ai-design-expert
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| analyze_requirementC | 解析需求文档(Word/PDF/MD),提取设计要求 |
| extract_tokensC | 从参考设计图提取 Design Tokens(颜色、间距、圆角等)- 支持多图批量处理 |
| generate_designC | 根据需求和 Design Tokens 生成 HTML/Tailwind 设计稿 |
| audit_visualB | 对比生成的代码与参考图,进行视觉审计 - 支持多参考图对比 |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool targets a distinct stage of the design pipeline: requirement analysis, token extraction, design generation, and visual audit. Input types and outputs are clearly differentiated, leaving no ambiguity about which tool to use.
All four tools follow a consistent snake_case verb_noun pattern: analyze_requirement, extract_tokens, generate_design, audit_visual. The naming is predictable and uniform throughout.
Four tools map cleanly onto a coherent design workflow. The count sits well within the 3-15 sweet spot, and each tool has a clear, non-redundant role.
The surface covers the full end-to-end workflow: parse requirements, extract tokens, generate a design, and audit the visual result. A minor gap exists in that there is no explicit tool to refine or fix the design based on audit findings, though an agent could work around this by re-invoking generate_design.