Skills
skills/jimliu/baoyu-skills/baoyu-imagine

baoyu-imagine

SKILL.md

Image Generation (AI SDK)

Official API-based image generation. Supports OpenAI, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), MiniMax, Jimeng (即梦), Seedream (豆包) and Replicate providers.

Script Directory

Agent Execution:

  1. {baseDir} = this SKILL.md file's directory
  2. Script path = {baseDir}/scripts/main.ts
  3. Resolve ${BUN_X} runtime: if bun installed → bun; if npx available → npx -y bun; else suggest installing bun

Step 0: Load Preferences ⛔ BLOCKING

CRITICAL: This step MUST complete BEFORE any image generation. Do NOT skip or defer.

Check EXTEND.md existence (priority: project → user):

# macOS, Linux, WSL, Git Bash
test -f .baoyu-skills/baoyu-imagine/EXTEND.md && echo "project"
test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-imagine/EXTEND.md" && echo "xdg"
test -f "$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md" && echo "user"

# PowerShell (Windows)
if (Test-Path .baoyu-skills/baoyu-imagine/EXTEND.md) { "project" }
$xdg = if ($env:XDG_CONFIG_HOME) { $env:XDG_CONFIG_HOME } else { "$HOME/.config" }
if (Test-Path "$xdg/baoyu-skills/baoyu-imagine/EXTEND.md") { "xdg" }
if (Test-Path "$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md") { "user" }
Result Action
Found Load, parse, apply settings. If default_model.[provider] is null → ask model only (Flow 2)
Not found ⛔ Run first-time setup (references/config/first-time-setup.md) → Save EXTEND.md → Then continue

CRITICAL: If not found, complete the full setup (provider + model + quality + save location) using AskUserQuestion BEFORE generating any images. Generation is BLOCKED until EXTEND.md is created.

Path Location
.baoyu-skills/baoyu-imagine/EXTEND.md Project directory
$HOME/.baoyu-skills/baoyu-imagine/EXTEND.md User home

EXTEND.md Supports: Default provider | Default quality | Default aspect ratio | Default image size | Default models | Batch worker cap | Provider-specific batch limits

Schema: references/config/preferences-schema.md

Usage

# Basic
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png

# With aspect ratio
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9

# High quality
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --quality 2k

# From prompt files
${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png

# With reference images (Google, OpenAI, Azure OpenAI, OpenRouter, Replicate, MiniMax, or Seedream 4.0/4.5/5.0)
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png

# With reference images (explicit provider/model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider google --model gemini-3-pro-image-preview --ref source.png

# Azure OpenAI (model means deployment name)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider azure --model gpt-image-1.5

# OpenRouter (recommended default model)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openrouter

# OpenRouter with reference images
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --provider openrouter --model google/gemini-3.1-flash-image-preview --ref source.png

# Specific provider
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai

# DashScope (阿里通义万象)
${BUN_X} {baseDir}/scripts/main.ts --prompt "一只可爱的猫" --image out.png --provider dashscope

# DashScope Qwen-Image 2.0 Pro (recommended for custom sizes and text rendering)
${BUN_X} {baseDir}/scripts/main.ts --prompt "为咖啡品牌设计一张 21:9 横幅海报，包含清晰中文标题" --image out.png --provider dashscope --model qwen-image-2.0-pro --size 2048x872

# DashScope legacy Qwen fixed-size model
${BUN_X} {baseDir}/scripts/main.ts --prompt "一张电影感海报" --image out.png --provider dashscope --model qwen-image-max --size 1664x928

# MiniMax
${BUN_X} {baseDir}/scripts/main.ts --prompt "A fashion editorial portrait by a bright studio window" --image out.jpg --provider minimax

# MiniMax with subject reference (best for character/portrait consistency)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A girl stands by the library window, cinematic lighting" --image out.jpg --provider minimax --model image-01 --ref portrait.png --ar 16:9

# MiniMax with custom size (documented for image-01)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic poster" --image out.jpg --provider minimax --model image-01 --size 1536x1024

# Replicate (google/nano-banana-pro)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate

# Replicate with specific model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana

# Batch mode with saved prompt files
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json

# Batch mode with explicit worker count
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4 --json

Batch File Format

{
  "jobs": 4,
  "tasks": [
    {
      "id": "hero",
      "promptFiles": ["prompts/hero.md"],
      "image": "out/hero.png",
      "provider": "replicate",
      "model": "google/nano-banana-pro",
      "ar": "16:9",
      "quality": "2k"
    },
    {
      "id": "diagram",
      "promptFiles": ["prompts/diagram.md"],
      "image": "out/diagram.png",
      "ref": ["references/original.png"]
    }
  ]
}

Paths in promptFiles, image, and ref are resolved relative to the batch file's directory. jobs is optional (overridden by CLI --jobs). Top-level array format (without jobs wrapper) is also accepted.

