクト属性、描画テキスト、編集範囲を確認し、意図しない対象や変更を防いでください。

資料公開日 2026-10-29

できること

  • 自然言語の画像依頼を VGL JSON 案に変換する
  • 指定画像向けの構造化編集指示を作る
  • JSON のオブジェクト、構図、テキスト、編集範囲を確認する

使う場面

  • Bria FIBO 向けの構造化プロンプトを準備するとき
  • 画像 API へプロンプト内容を送信することをユーザーが承認しているとき
  • 生成 JSON を使用前に項目ごとに確認できるとき

プロンプト例

スキルのドキュメントをもとに生成した例であり、実際の実行結果ではありません。

画像 API を呼び出さず場面説明を VGL 形式の JSON に変換する
参照画像用の編集 JSON を作り、維持・変更する範囲を明示する
JSON に未承認の文字や被写体属性が含まれていないか確認する

月次の推移

ダウンロード数2484
1415198925632026-03 · ダウンロード数 14942026-05 · ダウンロード数 18252026-06 · ダウンロード数 19212026-07 · ダウンロード数 22512026-08 · ダウンロード数 23802026-09 · ダウンロード数 248426-0326-09
スター数4
3452026-03 · スター数 42026-05 · スター数 42026-06 · スター数 42026-07 · スター数 42026-08 · スター数 42026-09 · スター数 426-0326-09

2026-09 から集計方法を変更し、同名スキルを作者ごとに分けて集計し、全スキルを対象にしました。破線は変更前の月で、変更後のデータとは直接比較せず、変更をまたぐ増減も計算していません。

月ダウンロード数前月比スター数
2026-092484—4
2026-082380+5.7%4
2026-072251+17.2%4
2026-061921+5.3%4
2026-051825—4
2026-031494—4

SKILL.md 原文

作者が公開した元のファイルをテキストのまま表示しています。AlphaMoat による編集や審査はしていません。リンクはクリックできません。コマンドは内容を確認してから実行してください。取得日 2026-10-23。

12 KB・ClawHub v1.2.2
---
name: vgl
description: 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.
license: MIT
metadata:
  author: Bria AI
  version: "1.3.4"
---

# Bria VGL — Full Control Over Image Generation
すべて表示(全 283 行)

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](../bria-ai/SKILL.md)** 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:

```json
{
  "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:
```json
{
  "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:
```json
{
  "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)
```json
{
  "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)
```json
{
  "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)
```json
{
  "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:
```json
{
  "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

```json
{
  "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

```bash
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](references/schema-reference.md)** - Complete JSON schema with all parameter values
- **[bria-ai](../bria-ai/SKILL.md)** - API client and endpoint documentation for executing VGL prompts

デザイン・メディアの人気スキル

データ月:2026-09 · ダウンロード数、スター数、インストール数は公開スキルレジストリ(ClawHub、SkillHub)から月単位で集計しています。詳しくはデータの方法論をご覧ください。