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srafi26

MCP Server

by srafi26

uppercase

Convert text to uppercase for formatting needs. This tool transforms input text into all capital letters.

Instructions

Convert text to uppercase

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesThe text to convert to uppercase

Implementation Reference

  • The handler logic for the 'uppercase' tool. It validates the 'text' input as a string and converts it to uppercase using toUpperCase() method.
    case 'uppercase':
      const text = validateString(args.text, 'text');
      return {
        content: [
          {
            type: 'text',
            text: text.toUpperCase(),
          } as TextContent,
        ],
      };
  • src/index.ts:44-57 (registration)
    Registration of the 'uppercase' tool in the tools array used for ListToolsRequestHandler.
    {
      name: 'uppercase',
      description: 'Convert text to uppercase',
      inputSchema: {
        type: 'object',
        properties: {
          text: {
            type: 'string',
            description: 'The text to convert to uppercase',
          },
        },
        required: ['text'],
      },
    },
  • Input schema for the 'uppercase' tool defining the required 'text' parameter as a string.
    inputSchema: {
      type: 'object',
      properties: {
        text: {
          type: 'string',
          description: 'The text to convert to uppercase',
        },
      },
      required: ['text'],
    },
  • Helper function used in the 'uppercase' handler to validate the input 'text' is a string.
    const validateString = (value: unknown, fieldName: string): string => {
      if (typeof value !== 'string') {
        throw new Error(`${fieldName} must be a string`);
      }
      return value;
    };
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Convert[s] text to uppercase', which implies a transformation but doesn't cover aspects like error handling (e.g., for non-string inputs), performance characteristics, or side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence that directly states the tool's function without any unnecessary words. It is front-loaded and wastes no space, making it easy for an agent to parse quickly. Every part of the sentence earns its place by conveying essential information.

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

Completeness3/5

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

For a simple transformation tool with one parameter and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on output format, error conditions, or behavioral nuances. Without annotations or an output schema, the agent might need to infer or test these aspects, leaving some gaps in 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 has 100% description coverage, with the parameter 'text' fully documented as 'The text to convert to uppercase'. The description adds no additional meaning beyond what the schema provides, such as examples or edge cases. Given the high schema coverage, a baseline score of 3 is appropriate as 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 with a specific verb ('Convert') and resource ('text'), making it immediately understandable. It doesn't explicitly distinguish from sibling tools like 'calculate' or 'echo', but the function is distinct enough that confusion is unlikely. The description avoids tautology by not just restating the name 'uppercase'.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'calculate' or 'echo'. It doesn't mention any specific contexts, prerequisites, or exclusions for usage. The agent must infer usage based solely on the tool's name and description without explicit direction.

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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