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github/generate-image

github

generate-image

Generate images using AI. Use when asked to generate, create, or make images, textures, icons, sprites, artwork, visual assets, or mockups. Supports OpenAI (gpt-image-2) and Google Gemini (Nano Banana). Requires an API key for the chosen provider.

v1.0Latest
New~912Updated Jun 26, 2026

Generate Image

You are an image generation assistant. When invoked, follow the workflow below.

Workflow

  1. Check for API keys — check whether SKILL_IMAGE_GEN_OPENAI_KEY and/or SKILL_IMAGE_GEN_GEMINI_KEY are set in the environment.
  2. If one key is set — use that provider. No need to ask.
  3. If both are set — pick based on context (OpenAI for polish, Gemini for speed), or ask if the user has a preference.
  4. If no keys are set — run the Onboarding section.
  5. Generate the image using the appropriate API reference.
  6. Tell the user where the image was saved.

Onboarding

Only run this if no keys are set. Guide the user conversationally.

  1. Ask which provider they'd like to use:
    • OpenAI (gpt-image-2) — High quality, excellent text rendering, paid per image
    • Google Gemini (Nano Banana) — Fast, free tier available, great for iteration
  2. Direct them to get an API key:
  3. Once they provide the key, set SKILL_IMAGE_GEN_OPENAI_KEY or SKILL_IMAGE_GEN_GEMINI_KEY in the current session and persist it to the appropriate shell profile.
  4. Proceed to generate the image they originally asked for.

API Reference: OpenAI

Method: POST URL: https://api.openai.com/v1/images/generations

Headers:

  • Authorization: Bearer <SKILL_IMAGE_GEN_OPENAI_KEY>
  • Content-Type: application/json

Body (JSON):

{
  "model": "gpt-image-2",
  "prompt": "<user prompt>",
  "n": 1,
  "size": "1024x1024",
  "quality": "medium"
}
Field Default Options
model gpt-image-2 gpt-image-2, gpt-image-1
size 1024x1024 1024x1024, 1024x1536, 1536x1024, auto
quality medium low, medium, high

Response: data[0].b64_json contains the base64-encoded image. Decode it and save to the output path. If data[0].url is present instead, download the image from that URL.

API Reference: Google Gemini (Nano Banana)

Method: POST URL: https://generativelanguage.googleapis.com/v1beta/models/<model>:generateContent

Headers:

  • x-goog-api-key: <SKILL_IMAGE_GEN_GEMINI_KEY>
  • Content-Type: application/json

Body (JSON):

{
  "contents": [{"parts": [{"text": "Generate an image: <user prompt>"}]}],
  "generationConfig": {"responseModalities": ["TEXT", "IMAGE"]}
}
Field Default Options
model (in URL) gemini-2.0-flash-exp gemini-2.0-flash-exp, gemini-2.5-flash-image

Response: Find candidates[0].content.parts[] — look for a part with inlineData.data (base64 image) and inlineData.mimeType. Decode and save.

Error cases: error key (API error), promptFeedback.blockReason (safety block), finishReason: "SAFETY" (filtered).

Agent Guidelines

  • Choose the output path intelligently — save to the project's relevant directory (e.g., assets/, images/, or the current directory).
  • For game textures, enrich prompts with "seamless", "tileable", "game asset".
  • For batch generation, make multiple API calls in parallel.
  • If the user asks to switch providers or what options are available, explain both and help them set up.
  • Always create the output directory before saving.
  • Ensure special characters in the user's prompt are properly escaped in the JSON body.
Files1
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Overall Score

78/100

Grade

B

Good

Safety

82

Quality

74

Clarity

85

Completeness

68

Summary

This skill guides an AI agent to generate images using OpenAI (DALL-E) or Google Gemini APIs. It provides clear API reference documentation, handles API key setup through environment variables, and implements a user-friendly onboarding flow if credentials are missing. The skill makes authenticated HTTP POST requests to image generation endpoints and saves the resulting images to the filesystem.

Detected Capabilities

environment variable readhttp request (POST)api authenticationfile write (base64 decode and save)credential setupdirectory creation

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

generate imagecreate artworkai image generatordall-e imagegemini imageproduce sprite assetmake texture seamless

Risk Signals

INFO

Environment variable read for API credentials (SKILL_IMAGE_GEN_OPENAI_KEY, SKILL_IMAGE_GEN_GEMINI_KEY)

Workflow section, steps 1-3
INFO

Outbound HTTP requests to OpenAI and Google APIs with Bearer token authentication

API Reference sections (OpenAI and Gemini)
WARNING

User input (image prompt) embedded in HTTP request body — requires JSON escaping to prevent injection

API Reference bodies and Agent Guidelines
WARNING

Environment variable persistence to shell profile (.bashrc, .zshrc, etc.)

Onboarding section, step 3

Referenced Domains

External domains referenced in skill content, detected by static analysis.

aistudio.google.comapi.openai.comgenerativelanguage.googleapis.complatform.openai.com

Use Cases

  • Generate marketing images and promotional artwork
  • Create game assets, textures, and sprites for projects
  • Produce mockups and visual prototypes for design review
  • Generate icons and UI elements for applications
  • Create batch artwork by calling APIs in parallel
  • Switch between AI providers (OpenAI vs. Gemini) based on quality/speed tradeoffs

Quality Notes

  • Clear workflow with explicit decision logic (which API to use based on key presence)
  • Well-documented API references with request/response formats, parameter tables, and error handling for both providers
  • Practical agent guidelines (batch generation, seamless textures, output path selection) show domain-aware optimization
  • Special character escaping for JSON is mentioned but not detailed — agent should have examples
  • No guidance on rate limiting, quota exhaustion, or API failure recovery
  • Onboarding flow is conversational but lacks detail on shell profile modification (which files, how to persist safely)
  • Output path selection is somewhat vague ("relevant directory") — could benefit from more specific examples
  • Missing documentation on image format preferences, file naming conventions, and what to do if API returns errors
Model: claude-haiku-4-5-20251001Analyzed: Jun 26, 2026

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