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visual-references视觉参考

Agent Skill

用于辅助界面设计、视觉规范、排版、配色、布局和交互体验优化。它适合让 Agent 根据产品场景整理页面结构、生成 UI 方案、检查视觉一致性或改进组件层级。使用时需要结合现有品牌、设计系统和用户任务,不应只堆装饰元素;涉及真实页面改动时,应通过截图或浏览器预览检查文本溢出、对齐和响应式表现。

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下载量

1,632
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

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:visual-references(视觉参考)
来源仓库:https://github.com/vdkroon/visual-references
安装命令:
openclaw skills install visual-references
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 visual-references

简介

从 Pexels 搜索并下载视觉参考图像。

  • 适合风格探索、情绪板和构图研究等场景。visual-references 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 输入关键词即可获取高质量免费图片资源。
  • 建议用于激发创作灵感或构建视觉素材库。
  • 使用时需遵守 Pexels 许可协议,确认商用授权范围。

SKILL.md

name
visual-references
description
Search and download visual reference images from Pexels to inspire image or video generation. Use when you need style references, mood boards, composition or color palette inspiration before generating an asset.
metadata
{"clawdbot":{"emoji":"🖼️","requires":{"bins":["python3"],"pip":["requests"],"env":["PEXELS_API_KEY"]}}}

Visual References (Pexels)

Download visual references from Pexels to inspect style, mood, and composition before generating.

When to use

Use when:

  • The brief mentions a specific style, mood, palette, or visual reference ("I want something minimalist", "editorial style", "something like X")
  • The client wants aesthetic coherence with something real or existing
  • The brief is visually vague and searching references would improve the result

Don't use when:

  • The brief is straightforward with no visual ambiguity (colors, text, and layout already defined)
  • You already have references in input_images
  • It's a minor edit of a previously delivered image
  • The brief doesn't mention style and the image is functional/technical

Prerequisites

Requires the PEXELS_API_KEY environment variable (free Pexels API key). The script will fail if the key is not configured. Get one at https://pexels.com/api.

Basic usage

python3 ~/.openclaw/workspace/skills/visual-references/scripts/visual_ref.py "QUERY" [options]

Options

FlagDefaultDescription
--count N5Number of images
--output DIR/tmp/visual-refsOutput folder
--orientationlandscape, portrait, square
--list-onlyList URLs only, no download

Output directory rule (MANDATORY)

ALWAYS use --output /tmp/visual-refs as the output directory. Do NOT invent unique folder names like visual-refs-salon-v2, visual-refs-v3, etc. The script automatically cleans the output folder before each search, so using the same folder every time is safe and prevents accumulation of old references.

Examples

# References for a real estate hero image
python3 visual_ref.py "luxury real estate minimalist nordic" --count 5 --orientation landscape --output /tmp/visual-refs

# Square thumbnails for social media
python3 visual_ref.py "personal branding outdoor golden hour" --count 5 --orientation square --output /tmp/visual-refs

# List only, no download
python3 visual_ref.py "product photography white background" --list-only

IMPORTANT: Usage limits

  • Maximum 3 searches per task. One main query, up to two refinements. Do NOT run dozens of searches looking for the perfect reference.
  • Use --count 5 (not 5) to keep it fast.
  • Pick the best reference from what you get and move on to generation. The references are inspiration, not the final product.

Workflow when you decide to use it

  1. Receive brief with vague style or mentioned inspiration
  2. Translate query to English — Pexels works best in English
  3. Run ONE search with --count 5
  4. Do NOT review or pick — pass ALL 3 references directly to generate_image
  5. Generate with ALL references as input_images (MANDATORY):
   generate_image(
     prompt: "description of the NEW asset to generate (subject, scene, format) — do NOT describe the references, the model sees them",
     input_images: ["/path/to/ref_01_xxx.jpg", "/path/to/ref_02_xxx.jpg", "/path/to/ref_03_xxx.jpg"],
     ...
   )

The generation model sees all references and picks the best style elements. Your prompt describes WHAT to create, not the style — the style comes from the reference images.

IMPORTANT: Do NOT waste tokens reviewing references with read. Do NOT pick a favorite. Pass all downloaded references as input_images and let the generation model decide.

Alternative: user picks references (only when requested)

If the brief explicitly asks to see references first ("enséñame referencias", "muéstrame antes de generar", "quiero elegir yo"), use this flow instead:

  1. Search and download references as usual
  2. Send ALL reference images in a SINGLE message via sessions_send:
   sessions_send(sessionKey="<REPLY_TO>", message="5 referencias de salón editorial:\
\
Archivo: /tmp/visual-refs/ref_01_xxx.jpg\
Archivo: /tmp/visual-refs/ref_02_xxx.jpg\
Archivo: /tmp/visual-refs/ref_03_xxx.jpg\
Archivo: /tmp/visual-refs/ref_04_xxx.jpg\
Archivo: /tmp/visual-refs/ref_05_xxx.jpg\
\
¿Cuál te gusta? Puedo usar una, mezclar varias, o buscar otras.", timeoutSeconds=0)
  1. Wait for user response before generating
  2. Generate with the references the user chose as input_images

CRITICAL: Send references EXACTLY ONCE. Do NOT send them individually AND again in a summary. Do NOT re-send references you already sent. One single message with all file paths, that's it.

Only use this alternative flow when the user EXPLICITLY asks to see references first. Default is always: search → pass all → generate.

Script output

  • Images downloaded to --output as ref_01_<id>.jpg, ref_02_<id>.jpg...
  • refs_meta.json with metadata: path, description, author
  • Attribution printed to stdout (required by Pexels guidelines)

Limits

  • Demo plan: 50 requests/hour — more than enough for creative use
  • Downloaded resolution: ~1080px (regular) — optimal for visual reference
  • Attribution: required for public apps, not for internal/creative use

Effective queries

  • Always in English — better results
  • Be specific: "hero shot luxury car black studio" > "car"
  • Include mood: "cozy home interior warm light bokeh", "cold corporate office minimal"
  • By sector: "restaurant food flat lay", "fashion editorial outdoor", "tech startup office"

适合场景

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能力概览

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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