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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, safely covering the operation type. The description adds behavioral context beyond annotations by revealing it uses an external API (Datamuse), ranks results by similarity score, and applies a default limit. This is useful information about data source and result behavior that annotations do not provide.

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 three sentences and every sentence adds value: it names the API and relation, explains scoring and limit, states the return format, and gives the use case. It is front-loaded with the core purpose and contains no fluff or repetition of schema fields.

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?

The tool has an output schema, so return structure is already documented. The description explains the result content (candidate word with score) and the default behavior. For a simple lookup tool with strong annotations and schema coverage, this is complete enough for an agent to select and invoke correctly. No critical missing information is evident.

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% for both parameters, with word and limit already described in the schema. The description mentions the default limit for 'limit' but adds no additional semantic meaning beyond what the schema provides. Baseline 3 is appropriate because the schema does the heavy lifting and the description does not compensate further.

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 finds synonyms for an English word, specifies the Datamuse API and rel_syn relation, and explains ranking by similarity score. It distinguishes itself from sibling tools like find_rhymes and find_words by focusing specifically on synonyms. The verb 'find' and resource 'synonyms' are explicit.

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 gives context for when to use it: 'when writing, editing, or paraphrasing English prose.' It does not explicitly mention alternatives or exclusions, but the mention of 'synonyms' and the API relation clearly signal its use case relative to sibling tools. The context is clear, though it lacks an explicit 'use this instead of X' statement.

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