Baoyu Imagine
guanyang/open-agent-hub
AI image generation with OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream and Replicate APIs.
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.
$ npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install JimLiu/baoyu-skills baoyu-image-gen --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/JimLiu/baoyu-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/baoyu-image-gen .claude/skills/baoyu-image-gen && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "baoyu-image-gen" agent skill from https://github.com/JimLiu/baoyu-skills/tree/main/skills/baoyu-image-gen into .claude/skills/baoyu-image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-gen", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/JimLiu/baoyu-skills/tree/main/skills/baoyu-image-genType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install JimLiu/baoyu-skills baoyu-image-gen --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JimLiu/baoyu-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/baoyu-image-gen .agents/skills/baoyu-image-gen && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "baoyu-image-gen" agent skill from https://github.com/JimLiu/baoyu-skills/tree/main/skills/baoyu-image-gen into .agents/skills/baoyu-image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-gen", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install JimLiu/baoyu-skills baoyu-image-gen --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JimLiu/baoyu-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/baoyu-image-gen .cursor/skills/baoyu-image-gen && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "baoyu-image-gen" agent skill from https://github.com/JimLiu/baoyu-skills/tree/main/skills/baoyu-image-gen into .cursor/skills/baoyu-image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-gen", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/JimLiu/baoyu-skills.git --path skills/baoyu-image-gen--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install JimLiu/baoyu-skills baoyu-image-gen --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JimLiu/baoyu-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/baoyu-image-gen .gemini/skills/baoyu-image-gen && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "baoyu-image-gen" agent skill from https://github.com/JimLiu/baoyu-skills/tree/main/skills/baoyu-image-gen into .gemini/skills/baoyu-image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-gen", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install JimLiu/baoyu-skills baoyu-image-genInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/JimLiu/baoyu-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/baoyu-image-gen .github/skills/baoyu-image-gen && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "baoyu-image-gen" agent skill from https://github.com/JimLiu/baoyu-skills/tree/main/skills/baoyu-image-gen into .github/skills/baoyu-image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-gen", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install JimLiu/baoyu-skills baoyu-image-gen --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/JimLiu/baoyu-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/baoyu-image-gen .opencode/skills/baoyu-image-gen && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "baoyu-image-gen" agent skill from https://github.com/JimLiu/baoyu-skills/tree/main/skills/baoyu-image-gen into .opencode/skills/baoyu-image-gen/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "baoyu-image-gen", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
baoyu-image-genAI image generation with OpenAI GPT Image 2.5, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs.
Baoyu Image Gen is an agent skill from JimLiu/baoyu-skills. 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.
Its SKILL.md is about 5.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 54 other files, including scripts and reference files (for example `references/codex-image2-fallback.md`, `references/codex-oauth-vs-openai-api-key.md` and `references/config/first-time-setup.md`).
It sits in Media & Creative, covering Image generation. It works with Azure OpenAI, MiniMax, OpenAI and OpenRouter. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 1567581. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 3 files in scripts/ (TypeScript, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
codexnpxbrewFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
OPENAI_API_KEYAZURE_OPENAI_API_KEYOPENROUTER_API_KEYGOOGLE_API_KEYDASHSCOPE_API_KEYZAI_API_KEYBIGMODEL_API_KEYMINIMAX_API_KEYREPLICATE_API_TOKENJIMENG_ACCESS_KEY_IDJIMENG_SECRET_ACCESS_KEYARK_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Baoyu Image Gen loads about 5.3k tokens when it runs, and up to ~17k if it reads all its reference files. Until then it costs about 118 tokens; SKILL.md has 2,136 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
END.md > env vars > `<cwd>/.baoyu-skills/.env` > `~/.baoyu-skills/.env`Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from JimLiu/baoyu-skills at commit 1567581, republished under its MIT licence (© JimLiu). 2,136 words, ~5,317 tokens.
.claude/skills/baoyu-image-gen/SKILL.md (or your agent's skills folder). This skill also uses 49 other files; get the full folder from GitHub.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.
When this skill prompts the user, follow this tool-selection rule (priority order):
AskUserQuestion, request_user_input, clarify, ask_user, or any equivalent.Concrete AskUserQuestion references below are examples — substitute the local equivalent in other runtimes.
{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.
