Ghcopilot Generate Image

---
name: generate-image
description: >-. Use when you need help with 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.
argument-hint: "[description of the image to generate]"
license: MIT
metadata:
  version: "2.1.0"
  providers: "openai, gemini"
---

# 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:
   - OpenAI → https://platform.openai.com/api-keys
   - Gemini → https://aistudio.google.com/apikey
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):**
```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):**
```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.