| name | baoyu-image-gen |
| description | AI image generation with OpenAI, Google and DashScope APIs. Supports text-to-image, reference images, aspect ratios. Sequential by default; parallel generation available on request. Use when user asks to generate, create, or draw images. |
Image Generation (AI SDK)
Official API-based image generation. Supports OpenAI, Google and DashScope (阿里通义万象) providers.
Script Directory
Agent Execution:
SKILL_DIR = this SKILL.md file's directory
- Script path =
${SKILL_DIR}/scripts/main.ts
Preferences (EXTEND.md)
Use Bash to check EXTEND.md existence (priority order):
test -f .baoyu-skills/baoyu-image-gen/EXTEND.md && echo "project"
test -f "$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "user"
┌──────────────────────────────────────────────────┬───────────────────┐
│ Path │ Location │
├──────────────────────────────────────────────────┼───────────────────┤
│ .baoyu-skills/baoyu-image-gen/EXTEND.md │ Project directory │
├──────────────────────────────────────────────────┼───────────────────┤
│ $HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md │ User home │
└──────────────────────────────────────────────────┴───────────────────┘
┌───────────┬───────────────────────────────────────────────────────────────────────────┐
│ Result │ Action │
├───────────┼───────────────────────────────────────────────────────────────────────────┤
│ Found │ Read, parse, apply settings │
├───────────┼───────────────────────────────────────────────────────────────────────────┤
│ Not found │ Use defaults │
└───────────┴───────────────────────────────────────────────────────────────────────────┘
EXTEND.md Supports: Default provider | Default quality | Default aspect ratio | Default image size | Default models
Schema: references/config/preferences-schema.md
Usage
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image cat.png
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image out.png --quality 2k
npx -y bun ${SKILL_DIR}/scripts/main.ts --promptfiles system.md content.md --image out.png
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "Make blue" --image out.png --provider google --model gemini-3-pro-image-preview --ref source.png
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "A cat" --image out.png --provider openai
npx -y bun ${SKILL_DIR}/scripts/main.ts --prompt "一只可爱的猫" --image out.png --provider dashscope
Options
| Option | Description |
|---|
--prompt <text>, -p | Prompt text |
--promptfiles <files...> | Read prompt from files (concatenated) |
--image <path> | Output image path (required) |
--provider google|openai|dashscope | Force provider (default: google) |
--model <id>, -m | Model ID (--ref with OpenAI requires GPT Image model, e.g. gpt-image-1.5) |
--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 (default: from quality) |
--ref <files...> | Reference images. Supported by Google multimodal and OpenAI edits (GPT Image models). If provider omitted: Google first, then OpenAI |
--n <count> | Number of images |
--json | JSON output |
Environment Variables
| Variable | Description |
|---|
OPENAI_API_KEY | OpenAI API key |
GOOGLE_API_KEY | Google API key |
DASHSCOPE_API_KEY | DashScope API key (阿里云) |
OPENAI_IMAGE_MODEL | OpenAI model override |
GOOGLE_IMAGE_MODEL | Google model override |
DASHSCOPE_IMAGE_MODEL | DashScope model override (default: z-image-turbo) |
OPENAI_BASE_URL | Custom OpenAI endpoint |
GOOGLE_BASE_URL | Custom Google endpoint |
DASHSCOPE_BASE_URL | Custom DashScope endpoint |
Load Priority: CLI args > EXTEND.md > env vars > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env
Provider Selection
--ref provided + no --provider → auto-select Google first, then OpenAI
--provider specified → use it (if --ref, must be google or openai)
- Only one API key available → use that provider
- Multiple available → default to Google
Quality Presets
| Preset | Google imageSize | OpenAI Size | Use Case |
|---|
normal | 1K | 1024px | Quick previews |
2k (default) | 2K | 2048px | Covers, illustrations, infographics |
Google 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
- Google Imagen: uses
aspectRatio parameter
- OpenAI: maps to closest supported size
Generation Mode
Default: Sequential generation (one image at a time). This ensures stable output and easier debugging.
Parallel Generation: Only use when user explicitly requests parallel/concurrent generation.
| Mode | When to Use |
|---|
| Sequential (default) | Normal usage, single images, small batches |
| Parallel | User explicitly requests, large batches (10+) |
Parallel Settings (when requested):
| Setting | Value |
|---|
| Recommended concurrency | 4 subagents |
| Max concurrency | 8 subagents |
| Use case | Large batch generation when user requests parallel |
Agent Implementation (parallel mode only):
# Launch multiple generations in parallel using Task tool
# Each Task runs as background subagent with run_in_background=true
# Collect results via TaskOutput when all complete
Error Handling
- Missing API key → error with setup instructions
- Generation failure → auto-retry once
- Invalid aspect ratio → warning, proceed with default
- Reference images with unsupported provider/model → error with fix hint (switch to Google multimodal or OpenAI GPT Image edits)
Extension Support
Custom configurations via EXTEND.md. See Preferences section for paths and supported options.
🔒 Mandatory Post-Processing (EXIF strip)
After every image generated by this skill — regardless of file extension claimed (.png/.jpg/.webp), regardless of provider (Gemini/OpenAI/DashScope), regardless of whether the user is going to share it — Claude MUST run the post-processing pipeline defined in:
~/.baoyu-skills/image-post-processing.md
Why this is mandatory and unconditional:
- AI providers routinely embed metadata: provider tags, timestamps, color profiles, copyright fingerprints, watermark indicators, C2PA chunks
- Provider-claimed file format (e.g.
.png) often disagrees with actual format (e.g. JPEG with PNG extension) — verify and rename
- Local-only files frequently get uploaded later (CDN, R2, screenshots into shared docs, git history) — strip on creation, not before sharing
Required steps for each generated image (in order):
- Detect actual format with
PIL.Image.open(f).format (not the extension)
- Re-save via PIL with no metadata (this is the EXIF-strip step):
from PIL import Image
img = Image.open(path)
data = list(img.getdata())
clean = Image.new(img.mode, img.size)
clean.putdata(data)
clean.save(target_path, img.format, quality=95, optimize=True)
- If actual format ≠ claimed extension, rename to the correct one and remove the original
- Verify: re-open the saved file and assert
img.getexif() is empty AND img.info has no metadata keys (other than benign jfif/dpi)
- Only after verification passes may you report the image as done
⚠️ Skipping this step or trusting "the provider doesn't add metadata" is a contract violation. Verify, do not assume.