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Agent Skill · 图像处理

vpick-image-generator(vpick 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。

vpick-image-generator 是图像处理类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,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 598。

总安装 3,998周安装 170GitHub Stars 公开资料未说明下载 1,401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
MIT-0
版本
1.0.2

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:vpick-image-generator(vpick 图像生成器)
来源仓库:https://github.com/snoopyrain/vpick-image-generator
安装命令:
openclaw skills install vpick-image-generator
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install vpick-image-generator

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。

用于在视觉画布上生成多模型 AI 图像,支持 Midjourney、Grok Imagine 等主流工具。适合辅助图像生成、编辑和视觉素材处理,可调用文本转图片、背景处理和提示词整理功能。使用时需确认输入图片版权、输出格式及模型限制,涉及人物或品牌素材时应核对授权与合规性。

通过 clawhub 安装,适用于 OpenClaw 宿主环境,需确保网络连接和 API 密钥配置正确。注意不同模型的输出差异,建议结合具体需求选择参数,避免生成侵权或不适宜内容。

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 OpenClaw;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 openclaw skills install vpick-image-generator;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

vpick-image-generator 怎么安装?

在终端执行 openclaw skills install vpick-image-generator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

vpick-image-generator 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

vpick-image-generator 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。

vpick-image-generator 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

vpick-image-generator 用的人多吗?

公开数据是累计安装 3,998 次,近一周安装 170 次,下载 1,401 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。

vpick-image-generator 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 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。
  • 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 OpenClaw,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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

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
vpick-image-generator

vpick 图像生成器 · 本页

3,998—接触敏感数据MIT-0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

name
vpick-image-generator
description
Multi-model AI image generation on a visual canvas. Supports Midjourney (relaxed/fast/turbo, v7.0, 4-image grid), Grok Imagine (6 images per call, auto I2I), nano-banana-2 (multi-reference), Seedream 5.0 (up to 3K HD). Features: text-to-image, image-to-image, style transfer, multi-reference composition, batch generation, aspect ratio control. Use when the user says 'generate image', 'create an image', 'AI image', 'Midjourney', 'generate artwork', 'character design', 'create illustration', or wants AI image generation.
version
1.0.1
metadata
openclaw
emoji
🎨
homepage
https://vpick-doc.10xboost.org/guide/mcp-connection.html

VPick Image Generator

Multi-model AI image generation on a visual canvas — Midjourney, Grok, nano-banana, Seedream — with reference image support, style transfer, and batch generation. Powered by VPick.

Security & Data Handling

  • Authentication: Your MCP link contains an embedded token — no separate API keys or credentials are needed or sent. Treat your MCP link like a password.
  • Data flow: All generation requests go through VPick's server (vpick.10xboost.org on Google Cloud). VPick routes requests to third-party AI model providers (Midjourney, Grok, Seedream, etc.) on your behalf. Your prompts and uploaded reference images are sent to these providers for processing.
  • Storage: Generated images are stored in Google Cloud Storage under your VPick account.
  • No local credentials: This skill does not require any local API keys, environment variables, or secrets.
  • Billing: Generation costs are charged to your VPick credit balance, not directly to any third-party service.

Prerequisites

  1. Sign up at vpick.10xboost.org (Google OAuth — new users get $1 free credit)
  2. Get your MCP link: Go to Settings → copy your MCP Server URL (contains your auth token)
  3. Add to Claude: Paste the MCP link into Claude settings as a Connector — no install, no API keys needed

Available Image Models

ModelCostOutputBest For
nano-banana-2$0.16/image1 imageDefault, fast, multi-reference support
Midjourney Relaxed$0.045/grid4 images (grid)Budget artistic generation
Midjourney Fast$0.12/grid4 images (grid)Quick artistic generation
Midjourney Turbo$0.24/grid4 images (grid)Fastest Midjourney
Grok Imagine$0.06/call6 images (T2I) or 2 (I2I)Budget bulk generation
Seedream 5.0 Lite$0.0825/image1 image (2K)High resolution, affordable
Seedream 5.0 HD$0.0825/image1 image (3K)Ultra high resolution

Aspect Ratios: 1:1, 16:9, 9:16, 3:4, 4:3 (all models)

Core Workflow

Step 1: Set Up

Check user's canvas and project:

get_canvas          → See current state
list_projects       → Check existing projects
create_project      → Start fresh if needed

Step 2: Create Image Generator Node

add_node(type: "image-generator", name: "My Image")

Step 3: Set the Prompt

Option A — Direct prompt:

update_node(id: "<node_id>", data: { prompt: "a cyberpunk cityscape at sunset, neon lights, rain reflections" })

Option B — Connect a Text node:

add_node(type: "text", name: "Prompt", data: { content: "a cyberpunk cityscape at sunset" })
connect_nodes(sourceId: "<text_node>", targetId: "<image_node>", sourceHandle: "text-out", targetHandle: "prompt-in")

Step 4: Add Reference Images (Optional)

Reference images guide the generation style or subject. Up to 10 reference images supported.

upload_image(url: "https://example.com/reference.jpg")
connect_nodes(sourceId: "<upload_node>", targetId: "<image_node>", sourceHandle: "file-out", targetHandle: "image-in")

Use @NodeLabel in prompts to reference connected images:

"A portrait in the style of @reference, vibrant colors"

The @reference is resolved at generation time to the connected image URL.

