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@forgespace/ui-mcp

@forgespace/ui-mcp

Official
by Forge-Space
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

refine_component

Refine existing UI components using natural language feedback for accessibility, dark mode, responsiveness, and framework upgrades.

Instructions

Iteratively improve an existing component based on natural language feedback. Apply accessibility fixes, dark mode, responsive improvements, component library upgrades, and design context alignment. Supports all frameworks.

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": {
      "component_code": "<component_code>",
      "feedback": "<feedback>",
      "framework": "<framework>"
    },
    "name": "refine_component"
  }
}

Input Schema

NameRequiredDescriptionDefault
component_codeYesThe existing component source code to refine
feedbackYesNatural language description of desired improvements (e.g., "make it more responsive", "add dark mode support", "improve accessibility", "use shadcn Button instead of raw button")
frameworkYesFramework of the existing component
dark_modeNoApply dark mode classes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.25.0

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the tool applies fixes and upgrades, and mentions 'Iteratively improve', implying multiple rounds. However, it does not explain the output format, whether changes are saved directly, or any side effects like code overwriting. The behavioral disclosure is adequate but not thorough.

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?

Three sentences, each adding value: first sentence states purpose, second lists capabilities, third asserts framework support. No redundancy, front-loaded purpose. Ideal length for quick understanding.

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 no output schema and no annotations, the description covers the tool's purpose and capabilities well. Missing details: return value description, constraints (e.g., code size limits), and clarification of 'iteratively' (whether multiple calls are needed). Still, it's largely complete for a refinement tool with well-named parameters.

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 baseline is 3. The description adds limited extra meaning beyond the schema: it groups feedback examples and mentions 'supports all frameworks' which aligns with the framework enum. It does not offer deep parameter semantics or usage tips beyond what the schema already provides.

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?

Description clearly states 'Iteratively improve an existing component' using a strong verb and specific resource. It lists concrete improvement types (accessibility, dark mode, responsive, library upgrades) and notes framework support, differentiating from sibling tools like generate_ui_component which create new components.

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?

Description provides examples of when to use (feedback like 'make it more responsive') and states it supports all frameworks. However, it does not explicitly mention when not to use this tool or suggest alternatives like generate_ui_component for creating new components from scratch.

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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