Agent skill

Baoyu Imagine

by LeoYeAI in LeoYeAI/openclaw-master-skills

AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs.

MITAuto-check: notesMedia & Creative

Install Baoyu Imagine

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill baoyu-imagine -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills baoyu-imagine --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/baoyu-imagine .claude/skills/baoyu-imagine && rm -rf skills-src

Use ~/.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/

Facts

Skill name
baoyu-imagine
GitHub stars
2.2k
Token cost
~5.1k tokens
SKILL.md length
1,594 words
Files
25 (incl. scripts, references)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs.

  • Works in 3 steps: {baseDir} = this SKILL.md file's directory → Script path = {baseDir}/scripts/main.ts → Resolve ${BUN_X} runtime: if bun…
  • Already has multiple prompts
  • SKILL.md covers Script Directory, Step 0: Load Preferences ⛔…, Usage and Options, plus 8 more sections
  • Runs TypeScript scripts from its folder; calls npx; reaches openrouter.ai and api.minimax.io; needs OPENAI_API_KEY and AZURE_OPENAI_API_KEY

What it does

Baoyu Imagine is an agent skill from LeoYeAI/openclaw-master-skills. AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate 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 5.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 28 other files, including scripts and reference files (for example `_meta.json`, `references/config/first-time-setup.md` and `references/config/preferences-schema.md`).

It sits in Media & Creative, covering Image generation and Model routing and gateways. It works with Azure OpenAI, MiniMax, OpenAI and OpenRouter. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Already has multiple prompts
  • Wants stable multi-image throughput
  • User asks to generate

Example prompts

  • “/baoyu-imagine”

Requirements

  • Node.js
  • A credential in OPENAI_API_KEY
  • A credential in AZURE_OPENAI_API_KEY

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 13 files in scripts/ (TypeScript, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • openrouter.ai
    • api.minimax.io
    • visual.volcengineapi.com
    • ark.cn-beijing.volces.com

    Also links to:

    • help.aliyun.com
    • platform.minimax.io

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • OPENAI_API_KEY
    • AZURE_OPENAI_API_KEY
    • OPENROUTER_API_KEY
    • GOOGLE_API_KEY
    • DASHSCOPE_API_KEY
    • MINIMAX_API_KEY
    • REPLICATE_API_TOKEN
    • JIMENG_ACCESS_KEY_ID
    • JIMENG_SECRET_ACCESS_KEY
    • ARK_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Baoyu Imagine loads about 5.1k tokens when it runs, and up to ~8.6k if it reads all its reference files. Until then it costs about 108 tokens; SKILL.md has 1,594 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~108
When it runs · the whole SKILL.md, loaded when a task matches
~5.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~8.6k

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.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NoteMentions a .env fileSKILL.md:215
    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.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 1,594 words, ~5,092 tokens.

Download SKILL.mdSave it as .claude/skills/baoyu-imagine/SKILL.md (or your agent's skills folder). This skill also uses 24 other files; get the full folder from GitHub.
name
baoyu-imagine
description
AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate 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.
version
1.56.4

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):

bash
# 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
# 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" }
ResultAction
FoundLoad, 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.

PathLocation
.baoyu-skills/baoyu-imagine/EXTEND.mdProject directory
$HOME/.baoyu-skills/baoyu-imagine/EXTEND.mdUser home

Legacy compatibility: if .baoyu-skills/baoyu-image-gen/EXTEND.md exists and the new path does not, runtime renames it to baoyu-imagine. If both files exist, runtime leaves them unchanged and uses the new path.

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

bash
# 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
json
{
  "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

OptionDescription
--prompt <text>, -pPrompt 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|replicateForce provider (default: auto-detect)
--model <id>, -mModel 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|2kQuality preset (default: 2k)
--imageSize 1K|2K|4KImage 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
--jsonJSON output