Step 5: Generate

run_image_generator(
  nodeId: "<image_node>",
  prompt: "a cyberpunk cityscape at sunset, neon lights",
  model: "nano-banana-2",
  aspectRatio: "16:9"
)

Midjourney-specific options:

run_image_generator(
  nodeId: "<image_node>",
  prompt: "a cyberpunk cityscape at sunset",
  model: "midjourney",
  aspectRatio: "16:9",
  mjSpeed: "fast",        // "relaxed", "fast", "turbo"
  mjVersion: "7.0"        // Midjourney version
)

Grok — auto-detects T2I vs I2I:

  • No reference image → Text-to-Image (6 images)
  • With reference image → Image-to-Image (2 images)

Step 6: Browse Results

Models may generate multiple images:

  • Midjourney: 4-image grid — browse via currentImageIndex (0-3)
  • Grok: 6 images (T2I) or 2 images (I2I)
  • Others: 1 image

Check results:

get_node(id: "<image_node>")   → See generatedImageUrl, status
list_nodes                      → Overview of all nodes

Step 7: Use Generated Images

Generated images can be used as input for:

  • Video generation: Connect to VideoGenerator's start-image-in port
  • More image generation: Connect as reference for another ImageGenerator
  • Character consistency: Use as Element reference in MultiShot video
connect_nodes(sourceId: "<image_node>", targetId: "<video_node>", sourceHandle: "image-out", targetHandle: "start-image-in")

Common Use Cases

Character Design (White Background References)

For video production, generate character references on white backgrounds:

run_image_generator(
  nodeId: "<node>",
  prompt: "full body portrait of a young woman, casual outfit, white background, isolated figure, front view",
  model: "nano-banana-2",
  aspectRatio: "3:4"
)

Generate multiple angles (front, side, 3/4) for use as MultiShot Elements.

Batch Generation

Create multiple ImageGenerator nodes and generate in parallel:

add_node(type: "image-generator", name: "Variant A")
add_node(type: "image-generator", name: "Variant B")
add_node(type: "image-generator", name: "Variant C")
run_image_generator(nodeId: "<A>", prompt: "sunset beach, warm tones", model: "midjourney")
run_image_generator(nodeId: "<B>", prompt: "sunset beach, cool tones", model: "grok-imagine")
run_image_generator(nodeId: "<C>", prompt: "sunset beach, dramatic", model: "nano-banana-2")

Style Transfer with References

upload_image(url: "https://example.com/style-reference.jpg")
connect_nodes(sourceId: "<upload>", targetId: "<image_node>", sourceHandle: "file-out", targetHandle: "image-in")
run_image_generator(
  nodeId: "<image_node>",
  prompt: "a portrait in the style of @style-reference, detailed, high quality",
  model: "nano-banana-2"
)

Organize Your Canvas

Keep things tidy:

auto_layout(nodeIds: [...], direction: "horizontal", spacing: 200)
create_group(nodeIds: [...], overrides: { label: "Character Designs", color: "#E57373" })

Check Usage & History

list_generated_files(limit: 20, model: "midjourney")   → Recent generations filtered by model
get_generation_stats                                     → Cost breakdown by model

Tips

  • nano-banana-2 is the best default — fast, affordable, supports multi-reference
  • Midjourney excels at artistic/stylized images — use relaxed speed to save cost
  • Grok is the cheapest for bulk generation ($0.06 for 6 images)
  • Seedream produces the highest resolution (up to 3K)
  • White background images are essential for video Element references
  • @NodeLabel references are resolved at generation time — make sure labels match exactly
  • Use list_models tool to check current pricing and available models

Error Handling

ErrorSolution
Generation timeoutAuto-retries up to 2 times; check status with get_node
Insufficient creditsTop up at vpick.10xboost.org
Invalid aspect ratioUse: 1:1, 16:9, 9:16, 3:4, or 4:3
Reference not resolvedEnsure @NodeLabel matches the connected node's label exactly
Node not foundUse list_nodes to get current node IDs

Documentation

  • VPick App: vpick.10xboost.org
  • Available models: Call list_models tool for current pricing and capabilities

适合场景

01

文本生成图片

02

图片风格化

03

产品图和创意图

04

需要 FLUX 模型时

能力概览

能力 1

调用 FLUX 图像模型

能力 2

支持文本生图和图像改写

能力 3

覆盖 LoRA 或风格适配

能力 4

适合创意视觉生成

平台分布

OpenClaw

95.01%
按下载量换算1,331

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

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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