baoyu-image-gen
AI image generation with OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs.
Skill by JimLiu
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/jimliu-baoyu-image-gen
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: cloud, agent-building, image-generation
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Node.js package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/baoyu-image-gen
What's inside
- Skill name
baoyu-image-gen- Description
- AI image generation with OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs. Supports text-to-image, reference images, aspect ratios, and batch generation from saved prompt files. Sequential by default; use batch parallel generation when the user already has multiple prompts or wants stable multi-image throughput. Use when user asks to generate, create, or draw images.
- License
- MIT
- Instructions
- 284 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
- Instructions read files in your home folder (~/.ssh, ~/.aws…)
Files (49)
- SKILL.md
- codex-image2-fallback.md · references/
- codex-oauth-vs-openai-api-key.md · references/
- first-time-setup.md · references/config/
- preferences-schema.md · references/config/
- agnes.md · references/providers/
- codex-cli.md · references/providers/
- dashscope.md · references/providers/
- minimax.md · references/providers/
- openrouter.md · references/providers/
- replicate.md · references/providers/
- zai.md · references/providers/
- usage-examples.md · references/
- build-batch.test.ts · scripts/
- build-batch.ts · scripts/
- cache.ts · scripts/codex-imagegen/
- logger.ts · scripts/codex-imagegen/
- main.ts · scripts/codex-imagegen/
- parser.ts · scripts/codex-imagegen/
- spawn.ts · scripts/codex-imagegen/
- types.ts · scripts/codex-imagegen/
- validator.ts · scripts/codex-imagegen/
- main.test.ts · scripts/
- main.ts · scripts/
- agnes.test.ts · scripts/providers/
- agnes.ts · scripts/providers/
- azure.test.ts · scripts/providers/
- azure.ts · scripts/providers/
- codex-cli.test.ts · scripts/providers/
- codex-cli.ts · scripts/providers/
- dashscope.test.ts · scripts/providers/
- dashscope.ts · scripts/providers/
- google.test.ts · scripts/providers/
- google.ts · scripts/providers/
- jimeng.test.ts · scripts/providers/
- jimeng.ts · scripts/providers/
- minimax.test.ts · scripts/providers/
- minimax.ts · scripts/providers/
- openai.test.ts · scripts/providers/
- openai.ts · scripts/providers/
- openrouter.test.ts · scripts/providers/
- openrouter.ts · scripts/providers/
- replicate.test.ts · scripts/providers/
- replicate.ts · scripts/providers/
- seedream.test.ts · scripts/providers/
- seedream.ts · scripts/providers/
- zai.test.ts · scripts/providers/
- zai.ts · scripts/providers/
- types.ts · scripts/
SKILL.md (first lines)
# Image Generation (AI SDK)
Official API-based image generation. Supports OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope (阿里通义万象), Z.AI GLM-Image, MiniMax, Jimeng (即梦), Seedream (豆包), Replicate and Agnes.
## User Input Tools
When this skill prompts the user, follow this tool-selection rule (priority order):
1. **Prefer built-in user-input tools** exposed by the current agent runtime — e.g., `AskUserQuestion`, `request_user_input`, `clarify`, `ask_user`, or any equivalent.
2. **Fallback**: if no such tool exists, emit a numbered plain-text message and ask the user to reply with the chosen number/answer for each question.
3. **Batching**: if the tool supports multiple questions per call, combine all applicable questions into a single call; if only single-question, ask them one at a time in priority order.
Concrete `AskUserQuestion` references below are examples — substitute the local equivalent in other runtimes.
## Script Directory
`{baseDir}` = this SKILL.md's directory. All `scripts/...` paths below are relative to `{baseDir}`. Main script: `{baseDir}/scripts/main.ts`. Batch payload helper: `{baseDir}/scripts/build-batch.ts`. Resolve `${BUN_X}`: prefer `bun`; else `npx -y bun`; else suggest `brew install oven-sh/bun/bun`.
## Step 0: Load Preferences ⛔ BLOCKING
This step MUST complete before any image generation — generation is blocked until EXTEND.md exists.
Check these paths in order; first hit wins:
| Path | Scope |
|------|-------|
| `.baoyu-skills/baoyu-image-gen/EXTEND.md` | Project |
| `${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-gen/EXTEND.md` | XDG |
| `$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md` | User home |
- **Found** → load, parse, apply. If `default_model.[provider]` is null → ask model only.
- **Not found** → run first-time setup (`references/config/first-time-setup.md`) using AskUserQuestion to collect provider + model + quality + save location. Save EXTEND.md, then continue. Do not generate images before this completes.
Legacy compatibility: if `.baoyu-skills/baoyu-imagine/EXTEND.md` exists and the new path doesn't, the runtime renames it to `baoyu-image-gen`. If both exist, the runtime leaves them alone and uses the new path.
