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DeepLcom
by DeepLcom

get-target-languages

Retrieve a list of supported target languages for translation using the DeepL API, enabling accurate selection for multilingual text processing.

Instructions

Get list of available target languages for translation

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The handler function for the 'get-target-languages' tool. It calls the helper getDeeplLanguages with 'target' parameter to fetch available target languages from the DeepL API.
    async function getTargetLanguages() {
      return await getDeeplLanguages('target');
    }
  • Registration of the 'get-target-languages' tool using McpServer.tool(). It has no input schema and points to the getTargetLanguages handler.
    server.tool(
      'get-target-languages',
      'Get list of available target languages for translation',
      getTargetLanguages
    );
  • Shared helper function that retrieves either source or target languages from the DeepL API based on the sourceOrDestination parameter ('target' for this tool). Formats the result using mcpTextContentify.
    async function getDeeplLanguages(sourceOrDestination) {
      const method = sourceOrDestination == 'source' ? 'getSourceLanguages' : 'getTargetLanguages';
    
      try {
        const languages = await deeplClient[method]();
        return mcpTextContentify(languages.map(JSON.stringify));  
    
      } catch (error) {
        return handleError(error);
      }
    }
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 states it 'gets' a list, implying a read-only operation, but doesn't specify whether this requires authentication, has rate limits, returns structured data, or involves any side effects. For a tool with zero annotation coverage, this is insufficient.

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 purpose with no wasted words. It's appropriately sized for a simple lookup tool and is front-loaded with the core functionality.

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?

Given the tool's simplicity (zero parameters, no output schema), the description adequately covers the basic purpose. However, without annotations or output schema, it lacks details on return format, authentication needs, or error handling, which could be relevant for integration. It's minimally viable but has gaps.

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

Parameters4/5

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

The tool has zero parameters, and schema description coverage is 100% (though trivial since there are no parameters). The description doesn't need to compensate for any parameter gaps, and it appropriately doesn't mention parameters. A baseline of 4 is appropriate for a zero-parameter tool.

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 action ('Get list') and resource ('available target languages for translation'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from its sibling 'get-source-languages' beyond the 'target' vs 'source' distinction in their names, which is why it doesn't achieve 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 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 'get-source-languages' or 'translate-text'. It doesn't mention prerequisites, typical use cases, or integration with sibling tools, leaving the agent to infer usage context.

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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