Options

Option Description
--prompt <text>, -p Prompt text
--promptfiles <files...> Read prompt from files (concatenated)
--image <path> Output image path (required in single-image mode)
--batchfile <path> JSON batch file for multi-image generation
--jobs <count> Worker count for batch mode (default: auto, max from config, built-in default 10)
--provider google|openai|azure|openrouter|dashscope|minimax|jimeng|seedream|replicate Force provider (default: auto-detect)
--model <id>, -m Model ID (Google: gemini-3-pro-image-preview; OpenAI: gpt-image-1.5; Azure: deployment name such as gpt-image-1.5 or image-prod; OpenRouter: google/gemini-3.1-flash-image-preview; DashScope: qwen-image-2.0-pro; MiniMax: image-01)
--ar <ratio> Aspect ratio (e.g., 16:9, 1:1, 4:3)
--size <WxH> Size (e.g., 1024x1024)
--quality normal|2k Quality preset (default: 2k)
--imageSize 1K|2K|4K Image size for Google/OpenRouter (default: from quality)
--ref <files...> Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate, MiniMax subject-reference, and Seedream 5.0/4.5/4.0. Not supported by Jimeng, Seedream 3.0, or removed SeedEdit 3.0
--n <count> Number of images
--json JSON output

Environment Variables

Variable Description
OPENAI_API_KEY OpenAI API key
AZURE_OPENAI_API_KEY Azure OpenAI API key
OPENROUTER_API_KEY OpenRouter API key
GOOGLE_API_KEY Google API key
DASHSCOPE_API_KEY DashScope API key (阿里云)
MINIMAX_API_KEY MiniMax API key
REPLICATE_API_TOKEN Replicate API token
JIMENG_ACCESS_KEY_ID Jimeng (即梦) Volcengine access key
JIMENG_SECRET_ACCESS_KEY Jimeng (即梦) Volcengine secret key
ARK_API_KEY Seedream (豆包) Volcengine ARK API key
OPENAI_IMAGE_MODEL OpenAI model override
AZURE_OPENAI_DEPLOYMENT Azure default deployment name
AZURE_OPENAI_IMAGE_MODEL Backward-compatible alias for Azure default deployment/model name
OPENROUTER_IMAGE_MODEL OpenRouter model override (default: google/gemini-3.1-flash-image-preview)
GOOGLE_IMAGE_MODEL Google model override
DASHSCOPE_IMAGE_MODEL DashScope model override (default: qwen-image-2.0-pro)
MINIMAX_IMAGE_MODEL MiniMax model override (default: image-01)
REPLICATE_IMAGE_MODEL Replicate model override (default: google/nano-banana-pro)
JIMENG_IMAGE_MODEL Jimeng model override (default: jimeng_t2i_v40)
SEEDREAM_IMAGE_MODEL Seedream model override (default: doubao-seedream-5-0-260128)
OPENAI_BASE_URL Custom OpenAI endpoint
AZURE_OPENAI_BASE_URL Azure resource endpoint or deployment endpoint
AZURE_API_VERSION Azure image API version (default: 2025-04-01-preview)
OPENROUTER_BASE_URL Custom OpenRouter endpoint (default: https://openrouter.ai/api/v1)
OPENROUTER_HTTP_REFERER Optional app/site URL for OpenRouter attribution
OPENROUTER_TITLE Optional app name for OpenRouter attribution
GOOGLE_BASE_URL Custom Google endpoint
DASHSCOPE_BASE_URL Custom DashScope endpoint
MINIMAX_BASE_URL Custom MiniMax endpoint (default: https://api.minimax.io)
REPLICATE_BASE_URL Custom Replicate endpoint
JIMENG_BASE_URL Custom Jimeng endpoint (default: https://visual.volcengineapi.com)
JIMENG_REGION Jimeng region (default: cn-north-1)
SEEDREAM_BASE_URL Custom Seedream endpoint (default: https://ark.cn-beijing.volces.com/api/v3)
BAOYU_IMAGE_GEN_MAX_WORKERS Override batch worker cap
BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY Override provider concurrency, e.g. BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY
BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS Override provider start gap, e.g. BAOYU_IMAGE_GEN_REPLICATE_START_INTERVAL_MS

