godot-asset-generator

jwynia/agent-skills · updated May 1, 2026

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$npx skills add https://github.com/jwynia/agent-skills --skill godot-asset-generator
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summary

Generate game assets using AI image generation APIs and prepare them for use in Godot 4.x. This skill covers the complete art pipeline from concept to Godot-ready sprites.

skill.md

Godot Asset Generator

Generate game assets using AI image generation APIs and prepare them for use in Godot 4.x. This skill covers the complete art pipeline from concept to Godot-ready sprites.

When to Use This Skill

Use this skill when:

  • Generating game sprites, characters, or objects using AI
  • Creating tilesets for platformers or top-down games
  • Generating UI elements, icons, or menu assets
  • Batch-generating animation frames
  • Preparing AI-generated assets for Godot import
  • Creating consistent asset sets with style guides

Do NOT use this skill when:

  • Creating 3D models or textures (2D assets only)
  • Manual pixel art or illustration (use art software)
  • Complex frame-by-frame animation (use animation tools)
  • Working with existing assets (use Godot directly)

Prerequisites

Required:

  • Deno runtime installed
  • At least one API key:
    • OPENAI_API_KEY for DALL-E 3
    • REPLICATE_API_TOKEN for Replicate (SDXL, Flux)
    • FAL_KEY for fal.ai

Optional:

  • ImageMagick for advanced image processing
  • Godot 4.x project for import file generation

Quick Start

Generate a Single Image

deno run --allow-env --allow-net --allow-write scripts/generate-image.ts \
  --provider dalle \
  --prompt "pixel art knight character, front view, 16-bit style, transparent background" \
  --output ./assets/knight.png

Batch Generate Animation Frames

deno run --allow-env --allow-net --allow-read --allow-write scripts/batch-generate.ts \
  --spec ./batch-spec.json \
  --output ./generated/

Create Sprite Sheet

deno run --allow-read --allow-write scripts/pack-spritesheet.ts \
  --input ./generated/*.png \
  --output ./sprites/player-sheet.png \
  --columns 4

Core Workflow

Phase 1: Style Definition

Define your art style before generating assets:

  1. Choose Art Style: Pixel art, hand-drawn, painterly, or vector
  2. Create Style Guide: Document colors, modifiers, and constraints
  3. Test Prompts: Generate samples to validate style consistency
{
  "style": "pixel-art",
  "resolution": 64,
  "palette": "limited-16-colors",
  "modifiers": "16-bit, no anti-aliasing, clean pixels"
}

Phase 2: Asset Generation

Generate assets using the appropriate provider:

  1. Single Assets: Use generate-image.ts for individual images
  2. Batch Assets: Use batch-generate.ts for multiple related assets
  3. Iterate: Refine prompts based on results

Phase 3: Post-Processing

Prepare raw AI output for game use:

  1. Background Removal: Extract sprites from backgrounds
  2. Color Correction: Normalize palette if needed
  3. Resize: Scale to exact game resolution
  4. Trim/Pad: Remove whitespace, add sprite padding
deno run --allow-read --allow-write scripts/process-sprite.ts \
  --input ./raw/knight.png \
  --output ./processed/knight.png \
  --remove-bg \
  --resize 64x64 \
  --filter nearest

Phase 4: Godot Integration

Prepare assets for Godot import:

  1. Pack Sprite Sheets: Combine frames into optimized sheets
  2. Generate Import Files: Create .import with optimal settings
  3. Configure Animations: Set up SpriteFrames resources

API Provider Selection

Provider Best For Quality Cost Speed
DALL-E 3 Consistency, high detail Excellent $$$ Medium
Replicate Style control, variations Very Good $$ Medium
fal.ai Fast iteration, testing Good $ Fast

DALL-E 3 (OpenAI)

Best for high-quality, consistent results. Excellent prompt following.

--provider dalle --model dall-e-3
  • Sizes: 1024x1024, 1792x1024, 1024x1792
  • Quality: standard, hd
  • Style: vivid, natural

Replicate (SDXL/Flux)

Best for style control and cheaper batch generation.

--provider replicate --model stability-ai/sdxl
  • More model options (SDXL, Flux, specialized)
  • Negative prompts supported
  • ControlNet and img2img available

fal.ai

Best for rapid iteration and testing prompts.