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 |
default_model.[provider] is null → ask model only.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.
Minimum working examples — see references/usage-examples.md for the full set including per-provider invocations and batch mode.
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:
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.
# 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 4When the user wants a person/object preserved from reference images:
| 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 |
| 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 |
ZAI_API_KEY (alias BIGMODEL_API_KEY) | Z.AI API key |
MINIMAX_API_KEY | MiniMax API key |
REPLICATE_API_TOKEN | Replicate API token |
JIMENG_ACCESS_KEY_ID, JIMENG_SECRET_ACCESS_KEY | Jimeng (即梦) Volcengine credentials |
ARK_API_KEY | Seedream (豆包) Volcengine ARK API key |
<PROVIDER>_IMAGE_MODEL | Per-provider model override (OPENAI_IMAGE_MODEL, GOOGLE_IMAGE_MODEL, DASHSCOPE_IMAGE_MODEL, ZAI_IMAGE_MODEL/BIGMODEL_IMAGE_MODEL, MINIMAX_IMAGE_MODEL, OPENROUTER_IMAGE_MODEL, REPLICATE_IMAGE_MODEL, JIMENG_IMAGE_MODEL, SEEDREAM_IMAGE_MODEL, AGNES_IMAGE_MODEL) |
AZURE_OPENAI_DEPLOYMENT (alias AZURE_OPENAI_IMAGE_MODEL) | Azure default deployment |
<PROVIDER>_BASE_URL | Per-provider endpoint override |
AZURE_API_VERSION | Azure image API version (default 2025-04-01-preview) |
JIMENG_REGION | Jimeng region (default cn-north-1) |
OPENAI_IMAGE_API_DIALECT | openai-native | ratio-metadata |
OPENROUTER_HTTP_REFERER, OPENROUTER_TITLE | Optional OpenRouter attribution |
BAOYU_IMAGE_GEN_MAX_WORKERS | Override batch worker cap |
BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCY | Per-provider concurrency (e.g., BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY; for codex-cli use BAOYU_IMAGE_GEN_CODEX_CLI_CONCURRENCY) |
BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MS | Per-provider start-gap |
BAOYU_CODEX_IMAGEGEN_BIN | Override the codex-imagegen wrapper path for the codex-cli provider (default: bundled scripts/codex-imagegen/main.ts; accepts .ts or legacy .sh/binary) |
BAOYU_CODEX_IMAGEGEN_CACHE_DIR | Enable idempotency cache for the codex-cli provider (off by default) |
BAOYU_CODEX_IMAGEGEN_TIMEOUT_MS | Per-attempt codex exec timeout for the codex-cli provider (default: 300000 ms) |
BAOYU_CODEX_IMAGEGEN_RETRIES | Wrapper-side retry attempts on retryable errors for the codex-cli provider (default: 2) |
BAOYU_CODEX_IMAGEGEN_LOG_FILE | Append JSONL diagnostic log for the codex-cli provider |
Load priority: CLI args > EXTEND.md > env vars > <cwd>/.baoyu-skills/.env > ~/.baoyu-skills/.env
--provider openai --model gpt-image-2.5-flare uses the standard OpenAI Images API (/v1/images/generations or /v1/images/edits) and requires OPENAI_API_KEY. A Codex or ChatGPT desktop login is a different entitlement and is not a drop-in replacement for OPENAI_API_KEY; do not paste a Codex OAuth token into OPENAI_API_KEY or only set OPENAI_BASE_URL to a Codex backend.
If the user wants to use their Codex subscription / GPT Image 2 entitlement without an OpenAI API key, route through a Codex-native backend instead of this skill's openai provider:
imagegen skill/tool.codex CLI installed and logged in: use baoyu-image-gen --provider codex-cli (preferred — it gives you the same retry / cache / batch flow as every other provider). The provider spawns the bundled scripts/codex-imagegen/main.ts; the same code lives upstream at packages/baoyu-codex-imagegen/src/main.ts for standalone callers.image_generate tool: use that tool as a fallback, and state whether reference images were passed directly or reconstructed from extracted traits.Do not modify the existing openai provider to silently consume Codex OAuth. The first-class Codex-CLI path is the dedicated codex-cli provider, which has its own auth (Codex login), route (codex exec), request shape, and tests. See references/codex-oauth-vs-openai-api-key.md.
