Levelang 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 effectively explains the unique behavior of producing translations at learner proficiency levels (beginner, intermediate, etc.) rather than native-speaker complexity. It also mentions that returns include 'metadata about the translation,' which adds useful context beyond basic translation output.

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 well-structured and appropriately sized. It starts with the core purpose, explains the unique value proposition, then provides clear parameter documentation in a structured format. Every sentence adds value with no wasted words, and the information is front-loaded effectively.

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 the tool's complexity (6 parameters, unique proficiency-based translation behavior) and the presence of an output schema (which handles return value documentation), the description provides complete context. It explains the tool's unique behavior, documents all parameters thoroughly, references related tools, and mentions the output includes metadata - covering all necessary aspects for effective use.

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 0%, so the description must fully compensate. It provides excellent parameter semantics: explaining what each parameter does, giving examples (e.g., 'fra, deu, cmn'), clarifying defaults ('eng for English'), and explaining constraints ('any length, any source language'). The description adds substantial meaning beyond the bare schema.

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 tool's purpose: 'Translate text to a target language at a specific proficiency level.' It distinguishes itself from standard translators by explaining it produces translations at the learner's level with varying complexity based on proficiency. This specificity helps differentiate it from generic translation 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?

The description provides clear context for when to use this tool (for learner-level translations) and references the sibling tool 'list_languages' to discover available language codes and modes. However, it doesn't explicitly state when NOT to use this tool or how it differs from 'translate_compare' (the other sibling tool mentioned).

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