ui-registry-mcp

Check design consistency across components

check_consistency

Analyze components from different libraries for design inconsistencies such as mismatched border-radius, hardcoded colors, missing dark-mode variants, and conflicting libraries. Get actionable pointers to normalize your UI before shipping.

Instructions

Given a set of components (from get_component / search results), statically analyze their source for design clashes when mixed together: inconsistent border-radius scales, hardcoded colors vs theme tokens, missing dark-mode variants, and conflicting icon/animation libraries. Returns findings with concrete pointers so you can normalize the UI before shipping. Run this after assembling components from different libraries.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "components": "<components>"
    },
    "name": "check_consistency"
  }
}

Input Schema

Name	Required	Description	Default
`components`	Yes	The components you plan to use together

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jul 10, 2026

TDQS

A4.2/5.0

Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the tool performs static analysis (no side effects), returns concrete findings with pointers, and checks specific design dimensions. It does not discuss auth needs, rate limits, or performance, but the static nature and output type are adequately communicated for a read-only analysis tool.

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?

The description is three sentences with no wasted words. It front-loads the core action, lists specific checks, describes the output, and ends with usage timing. Every sentence is informative and earns its place.

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?

Given the lack of output schema, the description adequately explains that returns are findings with concrete pointers and lists the categories (border-radius, colors, dark-mode, icon/animation libraries). It covers the tool's complexity well, though it could detail the output structure slightly more. The usage context (after assembling from different libraries) adds completeness.

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?

The input schema covers 100% of parameter descriptions, so the baseline is 3. The description adds context about the data source ('from get_component / search results') but does not deepen meaning beyond what the schema already provides (name and registry). It marginally hints at usage context but no new parameter semantics.

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

Purpose5/5

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

The description uses a specific verb-statically analyze design clashes-and clearly identifies the resource (components from get_component/search). It enumerates specific clash types (border-radius scales, hardcoded colors, missing dark-mode, conflicting libraries), which distinguishes it from sibling tools like compare_components (direct comparison) or get_component (single component details).

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?

The description explicitly states when to use the tool: 'Run this after assembling components from different libraries.' This implies the prerequisite actions (gathering components via get_component/search) and the post-assembly timing. It does not provide when-not-to-use scenarios or explicitly name alternatives, but the context is clear.

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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