Agent Skills › 0xsline/OpenChatCut › image-gen

image-gen

GitHub

用于通过AI模型生成或创建图像的技能。支持gpt-image-2、nano-banana和MiniMax image-01，根据配置自动选择模型，处理提示词优化、参考图融合及参数配置。

src/agent/skills/image-gen/SKILL.md 0xsline/OpenChatCut

Trigger Scenarios

用户希望生成图片用户请求创建图像

Install

npx skills add 0xsline/OpenChatCut --skill image-gen -g -y

More Options

Non-standard path

npx skills add https://github.com/0xsline/OpenChatCut/tree/main/src/agent/skills/image-gen -g -y

Use without installing

npx skills use 0xsline/OpenChatCut@image-gen

指定 Agent (Claude Code)

npx skills add 0xsline/OpenChatCut --skill image-gen -a claude-code -g -y

安装 repo 全部 skill

npx skills add 0xsline/OpenChatCut --all -g -y

预览 repo 内 skill

npx skills add 0xsline/OpenChatCut --list

SKILL.md

Frontmatter

{
    "name": "image-gen",
    "description": "AI image generation via gpt-image-2, nano-banana, and MiniMax image-01. Use when the user wants to generate or create an image \/ picture \/ still.\n",
    "user-invocable": true
}

Image Gen

Generate AI images via submit_image (configured provider keys only). Prefer one clear still per request unless the user asked for variants.

Model Selection

Model	Reference	Strengths	Max refs
`gpt-image-2`	references/gpt-image-2.md	Best text rendering, strongest prompt adherence	16
`nano-banana`	references/nano-banana.md	Strongest reference-image fidelity	14
`image-01`	references/image-01.md	MiniMax stills / live style; one subject reference via R2	1

Default: gpt-image-2 when that key is on.
Reference-heavy → nano-banana.
User named MiniMax / only MiniMax image key on → image-01.
Respect capabilities: do not call a model whose vendor is not configured.

IMPORTANT: Before generating, READ the chosen model's reference.

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`	`512px`, `1K`, `2K`, `4K` (model-specific)	`1K`
`width` / `height`	GPT Image: 512–3840, /16; MiniMax: 512–2048, /8	—
`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; image-01 max 9)	`1`
`promptOptimizer`	MiniMax `image-01` only — `prompt_optimizer`	`false`
`seed`	MiniMax `image-01` only	—
`maskAssetId`, `background`, `moderation`, `inputFidelity`	GPT Image edit/output controls	—
`outputFormat`, `outputCompression`	GPT Image PNG/JPEG/WebP controls	PNG

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",
});

// MiniMax (optional single subject reference; R2 must be configured for refs)
submit_image({
  model: "image-01",
  prompt: "matte product bottle on marble, soft studio light",
  name: "Bottle still",
  promptOptimizer: false,
});

OpenChatCut’s submit_image may return completed pool assets synchronously depending on the provider path. If a jobId is returned, use track_progress; otherwise treat the asset ids in the result as done.

Rules

Always provide name with a short descriptive asset name.
Before submitting, briefly tell the user what you're about to generate — especially when generating multiple images.
Only call models whose vendor key is configured (capabilities prompt).