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Agent Skill · 图像处理

baoyu-image-gen(宝玉图像生成器)

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

baoyu-image-gen 是图像处理类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描已通过,按安装量在图像处理类的 1,562 个 Skill 里排第 1,172。

总安装 1,008周安装 42GitHub Stars 5下载 336核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:baoyu-image-gen(宝玉图像生成器)
来源仓库:https://github.com/buda-ai/buda-marketplace
仓库路径:skills/baoyu-image-gen
安装命令:
npx skills add https://github.com/buda-ai/buda-marketplace --skill baoyu-image-gen
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/buda-ai/buda-marketplace --skill baoyu-image-gen

这个 Skill 是做什么的

图像处理类 Skill 处理生成、裁剪、压缩和批量转换图片的任务。

用于辅助图像生成、图片编辑和视觉素材处理工作流。适合根据文本生成图片、处理背景或调用图像模型工具。使用时需确认输入图片、版权来源、输出格式和模型限制。涉及人物、品牌或公开展示素材时应额外核对授权和合规边界。支持 OpenAI、Google、DashScope 等多种图像 API 提供商。

来源仓库内路径:skills/baoyu-image-gen

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/buda-ai/buda-marketplace --skill baoyu-image-g…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

baoyu-image-gen 怎么安装?

在终端执行 npx skills add https://github.com/buda-ai/buda-marketplace --skill baoyu-image-gen。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

baoyu-image-gen 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

baoyu-image-gen 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

baoyu-image-gen 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

baoyu-image-gen 用的人多吗?

公开数据是累计安装 1,008 次,近一周安装 42 次,下载 336 次,GitHub 5 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

baoyu-image-gen 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理图像处理类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

图像处理类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
ai-image-generation

AI 图像生成 · Codex、Claude

4,365,552382调用外部服务未明确有提醒
openai-image-gen

OpenAI 图像生成 · OpenClaw

1,906,88432需要联网MIT-0有提醒
image

图像 · OpenClaw

525,99926需要联网MIT-0通过
baoyu-cover-image

宝玉封面图 · Codex、Claude

474,24016,779只读MIT有提醒
baoyu-image-gen

宝玉图像生成器 · Codex、Claude

468,00716,778接触敏感数据MIT通过
baoyu-image-gen

宝玉图像生成器 · 本页

1,0085接触敏感数据未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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 from the current working directory:

test -f .baoyu-skills/baoyu-image-gen/EXTEND.md && echo "found"
ResultAction
FoundLoad, parse, apply settings. If default_model.[provider] is null → ask model only (Flow 2 in first-time-setup.md)
Not found⛔ STOP. Do NOT generate any images. Read references/config/first-time-setup.md and follow its Flow 1 checklist step by step. This is a multi-turn interactive setup that requires asking the user multiple questions. Resume image generation only after Step 5 (verify) passes.

CRITICAL: The first-time setup is a multi-step interactive workflow, NOT a single action. You must ask the user questions and wait for answers at each step.

PathLocation
.baoyu-skills/baoyu-image-gen/EXTEND.mdRelative to current working directory

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

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\openrouter\dashscope\jimeng\seedream\replicate`Force provider (default: auto-detect)
--model <id>, -mModel 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
--jsonJSON output

Environment Variables

VariableDescription
OPENAI_API_KEYOpenAI API key
OPENROUTER_API_KEYOpenRouter API key
GOOGLE_API_KEYGoogle API key
DASHSCOPE_API_KEYDashScope API key (阿里云)
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
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)
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
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
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

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:

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

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:

# 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

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

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

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.

Attribution

Based on baoyu-image-gen by JimLiu, licensed under MIT. Modified and adapted for the Buda.im platform.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

平台分布

Codex

37.95%
按下载量换算128

Claude

28.4%
按下载量换算95

Cursor

16.64%
按下载量换算56

Gemini CLI

8.9%
按下载量换算30

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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