image-gen
GitHub通过后端API生成AI图像。支持gpt-image-2(文字渲染优)和nano-banana(参考图保真度高)模型。提交任务后返回jobId,需配合track_progress工具追踪进度。
触发场景
安装
npx skills add ChatCut-Inc/agent-plugin --skill image-gen -g -y
SKILL.md
Frontmatter
{
"name": "image-gen",
"description": "AI image generation via gpt-image-2 and nano-banana. Use when the user wants to generate or create an image \/ picture \/ still through the backend image-generation jobs.\n",
"user-invocable": true
}
Image Gen
Generate AI images through the backend generation API. Submit-only: creates a generation job and returns a jobId.
After submission, use track_progress tool to check status or wait for completion.
Model Selection
| Model | Strengths | Max refs |
|---|---|---|
gpt-image-2 |
Best text rendering, strongest prompt adherence | 10 |
nano-banana |
Strongest reference-image fidelity | 14 |
gpt-image-2is the default.nano-bananais the reference-heavy choice. Use it when reference-image fidelity matters more than text rendering, or when the user needs more than 10 reference images.
IMPORTANT: Before generating, READ the model's reference document for params, limits, and prompt tips:
gpt-image-2→ references/gpt-image-2.mdnano-banana→ references/nano-banana.md
Tool Params
| Param | Values | Default |
|---|---|---|
aspectRatio |
1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 4:5, 5:4, 21:9 |
16:9 |
imageSize |
1K, 2K, 4K |
1K |
quality |
low, medium, high, auto (gpt-image-2 only) |
high |
referenceAssetIds |
Array of project asset ids — backend resolves bytes server-side | — |
name |
Short descriptive asset name shown in the library | — |
count |
Number of images to generate (1–10, each becomes a separate job) | 1 |
Defaults
- Aspect ratio: 16:9. If the project composition is not 16:9, ASK the user which aspect ratio they want before generating.
- Size: 1K.
Ask Before Submit
- Never auto-upgrade size.
- Only pass
imageSize: "2K"or"4K"when the user explicitly asks. Warn that 2K/4K are EXPERIMENTAL and may be slower.
Reference Images
Use when the user provides source material to edit, blend, or use as visual guidance (e.g. "change the background", "combine these into a poster").
- Pass project asset ids via
referenceAssetIds. The backend fetches and encodes them server-side — never pull the asset bytes yourself. - When the user @-references an image asset, pass its id directly in
referenceAssetIds. - Formats accepted by backend: png, jpeg, webp, svg (auto-rasterized to png), heic, heif. Each ≤ 50MB.
Run
// Basic generation
submit_image({
model: "gpt-image-2",
prompt: "a cute orange cat",
name: "Cat",
});
// With quality (gpt-image-2 only)
submit_image({
model: "gpt-image-2",
prompt: "hero poster with bold title",
quality: "high",
name: "Hero Poster",
});
// With reference images — pass project asset ids; backend resolves bytes
submit_image({
model: "gpt-image-2",
prompt: "change background to beach",
referenceAssetIds: ["<assetId>"],
name: "Beach Edit",
});
// Reference-heavy with nano-banana
submit_image({
model: "nano-banana",
prompt: "composite poster",
referenceAssetIds: ["<id1>", "<id2>"],
name: "Composite",
});
// Multiple images
submit_image({
model: "gpt-image-2",
prompt: "product shots",
count: 3,
name: "Product",
});
After submission, call the track_progress tool: action=status jobIds=<jobId> to poll, action=wait jobIds=<jobId> to block until terminal.
Rules
- Always provide
namewith a short descriptive asset name. - Default to submit-only. If there is no follow-up task, stop after submit and tell the user the job was created.
- Generation costs credits. Before submitting, briefly tell the user what you're about to generate — especially when generating multiple images.
- Do not use this skill for job management. Use
track_progresstool for that.
版本历史
- f85076d 当前 2026-07-19 09:56