Priority (highest → lowest) applies to every provider:
--model <id>default_model.[provider]<PROVIDER>_IMAGE_MODELFor OpenAI, the built-in default is gpt-image-2.5-flare (fast, lowest latency). gpt-image-2.5-sunburst is the most capable variant for complex scenes and precise edits; gpt-image-2, gpt-image-1.5, gpt-image-1, and dated GPT Image snapshots (e.g. gpt-image-2.5-flare-2026-09-08, gpt-image-2-2026-04-21) remain selectable with --model or OPENAI_IMAGE_MODEL.
For Google, the built-in default is gemini-3-pro-image. gemini-3.1-flash-image is the faster low-cost option, and gemini-3.1-flash-lite-image is the cheapest — it only produces 1K output, so --quality 2k / --imageSize 2K|4K is clamped to 1K with a warning.
For DashScope, the built-in default is qwen-image-2.0-pro; qwen-image-3.0-pro is the newest flagship and uses the same sizing rules.
For Azure, --model / default_model.azure is the Azure deployment name. AZURE_OPENAI_DEPLOYMENT is the preferred env var; AZURE_OPENAI_IMAGE_MODEL is kept as a backward-compatible alias. If your Azure deployment is named after the underlying model, use gpt-image-2.5-flare; otherwise use the exact custom deployment name.
EXTEND.md overrides env vars: if EXTEND.md sets default_model.google: "gemini-3-pro-image" and the env var sets GOOGLE_IMAGE_MODEL=gemini-3.1-flash-image, EXTEND.md wins.
Display model info before each generation:
Using [provider] / [model]Switch model: --model <id> | EXTEND.md default_model.[provider] | env <PROVIDER>_IMAGE_MODELprovider=openai means the auth and routing entrypoint is OpenAI-compatible. It does not guarantee the upstream image API uses OpenAI native semantics. When a gateway expects a different wire format, set default_image_api_dialect in EXTEND.md, OPENAI_IMAGE_API_DIALECT, or --imageApiDialect:
openai-native: pixel size (1536x1024) and native OpenAI quality fieldsratio-metadata: aspect-ratio size (16:9) plus metadata.resolution (1K|2K|4K) and metadata.orientationUse openai-native for the OpenAI native API or strict clones; try ratio-metadata for compatibility gateways in front of Gemini or similar models. Current limitation: ratio-metadata applies only to text-to-image; reference-image edits still need openai-native or a provider with first-class edit support.
Each provider has its own quirks (model families, size rules, ref support, limits). Read these when the user picks that provider or asks for non-default behavior:
| Provider | Reference |
|---|---|
| DashScope (Qwen-Image families, custom sizes) | references/providers/dashscope.md |
| Z.AI (GLM-Image, cogview-4) | references/providers/zai.md |
| MiniMax (image-01, subject-reference) | references/providers/minimax.md |
OpenRouter (multimodal models, /chat/completions flow) | references/providers/openrouter.md |
| Replicate (nano-banana, Seedream, Wan) | references/providers/replicate.md |
Codex CLI (wraps bundled scripts/codex-imagegen/; Codex login, no OPENAI_API_KEY) | references/providers/codex-cli.md |
| Agnes (agnes-image-2.5-flash, reference-image support) | references/providers/agnes.md |
--ref provided + no --provider → auto-select Google → OpenAI → Azure → OpenRouter → Replicate → Seedream → MiniMax → Agnes (MiniMax's subject reference is more specialized toward character/portrait consistency)--provider specified → use it (if --ref, must be google/openai/azure/openrouter/replicate/seedream/minimax/codex-cli/agnes)codex-cli is never auto-selected — set default_provider: codex-cli in EXTEND.md or pass --provider codex-cli. It spawns codex exec via the bundled scripts/codex-imagegen/main.ts TS entrypoint (run with bun) and uses the user's Codex subscription (no OPENAI_API_KEY). Requires codex on PATH with an active codex login.| Preset | Google imageSize | OpenAI size | OpenRouter size | Replicate resolution | Use case |
|---|---|---|---|---|---|
normal | 1K | 1024px target | 1K | 1K | Quick previews |
2k (default) | 2K | 2048px target | 2K | 2K | Covers, illustrations, infographics |
Google/OpenRouter imageSize can be overridden with --imageSize 1K|2K|4K.
