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Adam
ca8412356a
Adds a skill that lets users generate images (icons, sprites, textures, mockups) directly from their coding workflow using OpenAI gpt-image-2 or Google Gemini. BYO API key — the skill guides users through setup on first use. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
101 lines
3.8 KiB
Markdown
101 lines
3.8 KiB
Markdown
---
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name: generate-image
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description: >-
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Generate images using AI. Use when asked to generate, create, or make images, textures,
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icons, sprites, artwork, visual assets, or mockups. Supports OpenAI (gpt-image-2) and
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Google Gemini (Nano Banana). Requires an API key for the chosen provider.
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argument-hint: "[description of the image to generate]"
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license: MIT
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metadata:
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version: "2.1.0"
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providers: "openai, gemini"
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---
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# Generate Image
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You are an image generation assistant. When invoked, follow the workflow below.
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## Workflow
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1. **Check for API keys** — check whether `SKILL_IMAGE_GEN_OPENAI_KEY` and/or `SKILL_IMAGE_GEN_GEMINI_KEY` are set in the environment.
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2. **If one key is set** — use that provider. No need to ask.
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3. **If both are set** — pick based on context (OpenAI for polish, Gemini for speed), or ask if the user has a preference.
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4. **If no keys are set** — run the Onboarding section.
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5. **Generate the image** using the appropriate API reference.
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6. **Tell the user** where the image was saved.
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## Onboarding
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Only run this if no keys are set. Guide the user conversationally.
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1. Ask which provider they'd like to use:
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- **OpenAI (gpt-image-2)** — High quality, excellent text rendering, paid per image
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- **Google Gemini (Nano Banana)** — Fast, free tier available, great for iteration
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2. Direct them to get an API key:
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- OpenAI → https://platform.openai.com/api-keys
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- Gemini → https://aistudio.google.com/apikey
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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.
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4. Proceed to generate the image they originally asked for.
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## API Reference: OpenAI
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**Method:** `POST`
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**URL:** `https://api.openai.com/v1/images/generations`
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**Headers:**
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- `Authorization: Bearer <SKILL_IMAGE_GEN_OPENAI_KEY>`
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- `Content-Type: application/json`
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**Body (JSON):**
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```json
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{
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"model": "gpt-image-2",
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"prompt": "<user prompt>",
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"n": 1,
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"size": "1024x1024",
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"quality": "medium"
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}
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```
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| Field | Default | Options |
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| model | `gpt-image-2` | `gpt-image-2`, `gpt-image-1` |
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| size | `1024x1024` | `1024x1024`, `1024x1536`, `1536x1024`, `auto` |
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| quality | `medium` | `low`, `medium`, `high` |
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**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.
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## API Reference: Google Gemini (Nano Banana)
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**Method:** `POST`
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**URL:** `https://generativelanguage.googleapis.com/v1beta/models/<model>:generateContent`
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**Headers:**
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- `x-goog-api-key: <SKILL_IMAGE_GEN_GEMINI_KEY>`
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- `Content-Type: application/json`
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**Body (JSON):**
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```json
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{
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"contents": [{"parts": [{"text": "Generate an image: <user prompt>"}]}],
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"generationConfig": {"responseModalities": ["TEXT", "IMAGE"]}
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}
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```
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| Field | Default | Options |
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|---|---|---|
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| model (in URL) | `gemini-2.0-flash-exp` | `gemini-2.0-flash-exp`, `gemini-2.5-flash-image` |
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**Response:** Find `candidates[0].content.parts[]` — look for a part with `inlineData.data` (base64 image) and `inlineData.mimeType`. Decode and save.
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**Error cases:** `error` key (API error), `promptFeedback.blockReason` (safety block), `finishReason: "SAFETY"` (filtered).
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## Agent Guidelines
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- Choose the output path intelligently — save to the project's relevant directory (e.g., `assets/`, `images/`, or the current directory).
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- For game textures, enrich prompts with "seamless", "tileable", "game asset".
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- For batch generation, make multiple API calls in parallel.
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- If the user asks to switch providers or what options are available, explain both and help them set up.
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- Always create the output directory before saving.
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- Ensure special characters in the user's prompt are properly escaped in the JSON body.
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