DeepL MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the DeepL API but doesn't describe key behaviors like rate limits, authentication needs, error handling, or what the output looks like (e.g., returns rephrased text). This is inadequate for a tool with potential API constraints.

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

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

The description is a single, efficient sentence with zero waste. It's front-loaded with the core action and includes essential context (DeepL API, same language). Every word earns its place.

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

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

Given no annotations and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., rephrased text string), potential limitations, or how to interpret parameters like 'style' and 'tone' in practice. For a 3-parameter tool with API dependencies, this leaves significant gaps.

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

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

Schema description coverage is 100%, so the schema fully documents the three parameters (text, style, tone) with descriptions and enums. The description adds no additional parameter semantics beyond implying rephrasing occurs, which aligns with the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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

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

The description clearly states the verb 'rephrase' and the resource 'text', specifying it uses the DeepL API and maintains the same language. It distinguishes from sibling tools like 'translate-text' (which changes language) but doesn't explicitly differentiate from other potential text manipulation tools.

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

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

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention when rephrasing is appropriate compared to translation or other text processing, nor does it reference sibling tools like 'get-writing-styles-and-tones' that might inform parameter choices.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.