For OpenAI native gpt-image-2.5-* and gpt-image-2, normal maps to quality=medium and a low-latency valid size near the requested aspect ratio; 2k maps to quality=high and 2048px-class sizes such as 2048x2048, 2048x1152, or 1152x2048. Use explicit --size for valid custom or 4K outputs, e.g. 3840x2160.
Supported: 1:1, 16:9, 9:16, 4:3, 3:4, 2.35:1.
imageConfig.aspectRatiogpt-image-2.5-* and gpt-image-2 use the closest valid custom size for the requested ratio; older GPT Image and DALL·E models use their closest supported fixed sizeimageGenerationOptions.aspect_ratio; if only --size <WxH> is given, the ratio is inferredgoogle/nano-banana* uses aspect_ratio, bytedance/seedream-* uses documented Replicate ratios, Wan 2.7 maps --ar to a concrete sizeaspect_ratio values; if --size <WxH> is given without --ar, sends width/height for image-01Default: sequential. Batch parallel: enabled automatically when --batchfile contains 2+ pending tasks.
| Situation | Prefer | Why |
|---|---|---|
| One image, or 1-2 simple images | Sequential | Lower coordination overhead, easier debugging |
| Multiple images with saved prompt files | Batch (--batchfile) | Reuses finalized prompts, applies shared throttling/retries, predictable throughput |
| Each image still needs its own reasoning / prompt writing / style exploration | Subagents | Work is still exploratory, each needs independent analysis |
Input is outline.md + prompts/ (e.g. from baoyu-article-illustrator) | Batch — use {baseDir}/scripts/build-batch.ts to assemble the payload | The outline + prompt files already contain everything needed |
Rule of thumb: once prompt files are saved and the task is "generate all of these", prefer batch over subagents. Use subagents only when generation is coupled with per-image thinking or divergent creative exploration.
Parallel behavior:
--jobs <count>If --provider openai --model gpt-image-2.5-flare fails because OPENAI_API_KEY is missing but the current runtime has a native image-generation backend or the repo-level codex-imagegen wrapper is available, use that path rather than leaving the user waiting. Be explicit about whether the fallback is true reference-image generation or only a text-prompt reconstruction from extracted visual traits. See references/codex-image2-fallback.md.
| File | Content |
|---|---|
references/usage-examples.md | Extended CLI examples across providers and batch mode |
references/codex-oauth-vs-openai-api-key.md | Why Codex/ChatGPT OAuth image2 entitlement is not usable through baoyu-image-gen's standard OpenAI API-key provider |
references/codex-image2-fallback.md | Practical fallback behavior when OpenAI API credentials are absent but Codex/native image generation is available |
references/providers/dashscope.md | DashScope families, sizes, limits |
references/providers/zai.md | Z.AI GLM-image / cogview-4 |
references/providers/minimax.md | MiniMax image-01 + subject reference |
references/providers/openrouter.md | OpenRouter multimodal flow |
references/providers/replicate.md | Replicate supported families + guardrails |
references/providers/agnes.md | Agnes (agnes-image-2.5-flash) sizing, refs, and limits |
references/config/preferences-schema.md | EXTEND.md schema |
references/config/first-time-setup.md | First-time setup flow |
Custom configurations via EXTEND.md. See Step 0 for paths and schema.
© JimLiu, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 49 other files (scripts, references) in skills/baoyu-image-gen of JimLiu/baoyu-skills.
Open the folder on GitHubat commit 1567581
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in JimLiu/baoyu-skills, which our catalogue first saw on October 7, 2026.
Baoyu Image Gen next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Baoyu Image Gen this skillJimLiu/baoyu-skills | 27k | 1 repos | ~5.3k | Automated safety check: Notes | MIT | |
| Baoyu Imagineguanyang/open-agent-hub | 977 | — | ~4.6k | Automated safety check: Notes | MIT | |
| Baoyu ImagineLeoYeAI/openclaw-master-skills | 2.2k | — | ~5.1k | Automated safety check: Notes | MIT | |
| Media Toolstherichardngai-code/gpt-image-2-pro-max | 101 | — | ~1.5k | Automated safety check: Notes | MIT | |
| Image Genopen-octo/octo-agent | 125 | — | ~3.1k | Automated safety check: Notes | MIT | |
| 9Router Image Generationdecolua/9router | 31k | — | ~830 | Automated safety check: Pass | MIT |
guanyang/open-agent-hub
AI image generation with OpenAI GPT Image 2, Azure OpenAI, Google, OpenRouter, DashScope, Z.AI GLM-Image, MiniMax, Jimeng, Seedream and Replicate APIs.
