Generate-Image
Generate-Image是一款code方向的AI技能,核心价值是>-,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
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mkdir -p ./skills/generate-image && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/generate-image/SKILL.md -o ./skills/generate-image/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# 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):**
{
"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.
🎯 Best For
- Developers scaffolding new projects
- Prototype builders
- Claude users
- GitHub Copilot users
- Software engineers
💡 Use Cases
- Bootstrapping React components
- Creating API route handlers
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Generate-Image to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Can I customize the generated output?
Yes — modify the skill's prompt instructions to match your project conventions and coding style.
Is Generate-Image compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Generate-Image?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Generate-Image?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/generate-image/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Using generated code without understanding
Understand what generated code does before shipping it to production.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.