Environment Variables

VariableDescription
OPENAI_API_KEYOpenAI API key
AZURE_OPENAI_API_KEYAzure OpenAI API key
OPENROUTER_API_KEYOpenRouter API key
GOOGLE_API_KEYGoogle API key
DASHSCOPE_API_KEYDashScope API key (阿里云)
MINIMAX_API_KEYMiniMax API key
REPLICATE_API_TOKENReplicate API token
JIMENG_ACCESS_KEY_IDJimeng (即梦) Volcengine access key
JIMENG_SECRET_ACCESS_KEYJimeng (即梦) Volcengine secret key
ARK_API_KEYSeedream (豆包) Volcengine ARK API key
OPENAI_IMAGE_MODELOpenAI model override
AZURE_OPENAI_DEPLOYMENTAzure default deployment name
AZURE_OPENAI_IMAGE_MODELBackward-compatible alias for Azure default deployment/model name
OPENROUTER_IMAGE_MODELOpenRouter model override (default: google/gemini-3.1-flash-image-preview)
GOOGLE_IMAGE_MODELGoogle model override
DASHSCOPE_IMAGE_MODELDashScope model override (default: qwen-image-2.0-pro)
MINIMAX_IMAGE_MODELMiniMax model override (default: image-01)
REPLICATE_IMAGE_MODELReplicate model override (default: google/nano-banana-pro)
JIMENG_IMAGE_MODELJimeng model override (default: jimeng_t2i_v40)
SEEDREAM_IMAGE_MODELSeedream model override (default: doubao-seedream-5-0-260128)
OPENAI_BASE_URLCustom OpenAI endpoint
AZURE_OPENAI_BASE_URLAzure resource endpoint or deployment endpoint
AZURE_API_VERSIONAzure image API version (default: 2025-04-01-preview)
OPENROUTER_BASE_URLCustom OpenRouter endpoint (default: https://openrouter.ai/api/v1)
OPENROUTER_HTTP_REFEREROptional app/site URL for OpenRouter attribution
OPENROUTER_TITLEOptional app name for OpenRouter attribution
GOOGLE_BASE_URLCustom Google endpoint
DASHSCOPE_BASE_URLCustom DashScope endpoint
MINIMAX_BASE_URLCustom MiniMax endpoint (default: https://api.minimax.io)
REPLICATE_BASE_URLCustom Replicate endpoint
JIMENG_BASE_URLCustom Jimeng endpoint (default: https://visual.volcengineapi.com)
JIMENG_REGIONJimeng region (default: cn-north-1)
SEEDREAM_BASE_URLCustom Seedream endpoint (default: https://ark.cn-beijing.volces.com/api/v3)
BAOYU_IMAGE_GEN_MAX_WORKERSOverride batch worker cap
BAOYU_IMAGE_GEN_<PROVIDER>_CONCURRENCYOverride provider concurrency, e.g. BAOYU_IMAGE_GEN_REPLICATE_CONCURRENCY
BAOYU_IMAGE_GEN_<PROVIDER>_START_INTERVAL_MSOverride 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:

Rationormal2k
1:11024*10241536*1536
2:3768*11521024*1536
3:21152*7681536*1024
3:4960*12801080*1440
4:31280*9601440*1080
9:16720*12801080*1920
16:91280*7201920*1080
21:91344*5762048*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:

Show full SKILL.md (682 more words)Show less
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:

bash
# 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

PresetGoogle imageSizeOpenAI SizeOpenRouter sizeReplicate resolutionUse Case
normal1K1024px1K1KQuick previews
2k (default)2K2048px2K2KCovers, 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.

ModeWhen to Use
Sequential (default)Normal usage, single images, small batches
Parallel batchBatch mode with 2+ tasks

Execution choice:

SituationPreferred approachWhy
One image, or 1-2 simple imagesSequentialLower coordination overhead and easier debugging
Multiple images already have saved prompt filesBatch (--batchfile)Reuses finalized prompts, applies shared throttling/retries, and gives predictable throughput
Each image still needs separate reasoning, prompt writing, or style explorationSubagentsThe 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.

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 24 other files (scripts, references) in skills/baoyu-imagine of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • _meta.json
  • references/config/first-time-setup.md
  • references/config/preferences-schema.md
  • scripts/main.test.ts
  • scripts/main.ts
  • scripts/providers/azure.test.ts
  • scripts/providers/azure.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
  • … and 8 more

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Baoyu Imagine 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.

Baoyu Imagine compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Baoyu Imagine this skillLeoYeAI/openclaw-master-skills2.2k—~5.1kAutomated safety check: NotesMIT
Media Toolstherichardngai-code/gpt-image-2-pro-max101—~1.5kAutomated safety check: NotesMIT
Baoyu Image GenJimLiu/baoyu-skills27k1 repos~5.3kAutomated safety check: NotesMIT
Baoyu Imagineguanyang/open-agent-hub977—~4.6kAutomated safety check: NotesMIT
AI Image Creatorevolution-foundation/evo-nexus545—~5.1kAutomated safety check: NotesCustom licence
Generate ImageK-Dense-AI/claude-scientific-writer2.4k1 repos~3.8kAutomated safety check: NotesMIT

Similar skills

  • Media Tools

    therichardngai-code/gpt-image-2-pro-max

    Two CLI tools for image generation + vision analysis using goclaw's provider-chain pattern.

    101 GitHub stars~1.5k tokensUpdated 4 mo ago
    Media & CreativeAuto-check: notes
  • Baoyu Image Gen

    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.

    27k GitHub starsUsed in 1 repo~5.3k tokens
    Media & CreativeAuto-check: notes
  • 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.