LeoYeAI/openclaw-master-skills
AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs.
therichardngai-code/gpt-image-2-pro-max
Two CLI tools for image generation + vision analysis using goclaw's provider-chain pattern.
open-octo/octo-agent
Acquire images as files — generate them with an AI image model (14 providers: OpenAI/gpt-image, Gemini, Qwen, Zhipu, Volcengine, Stability, FLUX, Ideogram, MiniMax, and more), search openly-licensed…
decolua/9router
Generates images through a 9Router gateway's image endpoint, with model discovery, the request fields and per-provider quirks for OpenAI, Gemini, MiniMax and others.
centminmod/my-claude-code-setup
Generate, edit-from-reference, or analyze images with AI via OpenRouter (Gemini, GPT Image, Seedream, Qwen, MAI, Grok, FLUX.2, Recraft, Muse, Riverflow; Cloudflare AI Gateway BYOK).
JimLiu/baoyu-skills
Reformats plain text or Markdown articles with frontmatter, a title, a summary, headings, bold, lists and code blocks, and saves a separate formatted copy.
JimLiu/baoyu-skills
Saves tweets, threads and X Articles as Markdown files with YAML front matter, using an unofficial API that asks for your consent first.
JimLiu/baoyu-skills
Creates standalone dark-themed SVG diagrams, including architecture, flowchart, sequence, structural, mind map, timeline and state machine types.
JimLiu/baoyu-skills
Publishes articles and image-text posts to a WeChat Official Account through the API or Chrome CDP, converting markdown to WeChat-ready HTML with link citations.
JimLiu/baoyu-skills
Compresses images to WebP by default, or to PNG or JPEG, picking the best available tool on the machine and optionally processing whole folders.
JimLiu/baoyu-skills
Generates text and images through an unofficial, reverse-engineered Gemini Web API, supporting reference images and multi-turn conversations.
Categories
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. Baoyu Image Gen is an agent skill from JimLiu/baoyu-skills.AI GLM-Image, MiniMax, Jimeng, Seedream, Replicate and Agnes APIs.
Baoyu Image Gen fits situations like: already has multiple prompts; wants stable multi-image throughput; user asks to generate.
Run `npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a claude-code`. Or copy the skill folder (skills/baoyu-image-gen in JimLiu/baoyu-skills) into .claude/skills/baoyu-image-gen in your project. Claude Code loads it when a task matches its description.
Run `npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a codex`. Or copy the skill folder (skills/baoyu-image-gen in JimLiu/baoyu-skills) into .agents/skills/baoyu-image-gen in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add JimLiu/baoyu-skills --skill baoyu-image-gen -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/baoyu-image-gen, .gemini/skills/baoyu-image-gen, .github/skills/baoyu-image-gen and .opencode/skills/baoyu-image-gen in your project.
Going by SKILL.md and its folder, Baoyu Image Gen needs TypeScript for the scripts in its folder, the command-line tools its instructions call (codex, npx and brew) and credentials named OPENAI_API_KEY, AZURE_OPENAI_API_KEY, OPENROUTER_API_KEY and GOOGLE_API_KEY. Our summary lists: Node.js; A credential in OPENAI_API_KEY; A credential in AZURE_OPENAI_API_KEY.
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Baoyu Image Gen is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.3k tokens (SKILL.md is roughly 21k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 12k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Baoyu Image Gen: Baoyu Imagine (guanyang/open-agent-hub, 977 stars), Baoyu Imagine (LeoYeAI/openclaw-master-skills, 2.2k stars), Media Tools (therichardngai-code/gpt-image-2-pro-max, 101 stars) and Image Gen (open-octo/octo-agent, 125 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
JimLiu (a GitHub user) maintains it in JimLiu/baoyu-skills, which has 26,507 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on September 10, 2026.
Source: JimLiu/baoyu-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.