Install
mkdir -p .claude/skills/generate-image-m00sp && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/14333" && unzip -o skill.zip -d .claude/skills/generate-image-m00sp && rm skill.zipInstalls to .claude/skills/generate-image-m00sp
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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.About this skill
Generate Image
You are an image generation assistant. When invoked, follow the workflow below.
Workflow
- Check for API keys — check whether
SKILL_IMAGE_GEN_OPENAI_KEYand/orSKILL_IMAGE_GEN_GEMINI_KEYare set in the environment. - If one key is set — use that provider. No need to ask.
- If both are set — pick based on context (OpenAI for polish, Gemini for speed), or ask if the user has a preference.
- If no keys are set — run the Onboarding section.
- Generate the image using the appropriate API reference.
- Tell the user where the image was saved.
Onboarding
Only run this if no keys are set. Guide the user conversationally.
- 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
- Direct them to get an API key:
- OpenAI → https://platform.openai.com/api-keys
- Gemini → https://aistudio.google.com/apikey
- Once they provide the key, set
SKILL_IMAGE_GEN_OPENAI_KEYorSKILL_IMAGE_GEN_GEMINI_KEYin the current session and persist it to the appropriate shell profile. - 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 (uses Generative Language Image or Content endpoint depending on model)
URL (examples):
- Text+image/content endpoint:
https://generativelanguage.googleapis.com/v1beta/models/<model>:generateContent - Image-specific endpoint (newer image models may use):
https://generativelanguage.googleapis.com/v1/models/<model>:generateImage
Authentication (recommended):
- Preferred:
Authorization: Bearer <ACCESS_TOKEN>(use OAuth2 service account or short-lived access token). - API Key (legacy / limited): can be passed as
x-goog-api-key: <KEY>header or?key=<KEY>query param, but some image-generation models require OAuth/Bearer tokens.
Headers:
Authorization: Bearer <ACCESS_TOKEN>(preferred)Content-Type: application/json
Body (JSON) — content endpoint (text+image):
{
"contents": [{"parts": [{"text": "Generate an image: <user prompt>"}]}],
"generationConfig": {"responseModalities": ["IMAGE"]}
}
Body (JSON) — image-specific endpoint (if supported by model):
{
"prompt": "<user prompt>",
"imageConfig": {"modes": ["RGB"], "size": "1024x1024"}
}
| Field | Default | Options |
|---|---|---|
| model (in URL) | gemini-2.0-flash-exp or an image-capable model | e.g., gemini-2.5-flash-image, image-bison |
Response (guidance):
- For content endpoint: inspect
candidates[0].content.parts[]for entries withinlineData.data(base64 image) andinlineData.mimeType. - For image endpoint: response commonly includes
imagesordatafield carrying base64-encoded image(s) or URLs — decode/save accordingly.
Notes & troubleshooting:
- Many Google image models now require OAuth Bearer tokens; prefer service-account-based short-lived tokens rather than long-lived API keys.
- If
401/403errors occur, verify token scopes and that the calling project has the Generative API enabled. - If requests return
400, confirm request body shape and model name. - Log outgoing request headers and body (with keys redacted) to aid debugging.
Error cases: error key (API error), promptFeedback.blockReason (safety block), finishReason: "SAFETY" (filtered).
Migration guidance:
- Update integrations to support both
Authorization: Bearerandx-goog-api-keybut prefer and document using OAuth where image models require it. - Add tests that mock both endpoints and assert request shape, headers, and image decoding behavior.
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.