dictionary_sounds_like

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It mentions offline CMU dict usage but fails to describe output format, error behavior for missing words, or limitations. This lack of detail leaves the agent uncertain about side effects or edge cases.

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, front-loaded sentence that efficiently conveys the core purpose. However, it could be restructured to include parameter details without losing conciseness. Still, no extraneous information is present.

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 absence of output schema, annotations, and parameter descriptions, the description should provide more context. It does not explain return format, error cases, or usage scenarios, leaving the tool under-specified for agents, especially given the large number of sibling tools.

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 must compensate. It only references the 'input' word parameter but omits the 'limit' parameter entirely, offering no additional meaning beyond the schema. The limit parameter's purpose and behavior remain unexplained.

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 'Find', the resource 'English words that sound similar', and specifies it is for homophones/soundalikes using offline CMU dict. It distinguishes itself from sibling tools like dictionary_rhymes (rhyming) and dictionary_spelled_like (spelling similarity).

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 the tool is for finding homophones but does not explicitly state when to use it versus alternatives such as dictionary_rhymes or dictionary_pronunciation. No exclusions or context are provided to guide selection among many phonetic siblings.

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