list_vocabulary

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the tool is clearly safe. The description adds context about the closed vocabulary, which helps explain the tool's purpose but does not detail response behavior or pagination. This is adequate given the strong 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?

The description is compact, front-loads the core purpose, provides a practical usage context, and then documents parameters in a clear block. Every sentence earns its place with no redundancy.

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?

Despite lacking output schema details in the description, the presence of an output schema means return format is not needed. The tool's purpose, usage trigger, and all parameter semantics are fully covered, making it complete for an agent to invoke correctly.

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?

The description explicitly documents each parameter in the Args section: 'starts_with' is defined as a prefix filter and 'limit' as the maximum number of terms returned. Since schema description coverage is 0%, this full compensation is essential and well executed.

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 that the tool lists the visual words the library knows, tying it to Apple's closed vocabulary. It explicitly differentiates itself from search tools by positioning it as the way to discover valid words when a search returns nothing.

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 a specific use case: 'When a search finds nothing, this is how to discover the word it does understand instead.' This implies when to use it relative to search, but it does not enumerate alternative tools or explicit when-not-to-use conditions. Still, the guidance is clear enough for an agent.

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