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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,第三方扫描有未通过项,按安装量在图像处理类的 1,562 个 Skill 里排第 1,457。

总安装 272周安装 11GitHub Stars 公开资料未说明下载 85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/stonehah/qunz-skills
仓库路径:skills/baoyu-image-gen
安装命令:
npx skills add https://github.com/stonehah/qunz-skills --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/stonehah/qunz-skills --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。

baoyu-image-gen 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。

安装命令:npx skills add https://github.com/stonehah/qunz-skills --skill baoyu-image-gen

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/stonehah/qunz-skills --skill baoyu-image-gen;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/stonehah/qunz-skills --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 272 次,近一周安装 11 次,下载 85 次。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?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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

272—接触敏感数据未明确未通过

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, DashScope (阿里通义万象), Replicate and APIMart 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):

# macOS, Linux, WSL, Git Bash
test -f .baoyu-skills/baoyu-image-gen/EXTEND.md && echo "project"
test -f "${XDG_CONFIG_HOME:-$HOME/.config}/baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "xdg"
test -f "$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.md" && echo "user"
# PowerShell (Windows)
if (Test-Path .baoyu-skills/baoyu-image-gen/EXTEND.md) { "project" }
$xdg = if ($env:XDG_CONFIG_HOME) { $env:XDG_CONFIG_HOME } else { "$HOME/.config" }
if (Test-Path "$xdg/baoyu-skills/baoyu-image-gen/EXTEND.md") { "xdg" }
if (Test-Path "$HOME/.baoyu-skills/baoyu-image-gen/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-image-gen/EXTEND.mdProject directory
$HOME/.baoyu-skills/baoyu-image-gen/EXTEND.mdUser home

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 multimodal or OpenAI edits)
${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

# 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

# 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

# APIMart (Gemini-3-Pro-Image-preview, async task polling)
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cat in watercolor style" --image out.png --provider apimart

# APIMart with reference image
${BUN_X} {baseDir}/scripts/main.ts --prompt "Make this into anime style" --image out.png --provider apimart --ref source.png

# APIMart with doubao-seedream-5-0-lite model
${BUN_X} {baseDir}/scripts/main.ts --prompt "A cinematic mountain sunrise" --image out.png --provider apimart --model doubao-seedream-5-0-lite

# 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\dashscope\replicate\apimart`Force provider (default: auto-detect)
--model <id>, -mModel ID (Google: gemini-3-pro-image-preview, gemini-3.1-flash-image-preview; OpenAI: gpt-image-1.5, gpt-image-1; APIMart: gemini-3-pro-image-preview, doubao-seedream-5-0-lite)
--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/APIMart (default: from quality)
--ref <files...>Reference images. Supported by Google multimodal, OpenAI GPT Image edits, Replicate, and APIMart
--n <count>Number of images for the current task (APIMart currently supports only 1)
--jsonJSON output

Environment Variables

VariableDescription
OPENAI_API_KEYOpenAI API key
GOOGLE_API_KEYGoogle API key
DASHSCOPE_API_KEYDashScope API key (阿里云)
REPLICATE_API_TOKENReplicate API token
APIMART_API_KEYAPIMart API key
OPENAI_IMAGE_MODELOpenAI model override
GOOGLE_IMAGE_MODELGoogle model override
DASHSCOPE_IMAGE_MODELDashScope model override (default: z-image-turbo)
REPLICATE_IMAGE_MODELReplicate model override (default: google/nano-banana-pro)
APIMART_IMAGE_MODELAPIMart model override (default: gemini-3-pro-image-preview, e.g. doubao-seedream-5-0-lite)
OPENAI_BASE_URLCustom OpenAI endpoint
GOOGLE_BASE_URLCustom Google endpoint
DASHSCOPE_BASE_URLCustom DashScope endpoint
REPLICATE_BASE_URLCustom Replicate endpoint
APIMART_BASE_URLCustom APIMart endpoint (default: https://api.apimart.ai)
APIMART_TASK_LANGUAGETask status language for polling (default: en)
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

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 Replicate, then APIMart
  2. --provider specified → use it (if --ref, must be google, openai, replicate, or apimart)
  3. Only one API key available → use that provider
  4. Multiple available → default to Google

Quality Presets

PresetGoogle imageSizeOpenAI SizeReplicate resolutionUse Case
normal1K1024px1KQuick previews
2k (default)2K2048px2KCovers, illustrations, infographics

Google/APIMart 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
  • 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
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 (switch to Google multimodal: gemini-3-pro-image-preview, gemini-3.1-flash-image-preview; OpenAI GPT Image edits; Replicate; or APIMart)

Extension Support

Custom configurations via EXTEND.md. See Preferences section for paths and supported options.

平台分布

Codex

35.42%
按下载量换算30

Claude

31.59%
按下载量换算27

Cursor

16.95%
按下载量换算14

Gemini CLI

8.42%
按下载量换算7

安全审计

Gen Agent Trust Hub

未通过

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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