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design_recommend

Read-only

Recommend a complete design system (palette, style, font pairing, page sections, key UX rules, anti-patterns) for a project. Works for ANY page type. Best results: first get a SNAPSHOT from the user and pass what you observed as keywords.

Input Schema

NameRequiredDescriptionDefault
industryNoe.g. skincare, dev tools, real estate
keywordsNostyle/brand cues, e.g. 'minimal, trust, dark, bold' — include what you saw in a snapshot
page_typeNolanding | ecommerce_pdp | dashboard | blog | portfolio | pricing | about | contact
project_typeNoe.g. SaaS, e-commerce, agency, portfolio, fintech, healthcare

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=true, so the safety profile is covered. The description adds the 'works for any page type' scope and a usage hint, but does not explain the non-idempotent behavior (idempotentHint=false) or what the returned recommendation looks like. Moderate added value over annotations.

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

Conciseness5/5

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

Two tight sentences, front-loaded with the core purpose and output list, followed by the practical usage hint. No filler or redundancy.

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

Completeness4/5

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

For a read-only, all-optional-parameter tool with no output schema, the description adequately conveys what the tool produces by enumerating the design system components. It could say more about the return structure, but the enumerated outputs largely cover that need.

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 four optional parameters with examples. The description only adds a hint about populating 'keywords' from a snapshot, which is marginal over the schema's own example ('minimal, trust, dark, bold — include what you saw in a snapshot'). Baseline 3 applies.

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 uses a specific verb ('Recommend') plus resource ('complete design system') and enumerates the concrete outputs (palette, style, font pairing, sections, UX rules, anti-patterns), which clearly separates it from the sibling design_search. It stops short of explicitly naming a sibling alternative, so it falls just below a 5.

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

Usage Guidelines4/5

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

It gives clear operating context ('Works for ANY page type') and a concrete recommended workflow ('first get a SNAPSHOT from the user and pass what you observed as keywords'). It does not state when NOT to use it or name an alternative tool, so it lacks exclusions.

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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