Baoyu Image Gen

AI image generation with OpenAI, Google, OpenRouter, DashScope, Jimeng, Seedream and Replicate APIs. Supports text-to-image, reference images, aspect ratios,...

Security Scan

The skill's instructions reference running a local script and multiple cloud providers but the package contains no executable code and declares no API credentials—these mismatches are inconsistent and warrant caution.

Purpose & Capability

The SKILL.md claims multi-provider image generation (OpenAI, Google, OpenRouter, DashScope, Jimeng, Seedream, Replicate) but the registry metadata declares no required environment variables or primary credential. A networked multi-provider image tool would normally require provider API keys/tokens; those are not declared. Also the SKILL.md references scripts/main.ts (the actual runtime) but the skill bundle contains no code files — only the SKILL.md and reference docs. This mismatch between claimed capabilities and what is present is concerning.

Instruction Scope

Runtime instructions tell the agent to: detect bun/npx, compute baseDir, and run {baseDir}/scripts/main.ts; require a blocking first-time setup that reads/writes EXTEND.md under project or $HOME; and use AskUserQuestion flows. Those file reads/writes (project and home) are consistent with saving preferences, but the instructions do not mention obtaining or using provider API credentials even though networked provider calls are implied. Crucially, the instructions call a local script that is not included in the bundle — the agent would attempt to run a non-existent program unless code is provided elsewhere.

Install Mechanism

There is no install spec (instruction-only), which reduces immediate disk-write/install risk. The skill requires bun or npx to run a TypeScript runtime; requiring those binaries is reasonable for a TypeScript script. However, because the script referred to in SKILL.md is absent from the provided files, there is uncertainty about what would be installed or executed in a real installation from the referenced homepage/repo.

Credentials

The skill integrates many external providers but declares no required env vars or credentials. Calling these APIs normally requires tokens (e.g., OPENAI_API_KEY, GOOGLE_API_KEY/OAuth, REPLICATE_API_TOKEN, DashScope credentials). The absence of declared credentials is disproportionate to the stated networked functionality and hides what secrets the runtime will actually use or request.

Persistence & Privilege

The skill does not request always:true and does not claim to modify other skills or system-wide settings. It does instruct writing EXTEND.md into project or user home directories (preference storage), which is a reasonable local persistence for a preferences file.

What to consider before installing

Do not install blindly. The SKILL.md expects to run {baseDir}/scripts/main.ts but the skill bundle contains no runtime code — ask for the script or an install spec before trusting this skill. Verify where the code will come from (the GitHub homepage) and inspect it for network endpoints and credential handling. Expect that using this skill will require API keys for providers (OpenAI, Google, Replicate, DashScope, etc.); confirm which environment variables or auth flows are required and that keys are stored securely. Be aware the skill will create/modify EXTEND.md in your project or $HOME; review its content. If you cannot review the runtime code or prefer isolation, run this in a sandboxed environment or decline until the author supplies the missing scripts and a clear list of required credentials.

Image Generation (AI SDK)

Official API-based image generation. Supports OpenAI, Google, OpenRouter, DashScope (阿里通义万象), 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-image-gen/EXTEND.md && echo "project"
test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "xdg"
test -f "$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "user"

# PowerShell (Windows)
if (Test-Path .baoyu-skills/baoyu-image-gen/EXTEND.md) { "project" }
$xdg = if ($env:XDG_CONFIG_HOME) { $env:XDG_CONFIG_HOME } else { "$HOME/.config" }
if (Test-Path "$xdg/baoyu-skills/baoyu-image-gen/EXTEND.md") { "xdg" }
if (Test-Path "$HOME/.baoyu-skills/baoyu-image-gen/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-image-gen/EXTEND.md	Project directory
$HOME/.baoyu-skills/baoyu-image-gen/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, OpenRouter, Replicate, 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

# 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

# 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|openrouter|dashscope|jimeng|seedream|replicate	Force provider (default: auto-detect)
--model <id>, -m	Model ID (Google: gemini-3-pro-image-preview; OpenAI: gpt-image-1.5; OpenRouter: google/gemini-3.1-flash-image-preview; DashScope: qwen-image-2.0-pro)
--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, OpenRouter multimodal models, Replicate, 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
OPENROUTER_API_KEY	OpenRouter API key
GOOGLE_API_KEY	Google API key
DASHSCOPE_API_KEY	DashScope API key (阿里云)
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
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)
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
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
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

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-image-gen 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-image-gen does not expose them as dedicated CLI flags today.

Official references:

• Qwen-Image API
• Text-to-image guide
• Qwen-Image Edit API

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 OpenRouter, then Replicate (Jimeng and Seedream do not support reference images)
2. --provider specified → use it (if --ref, must be google, openai, openrouter, or replicate)
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

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.