Load Priority: CLI args > EXTEND.md > env vars > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env

Model Resolution

Model priority (highest → lowest), applies to all providers:

  1. CLI flag: --model <id>
  2. EXTEND.md: default_model.[provider]
  3. Env var: <PROVIDER>_IMAGE_MODEL (e.g., GOOGLE_IMAGE_MODEL)
  4. Built-in default

For Azure, --model / default_model.azure should be the Azure deployment name. AZURE_OPENAI_DEPLOYMENT is the preferred env var, and AZURE_OPENAI_IMAGE_MODEL remains as a backward-compatible alias.

EXTEND.md overrides env vars. If both EXTEND.md default_model.google: "gemini-3-pro-image-preview" and env var GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image-preview exist, EXTEND.md wins.

Agent MUST display model info before each generation:

  • Show: Using [provider] / [model]
  • Show switch hint: Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODEL

DashScope Models

Use --model qwen-image-2.0-pro or set default_model.dashscope / DASHSCOPE_IMAGE_MODEL when the user wants official Qwen-Image behavior.

Official DashScope model families:

  • qwen-image-2.0-pro, qwen-image-2.0-pro-2026-03-03, qwen-image-2.0, qwen-image-2.0-2026-03-03
    • Free-form size in 宽*高 format
    • Total pixels must stay between 512*512 and 2048*2048
    • Default size is approximately 1024*1024
    • Best choice for custom ratios such as 21:9 and text-heavy Chinese/English layouts
  • qwen-image-max, qwen-image-max-2025-12-30, qwen-image-plus, qwen-image-plus-2026-01-09, qwen-image
    • Fixed sizes only: 1664*928, 1472*1104, 1328*1328, 1104*1472, 928*1664
    • Default size is 1664*928
    • qwen-image currently has the same capability as qwen-image-plus
  • Legacy DashScope models such as z-image-turbo, z-image-ultra, wanx-v1
    • Keep using them only when the user explicitly asks for legacy behavior or compatibility

When translating CLI args into DashScope behavior:

  • --size wins over --ar
  • For qwen-image-2.0*, prefer explicit --size; otherwise infer from --ar and use the official recommended resolutions below
  • For qwen-image-max/plus/image, only use the five official fixed sizes; if the requested ratio is not covered, switch to qwen-image-2.0-pro
  • --quality is a baoyu-imagine compatibility preset, not a native DashScope API field. Mapping normal / 2k onto the qwen-image-2.0* table below is an implementation inference, not an official API guarantee

Recommended qwen-image-2.0* sizes for common aspect ratios:

Ratio normal 2k
1:1 1024*1024 1536*1536
2:3 768*1152 1024*1536
3:2 1152*768 1536*1024
3:4 960*1280 1080*1440
4:3 1280*960 1440*1080
9:16 720*1280 1080*1920
16:9 1280*720 1920*1080
21:9 1344*576 2048*872

DashScope official APIs also expose negative_prompt, prompt_extend, and watermark, but baoyu-imagine does not expose them as dedicated CLI flags today.

Official references:

MiniMax Models

Use --model image-01 or set default_model.minimax / MINIMAX_IMAGE_MODEL when the user wants MiniMax image generation.