--provider fal --model fal-ai/flux/schnell
  • Fastest inference
  • Good for prototyping
  • Lower cost per image

Prompting by Art Style

Pixel Art

"pixel art [subject], 16-bit style, clean pixels, no anti-aliasing,
limited color palette, retro game sprite, transparent background"

Key modifiers: 16-bit, 8-bit, pixel art, retro, clean pixels, no anti-aliasing

Avoid: realistic, detailed, smooth, gradient

Hand-Drawn / Illustrated

"hand-drawn illustration of [subject], ink lines, watercolor texture,
sketch style, game art, white background"

Key modifiers: hand-drawn, illustration, ink lines, sketch, watercolor

Painterly / Concept Art

"digital painting of [subject], concept art style, painterly brush strokes,
dramatic lighting, game asset"

Key modifiers: digital painting, concept art, painterly, brush strokes

Vector / Flat Design

"flat design [subject], vector art style, clean edges, solid colors,
minimal shading, game icon, transparent background"

Key modifiers: flat design, vector, clean edges, solid colors, minimal

Script Reference

generate-image.ts

Generate a single image from any supported provider.

deno run --allow-env --allow-net --allow-write scripts/generate-image.ts [options]

Options:
  --provider <name>   Provider: dalle, replicate, fal (required)
  --prompt <text>     Generation prompt (required)
  --output <path>     Output file path (required)
  --model <name>      Specific model (optional, provider-dependent)
  --size <WxH>        Image size, e.g., 1024x1024 (default: 1024x1024)
  --style <name>      Style preset: pixel-art, hand-drawn, painterly, vector
  --negative <text>   Negative prompt (Replicate/fal only)
  --quality <level>   Quality: standard, hd (DALL-E only)
  --json              Output metadata as JSON
  -h, --help          Show help

batch-generate.ts

Generate multiple images from a specification file.

deno run --allow-env --allow-net --allow-read --allow-write scripts/batch-generate.ts [options]

Options:
  --spec <path>       Path to batch specification JSON (required)
  --output <dir>      Output directory (required)
  --concurrency <n>   Parallel requests (default: 2)
  --delay <ms>        Delay between requests (default: 1000)
  --resume            Resume from last successful
  --json              Output results as JSON
  -h, --help          Show help

Batch Spec Format:

{
  "provider": "replicate",
  "model": "stability-ai/sdxl",
  "style": "pixel-art",
  "basePrompt": "16-bit pixel art, game sprite, transparent background",
  "assets": [
    { "name": "player-idle", "prompt": "knight standing idle, front view" },
    { "name": "player-walk-1", "prompt": "knight walking, frame 1 of 4" },
    { "name": "player-walk-2", "prompt": "knight walking, frame 2 of 4" }
  ]
}

process-sprite.ts

Post-process generated images for game use.

deno run --allow-read --allow-write scripts/process-sprite.ts [options]

Options:
  --input <path>      Input image path (required)
  --output <path>     Output image path (required)
  --remove-bg         Remove background (make transparent)
  --resize <WxH>      Resize to dimensions
  --filter <type>     Resize filter: nearest, linear (default: nearest)
  --trim              Trim transparent whitespace
  --padding <n>       Add padding pixels
  --color-key <hex>   Color to make transparent (e.g., ff00ff)
  -h, --help          Show help

pack-spritesheet.ts

Pack multiple sprites into a sprite sheet.

deno run --allow-read --allow-write scripts/pack-spritesheet.ts [options]

Options:
  --input <pattern>   Input files (glob pattern, required)
  --output <path>     Output sprite sheet path (required)
  --columns <n>       Number of columns (default: auto)
  --padding <n>       Padding between sprites (default: 0)
  --power-of-two      Force power-of-two dimensions
  --metadata <path>   Output JSON metadata path
  -h, --help          Show help

Output Metadata:

{
  "image": "player-sheet.png",
  "size": { "width": 256, "height": 128 },
  "frames": [
    { 
how to use godot-asset-generator

How to use godot-asset-generator on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add godot-asset-generator
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jwynia/agent-skills --skill godot-asset-generator

The skills CLI fetches godot-asset-generator from GitHub repository jwynia/agent-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/godot-asset-generator

Reload or restart Cursor to activate godot-asset-generator. Access the skill through slash commands (e.g., /godot-asset-generator) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.860 reviews
  • James Gupta· Dec 28, 2024

    godot-asset-generator has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ganesh Mohane· Dec 16, 2024

    godot-asset-generator reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Lucas Farah· Dec 12, 2024

    Solid pick for teams standardizing on skills: godot-asset-generator is focused, and the summary matches what you get after install.

  • Mia Kapoor· Nov 19, 2024

    godot-asset-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Sakshi Patil· Nov 7, 2024

    I recommend godot-asset-generator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Liam Lopez· Nov 3, 2024

    We added godot-asset-generator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Chaitanya Patil· Oct 26, 2024

    Useful defaults in godot-asset-generator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Lucas White· Oct 22, 2024

    godot-asset-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Nia Jackson· Oct 10, 2024

    We added godot-asset-generator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Mia Nasser· Sep 21, 2024

    godot-asset-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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