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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. Description adds behavioral context by explaining it returns words with specific relationships and mentions Datamuse as the data source, which helps the agent understand the tool's behavior beyond annotations.

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?

Two efficient sentences plus examples. Every sentence adds value: first sentence states purpose, second gives examples, third suggests use cases. No fluff, front-loaded with key information.

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 5 optional parameters and multiple search dimensions, the description is complete. It covers all search types with examples, mentions intended use cases, and is adequate for agent to understand when and how to invoke this tool.

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 coverage is 100%, so baseline 3. Description includes examples that map to parameters (meaning, rhymes_with) but does not add additional parameter semantics beyond what the schema already provides. Examples illustrate usage but do not raise score above baseline.

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?

Description clearly states it finds words by meaning, sound, rhyme, or spelling pattern. Examples like 'happy' → pleased and 'algorithm' rhymes → rhythm demonstrate functionality. Differentiates from sibling tools like language.dictionary.define by focusing on related words.

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?

Explicitly says 'great for writing, creative tasks, word games', providing clear usage context. Does not explicitly state when not to use or list alternatives, but context implies it's for word relation queries.

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