Official MiniMax image model options currently documented in the API reference:

  • image-01 (recommended default)
    • Supports text-to-image and subject-reference image generation
    • Supports official aspect_ratio values: 1:1, 16:9, 4:3, 3:2, 2:3, 3:4, 9:16, 21:9
    • Supports documented custom width / height output sizes when using --size <WxH>
    • width and height must both be between 512 and 2048, and both must be divisible by 8
  • image-01-live
    • Lower-latency variant
    • Use --ar for sizing; MiniMax documents custom width / height as only effective for image-01

MiniMax subject reference notes:

  • --ref files are sent as MiniMax subject_reference
  • MiniMax docs currently describe subject_reference[].type as character
  • Official docs say image_file supports public URLs or Base64 Data URLs; baoyu-imagine sends local refs as Data URLs
  • Official docs recommend front-facing portrait references in JPG/JPEG/PNG under 10MB

Official references:

OpenRouter Models

Use full OpenRouter model IDs, e.g.:

  • google/gemini-3.1-flash-image-preview (recommended, supports image output and reference-image workflows)
  • google/gemini-2.5-flash-image-preview
  • black-forest-labs/flux.2-pro
  • Other OpenRouter image-capable model IDs

Notes:

  • OpenRouter image generation uses /chat/completions, not the OpenAI /images endpoints
  • If --ref is used, choose a multimodal model that supports image input and image output
  • --imageSize maps to OpenRouter imageGenerationOptions.size; --size <WxH> is converted to the nearest OpenRouter size and inferred aspect ratio when possible

Replicate Models

Supported model formats:

  • owner/name (recommended for official models), e.g. google/nano-banana-pro
  • owner/name:version (community models by version), e.g. stability-ai/sdxl:<version>

Examples:

# Use Replicate default model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate

# Override model explicitly
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider replicate --model google/nano-banana

Provider Selection

  1. --ref provided + no --provider → auto-select Google first, then OpenAI, then Azure, then OpenRouter, then Replicate, then Seedream, then MiniMax (MiniMax subject reference is more specialized toward character/portrait consistency)
  2. --provider specified → use it (if --ref, must be google, openai, azure, openrouter, replicate, seedream, or minimax)
  3. Only one API key available → use that provider
  4. Multiple available → default to Google

Quality Presets

Preset Google imageSize OpenAI Size OpenRouter size Replicate resolution Use Case
normal 1K 1024px 1K 1K Quick previews
2k (default) 2K 2048px 2K 2K Covers, illustrations, infographics

Google/OpenRouter imageSize: Can be overridden with --imageSize 1K|2K|4K

Aspect Ratios

Supported: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1

  • Google multimodal: uses imageConfig.aspectRatio
  • OpenAI: maps to closest supported size
  • OpenRouter: sends imageGenerationOptions.aspect_ratio; if only --size <WxH> is given, aspect ratio is inferred automatically
  • Replicate: passes aspect_ratio to model; when --ref is provided without --ar, defaults to match_input_image
  • MiniMax: sends official aspect_ratio values directly; if --size <WxH> is given without --ar, width / height are sent for image-01

Generation Mode

Default: Sequential generation.

Batch Parallel Generation: When --batchfile contains 2 or more pending tasks, the script automatically enables parallel generation.

Mode When to Use
Sequential (default) Normal usage, single images, small batches
Parallel batch Batch mode with 2+ tasks

Execution choice:

Situation Preferred approach Why
One image, or 1-2 simple images Sequential Lower coordination overhead and easier debugging
Multiple images already have saved prompt files Batch (--batchfile) Reuses finalized prompts, applies shared throttling/retries, and gives predictable throughput
Each image still needs separate reasoning, prompt writing, or style exploration Subagents The work is still exploratory, so each image may need independent analysis before generation
Output comes from baoyu-article-illustrator with outline.md + prompts/ Batch (build-batch.ts -> --batchfile) That workflow already produces prompt files, so direct batch execution is the intended path

Rule of thumb:

  • Prefer batch over subagents once prompt files are already saved and the task is "generate all of these"
  • Use subagents only when generation is coupled with per-image thinking, rewriting, or divergent creative exploration

Parallel behavior:

  • Default worker count is automatic, capped by config, built-in default 10
  • Provider-specific throttling is applied only in batch mode, and the built-in defaults are tuned for faster throughput while still avoiding obvious RPM bursts
  • You can override worker count with --jobs <count>
  • Each image retries automatically up to 3 attempts
  • Final output includes success count, failure count, and per-image failure reasons

Error Handling

  • Missing API key → error with setup instructions
  • Generation failure → auto-retry up to 3 attempts per image
  • Invalid aspect ratio → warning, proceed with default
  • Reference images with unsupported provider/model → error with fix hint

Extension Support

Custom configurations via EXTEND.md. See Preferences section for paths and supported options.

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