Icelandic Morphology 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 describes what the tool does (converts words to specified grammatical forms), provides examples of input-output behavior, and outlines the return structure. It doesn't mention error cases, rate limits, or authentication needs, but covers core functionality well given the annotation gap.

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 efficiently structured with a clear purpose statement, explanatory sentence, examples, and well-organized parameter documentation. Every sentence earns its place by providing essential information without redundancy, and it's appropriately front-loaded with the core functionality.

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 complexity of grammatical transformation with three parameters and no output schema, the description does an excellent job explaining inputs and providing return value documentation. It could be more complete by explicitly mentioning error conditions or limitations, but it covers the essential context needed for effective tool 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?

With 0% schema description coverage, the description fully compensates by providing detailed semantic explanations for all three parameters. It defines 'word' with examples, explains 'word_class' with common values and meanings, and thoroughly documents 'target_form' with multiple examples and tag explanations, adding significant value 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 with specific verbs ('Get', 'converts') and resources ('grammatical variant of an Icelandic word'), distinguishing it from siblings like 'get_lemma' (which likely returns base forms) and 'lookup_word' (which likely provides definitions or general information). It provides concrete examples ('convert "hestur" to dative plural') that illustrate its unique functionality.

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 implies when to use this tool through examples and parameter explanations, suggesting it's for grammatical transformation rather than lemma retrieval or general lookup. However, it doesn't explicitly state when NOT to use it or name alternatives like 'get_lemma' or 'lookup_word', which would be needed for a perfect score.

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