Token导航 LogoToken导航TokenDH.com
研究检索只读clawhub未标认证来源可访问clear审计通过

aesthetic-copilotaesthetic GitHub Copilot 搜索

Agent Skill

aesthetic-copilot 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,680

周安装

199

GitHub Stars

公开资料未说明

下载量

1,640
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:aesthetic-copilot(aesthetic GitHub Copilot 搜索)
来源仓库:https://github.com/chenchen913/aesthetic-copilot
安装命令:
openclaw skills install aesthetic-copilot
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 aesthetic-copilot

简介

当用户想要基于模糊的布局/内容描述为文本到图像模型(Flux、Ideogram、Midjourney)生成高保真提示时使用。

SKILL.md

name
aesthetic-copilot
description
Use when the user wants to generate high-fidelity PROMPTS for Text-to-Image models (Flux, Ideogram, Midjourney) based on vague layout/content descriptions.

Aesthetic Copilot (v3.4 - Integrated)

Overview

This skill acts as a Meta-Prompt Generator. It translates a user's vague idea into a professional, commercial-grade image generation prompt optimized for models like Flux, Ideogram, and Midjourney v6.

File Map (MANDATORY READ ORDER)

FileRoleWhen to Read
SKILL.mdThis file — entry pointAlways
engine/README.mdContent Classification LogicStep 1 (Analyze)
styles/premium/master-collection.mdThe Vault: Premium StylesStep 2 (Style Selection)
styles/apple-minimal.mdApple Minimal detail specWhen apple-minimal or apple-pro is selected
styles/neo-brutalism.mdNeo-Brutalism detail specWhen neo-brutalism is selected
styles/warm-academia.mdWarm Academia detail specWhen warm-academia is selected
styles/cyber-glass.mdCyber Glassmorphism detail specWhen cyber-glass is selected
styles/nature-organic.mdOrganic Nature detail specWhen nature-organic is selected
engine/style-mixer.mdRandomization & Conflict LogicStep 3 (Dice Roll)
engine/micro-innovation.mdArtistic TwistsStep 4 (Innovation)
layouts/README.mdLayout TemplatesStep 5 (Layout Selection)
prompt-templates/*.mdOutput SkeletonsStep 6 (Generate)

The Workflow (Strict Execution Path)

Step 1 — Analyze & Classify Intent

Action: Read engine/README.md. Apply its classification logic to extract:

  • Keywords from the user's input
  • Sentiment / Mood (Warm, Playful, Serious, Futuristic…)
  • Industry (Tech, Fashion, Education, Food…)
  • Attribute scores: formal_level, color_temp, contrast, complexity

Use these attributes to drive all downstream decisions.

Step 2 — Select Base Style

Action: Read styles/premium/master-collection.md. Match the attributes from Step 1 to the closest style ID.

  • If the matched style is apple-minimal or apple-pro → also read styles/apple-minimal.md for detail tokens.
  • If the matched style is neo-brutalism → also read styles/neo-brutalism.md for detail tokens.
  • If the matched style is warm-academia → also read styles/warm-academia.md for detail tokens.
  • If the matched style is cyber-glass → also read styles/cyber-glass.md for detail tokens.
  • If the matched style is nature-organic → also read styles/nature-organic.md for detail tokens.
  • Fallback: If no confident match, default to apple-pro.

Step 3 — Roll the Dice (Mixer)

Action: Read engine/style-mixer.md. Randomly select (do NOT default to first item):

  • ONE Material Twist from Pool A
  • ONE Lighting Modifier from Pool B
  • ONE Composition Rule from Pool C

Apply the Harmony & Conflict Resolution rules before proceeding.

Step 4 — Inject Micro-Innovation

Action: Read engine/micro-innovation.md.

  • Find the Input Category that matches the user's subject.
  • Apply the corresponding Twist (not the standard depiction).
  • Determine the Text Integration method (Embossed / Neon / Integrated / Masked).

Step 5 — Select Layout

Action: Read layouts/README.md. Match the user's description to a Layout ID:

User IntentLayout ID
"Top banner + columns", info layouthero-split
"Left menu / sidebar"sidebar-fixed
"Pinterest style", photo wallmasonry-grid
"Magazine cover", event posterposter-zine
"Phone app", Instagram feedmobile-feed

Pass the selected Layout ID into the template as [Layout].

Step 6 — Route to Template

Select the correct template based on the classified intent from Step 1:

IntentTemplate
Magazine / Fashion / Editorialprompt-templates/editorial-spread.md
Product / Object / Commercialprompt-templates/product-showcase.md
Dream / Abstract / Surrealprompt-templates/surreal-concept.md
Informational / Defaultprompt-templates/structural-poster.md

Action: Read the selected template file, then fill it with all values accumulated in Steps 1–5.


Output Format

Return the final result wrapped in a single plaintext code block:

~~~markdown 🎨 Aesthetic Copilot: Generated Prompt

Template: [Selected Template Name] Style DNA: [Base Style] + [Material Twist] + [Lighting Modifier] Layout: [Layout ID] — [Layout Name] Concept: [One sentence explaining the Micro-Innovation twist]
[Filled prompt content from the selected template]

~~~


Anti-Patterns

  • Do not use structural-poster for everything — route correctly in Step 6.
  • Do not pick the first item in the Mixer pools — randomize.
  • Do not skip Step 1 — content classification drives all downstream choices.
  • Do not skip Step 5 — layout selection must be passed into the template.
  • Do not use vague style guesses — always read master-collection.md first.

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

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。

平台分布

OpenClaw

77.84%
按下载量换算1,277

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills