/install aesthetic-copilot
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)
| File | Role | When to Read |
|---|---|---|
SKILL.md |
This file — entry point | Always |
engine/README.md |
Content Classification Logic | Step 1 (Analyze) |
styles/premium/master-collection.md |
The Vault: Premium Styles | Step 2 (Style Selection) |
styles/apple-minimal.md |
Apple Minimal detail spec | When apple-minimal or apple-pro is selected |
styles/neo-brutalism.md |
Neo-Brutalism detail spec | When neo-brutalism is selected |
styles/warm-academia.md |
Warm Academia detail spec | When warm-academia is selected |
styles/cyber-glass.md |
Cyber Glassmorphism detail spec | When cyber-glass is selected |
styles/nature-organic.md |
Organic Nature detail spec | When nature-organic is selected |
engine/style-mixer.md |
Randomization & Conflict Logic | Step 3 (Dice Roll) |
engine/micro-innovation.md |
Artistic Twists | Step 4 (Innovation) |
layouts/README.md |
Layout Templates | Step 5 (Layout Selection) |
prompt-templates/*.md |
Output Skeletons | Step 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-minimalorapple-pro→ also readstyles/apple-minimal.mdfor detail tokens. - If the matched style is
neo-brutalism→ also readstyles/neo-brutalism.mdfor detail tokens. - If the matched style is
warm-academia→ also readstyles/warm-academia.mdfor detail tokens. - If the matched style is
cyber-glass→ also readstyles/cyber-glass.mdfor detail tokens. - If the matched style is
nature-organic→ also readstyles/nature-organic.mdfor 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 Intent | Layout ID |
|---|---|
| "Top banner + columns", info layout | hero-split |
| "Left menu / sidebar" | sidebar-fixed |
| "Pinterest style", photo wall | masonry-grid |
| "Magazine cover", event poster | poster-zine |
| "Phone app", Instagram feed | mobile-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:
| Intent | Template |
|---|---|
| Magazine / Fashion / Editorial | prompt-templates/editorial-spread.md |
| Product / Object / Commercial | prompt-templates/product-showcase.md |
| Dream / Abstract / Surreal | prompt-templates/surreal-concept.md |
| Informational / Default | prompt-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:
**🎨 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-posterfor 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.mdfirst.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install aesthetic-copilot - 安装完成后,直接呼叫该 Skill 的名称或使用
/aesthetic-copilot触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
aesthetic-copilot 是什么?
Use when the user wants to generate high-fidelity PROMPTS for Text-to-Image models (Flux, Ideogram, Midjourney) based on vague layout/content descriptions. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 160 次。
如何安装 aesthetic-copilot?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install aesthetic-copilot」即可一键安装,无需额外配置。
aesthetic-copilot 是免费的吗?
是的,aesthetic-copilot 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
aesthetic-copilot 支持哪些平台?
aesthetic-copilot 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 aesthetic-copilot?
由 ChenChen(@chenchen913)开发并维护,当前版本 v1.0.0。