**EXTEND.md keys**: default provider, default quality, default aspect ratio, default image size, OpenAI image API dialect, default models, batch worker cap, provider-specific batch limits. Schema: `references/config/preferences-schema.md`.
## Usage
Minimum working examples — see `references/usage-examples.md` for the full set including per-provider invocations and batch mode.
### Identity-preserving reference prompts
When the user wants a real person/character/object preserved from reference images, do **not** replace the reference with a long generic description. Prefer short, hard identity-preservation language:
- "Use the person/object in the reference image(s) as the same identity. Do not redesign it or create a similar-looking new subject."
- "Only change scene, clothing, pose, lighting, rendering style, and composition. Keep the face/proportions/hair/key accessories/overall identity from the references."
- If using multiple references, state that they are the same subject and should jointly define identity.
Pitfall: long descriptions like "young East Asian woman, oval face, clear eyes..." can cause the model to synthesize a new person matching the description instead of preserving the referenced person.
```bash
# Basic
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image cat.png
# With aspect ratio and high quality
${BUN_X} {baseDir}/scripts/main.ts --prompt "A landscape" --image out.png --ar 16:9 --quality 2k
# Prompt from files
${BUN_X} {baseDir}/scripts/main.ts --promptfiles system.md content.md --image out.png
# With reference image
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make blue" --image out.png --ref source.png
# Specific provider
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider dashscope --model qwen-image-2.0-pro
# OpenAI GPT Image 2
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider openai --model gpt-image-2.5-flare
# Codex CLI (uses logged-in Codex subscription — no OPENAI_API_KEY required; requires `codex` on PATH)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat" --image out.png --provider codex-cli --ar 16:9
# Batch mode
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4
# Build a batch file from outline.md + prompts/ (e.g. baoyu-article-illustrator output)
${BUN_X} {baseDir}/scripts/build-batch.ts --outline outline.md --prompts prompts --output batch.json --images-dir attachments
${BUN_X} {baseDir}/scripts/main.ts --batchfile batch.json --jobs 4
```
## Reference-Image Identity Preservation
When the user wants a person/object preserved from reference images:
- Prefer a small curated set of existing source references (usually 2–4) over many images; large multi-megabyte refs can destabilize streaming providers.
- Make the prompt say the references are the same subject and the output must use that identity. Avoid long generic facial-feature descriptions that can cause the model to synthesize a new similar-looking person.
- Do not use newly generated outputs as references unless the user explicitly asks; generated refs compound drift.
- If results become too polished or influencer-like, reduce stylized refs and add explicit anti-beautification constraints (no face slimming, eye enlargement, heavy makeup, commercial travel shoot, over-smoothing).
- If the subject should look younger/older, preserve the face and express age through clothing, posture, scene, and styling; do not ask the model to change facial identity.
## 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\|zai\|minimax\|jimeng\|seedream\|replicate\|codex-cli\|agnes` | Force provider (default: auto-detect; `codex-cli` is never auto-selected — must be pinned via CLI or EXTEND.md) |
| `--model <id>`, `-m` | Model ID — see provider references for defaults and allowed values |
| `--ar <ratio>` | Aspect ratio (`16:9`, `1:1`, `4:3`, …) |
| `--size <WxH>` | Explicit size (e.g., `1024x1024`; for `gpt-image-2.5-*` and `gpt-image-2`, width/height must be multiples of 16, max edge 3840px, ratio no wider than 3:1) |
| `--quality normal\|2k` | Quality preset (default: `2k`) |
| `--imageSize 1K\|2K\|4K` | Image size for Google/OpenRouter (default: from quality) |
| `--imageApiDialect openai-native\|ratio-metadata` | OpenAI-compatible endpoint dialect — use `ratio-metadata` for gateways that expect aspect-ratio `size` plus `metadata.resolution` |
| `--ref <files...>` | Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Azure OpenAI edits (PNG/JPG only), OpenRouter multimodal models, Replicate supported families, MiniMax subject-reference, Seedream 5.0/4.5/4.0, DashScope `wan2.7-image-pro`/`wan2.7-image`. Not supported by Jimeng, Seedream 3.0, SeedEdit 3.0, or any DashScope model outside the `wan2.7-image*` family |
| `--n <count>` | Number of images. Replicate requires `--n 1` (single-output save semantics) |
| `--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 |From JimLiu/baoyu-skills, MIT.
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- Stars
- 26,925
- Forks
- 2,950
- Open issues
- 13
- Last commit (this folder)
- Sep 10, 2026 (1 month ago)
- Last release
- Jun 18, 2026 (4 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/JimLiu/baoyu-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
baoyu-image-gen skill. Agent Mart. https://agentmart.dev/skills/jimliu-baoyu-image-gen (last updated 2026-10-24)