    977 GitHub stars~4.6k tokensUpdated today
    Media & CreativeAuto-check: notes
  • AI Image Creator

    evolution-foundation/evo-nexus

    Generates PNG images through OpenRouter models, with transparent backgrounds and reference-image edits, and describes existing images with multimodal vision.

    545 GitHub stars~5.1k tokensUpdated 5 mo ago
    Media & CreativeAuto-check: notes
  • Generate Image

    K-Dense-AI/claude-scientific-writer

    Generate or edit images with AI models through the OpenRouter Image API (Gemini, Seedream, Recraft, GPT-Image, Riverflow).

    2.4k GitHub starsUsed in 1 repo~3.8k tokens
    Media & CreativeAuto-check: notes
  • Aigen Image Generation

    Peiiii/nextclaw

    Use the local aigen CLI to generate images through configured providers such as OpenRouter or OpenAI.

    260 GitHub stars~1.3k tokensUpdated yesterday
    Media & CreativeAuto-check passed

More from LeoYeAI/openclaw-master-skills

All 1,200 skills in this repo
  • DevOps Pipeline Management

    LeoYeAI/openclaw-master-skills

    Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.

    2.2k GitHub stars~4.2k tokensUpdated 2 mo ago
    Auto-check: notes
  • Feishu Document Collaboration

    LeoYeAI/openclaw-master-skills

    Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.

    2.2k GitHub stars~2k tokensUpdated 2 mo ago
    Auto-check passed
  • Files Memory System

    LeoYeAI/openclaw-master-skills

    Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.

    2.2k GitHub stars~3.8k tokensUpdated 2 mo ago
    Auto-check passed
  • GEO-Claw AI Visibility Agent

    LeoYeAI/openclaw-master-skills

    Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.

    2.2k GitHub stars~4.7k tokensUpdated 2 mo ago
    Auto-check passed
  • Google Workspace CLI

    LeoYeAI/openclaw-master-skills

    Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.

    2.2k GitHub stars~2.6k tokensUpdated 2 mo ago
    Auto-check: notes
  • HealthFit Health Advisors

    LeoYeAI/openclaw-master-skills

    Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.

    2.2k GitHub stars~4.4k tokensUpdated 2 mo ago
    Auto-check passed

Questions about Baoyu Imagine

What does Baoyu Imagine do?

AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs. Baoyu Imagine is an agent skill from LeoYeAI/openclaw-master-skills. AI image generation with OpenAI, Azure OpenAI, Google, OpenRouter, DashScope, MiniMax, Jimeng, Seedream and Replicate APIs.

When should I use Baoyu Imagine?

Baoyu Imagine fits situations like: already has multiple prompts; wants stable multi-image throughput; user asks to generate.

How do I install Baoyu Imagine in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill baoyu-imagine -a claude-code`. Or copy the skill folder (skills/baoyu-imagine in LeoYeAI/openclaw-master-skills) into .claude/skills/baoyu-imagine in your project. Claude Code loads it when a task matches its description.

How do I install Baoyu Imagine in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill baoyu-imagine -a codex`. Or copy the skill folder (skills/baoyu-imagine in LeoYeAI/openclaw-master-skills) into .agents/skills/baoyu-imagine in your project. Codex loads it when a task matches its description.

Can I use Baoyu Imagine in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill baoyu-imagine -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-imagine, .gemini/skills/baoyu-imagine, .github/skills/baoyu-imagine and .opencode/skills/baoyu-imagine in your project.

What does Baoyu Imagine need to run?

Going by SKILL.md and its folder, Baoyu Imagine needs TypeScript for the scripts in its folder, the command-line tools its instructions call (npx) 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.

Does Baoyu Imagine access the network?

SKILL.md names 6 domains. In commands or code: openrouter.ai, api.minimax.io, visual.volcengineapi.com and ark.cn-beijing.volces.com; the agent is likely to contact these when it follows the instructions. As links in the text: help.aliyun.com and platform.minimax.io. This is read from the text; nothing was executed.

Is Baoyu Imagine safe to install?

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.

What licence does Baoyu Imagine use?

Baoyu Imagine is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Baoyu Imagine use?

About 5.1k tokens (SKILL.md is roughly 20k 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 3.6k tokens, read only when the agent opens those files.

What are the alternatives to Baoyu Imagine?

Skills that share tags, products or a category with Baoyu Imagine: Media Tools (therichardngai-code/gpt-image-2-pro-max, 101 stars), Baoyu Image Gen (JimLiu/baoyu-skills, 27k stars), Baoyu Imagine (guanyang/open-agent-hub, 977 stars) and AI Image Creator (evolution-foundation/evo-nexus, 545 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Baoyu Imagine?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.