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madebyaris
by madebyaris

mcp_rakit-ui-ai_designselection

Generate three UI component designs from natural language prompts or compare existing designs, adapting layouts for any CSS framework to help select optimal visual solutions.

Instructions

Compare and select between 3 UI component designs with intelligent layout adaptation. Supports all CSS frameworks (Tailwind, Bootstrap, Bulma, etc.) and automatically chooses the best viewing mode based on component complexity. Perfect for design systems, component libraries, and UI pattern selection. NEW: Can generate designs from natural language prompts using MiniMax-M2.1 API - just provide a prompt and the tool will create 3 distinct designs for you to choose from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesNatural language description of the UI component to generate (e.g., 'Create 3 modern button designs for a SaaS dashboard'). When provided, the tool will use MiniMax-M2.1 to generate designs automatically. If provided, design_name_1/design_html_1 are not required.
style_preferenceYesOptional style guidance for design generation (e.g., 'modern and clean', 'playful and colorful', 'minimalist and professional').
frameworkYesTarget CSS framework for design generation (tailwind, bootstrap, bulma, foundation, semantic ui, or plain css). Defaults to 'tailwind'.
component_typeYesType of component to generate (button, card, form, navigation, modal, table). Helps optimize the prompt for better results.
design_name_1Yes[Optional] Name/title for the first design option. Only required if not using prompt-based generation.
design_html_1Yes[Optional] Complete HTML code for the first design. Only required if not using prompt-based generation.
design_name_2Yes[Optional] Name/title for the second design option
design_html_2Yes[Optional] Complete HTML code for the second design
design_name_3Yes[Optional] Name/title for the third design option
design_html_3Yes[Optional] Complete HTML code for the third design
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'intelligent layout adaptation', 'automatically chooses the best viewing mode', and API integration (MiniMax-M2.1), but fails to describe critical behavioral aspects: what 'compare and select' actually means operationally, whether designs are persisted or temporary, authentication requirements for the API, rate limits, error handling, or what the output looks like. The description provides some context but leaves significant gaps for a tool with 10 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized (4 sentences) but not optimally structured. It front-loads the core functionality but mixes multiple concepts (comparison/selection, layout adaptation, framework support, prompt generation) without clear separation. The 'NEW:' section feels tacked on rather than integrated. Some sentences could be more focused.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (10 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain what 'compare and select' means in practice, what the output format is, how the 'intelligent layout adaptation' works, or what happens after selection. For a tool with this many parameters and no structured output documentation, the description should provide more operational context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 10 parameters thoroughly. The description adds marginal value by mentioning the prompt-based generation feature and CSS framework support, but doesn't provide additional parameter semantics beyond what's in the schema descriptions. The baseline of 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Compare and select between 3 UI component designs with intelligent layout adaptation' and 'generate designs from natural language prompts'. It specifies the verb (compare/select/generate) and resource (UI component designs). However, without sibling tools, it cannot demonstrate differentiation from alternatives, preventing a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage contexts ('Perfect for design systems, component libraries, and UI pattern selection') and mentions the new prompt-based generation feature, but lacks explicit guidance on when to use this tool versus other design tools or alternatives. No when-not-to-use scenarios or prerequisite conditions are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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