starting_words

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 adds relevant context by explaining that the guesses are 'rich in common, distinct letters,' giving insight into the output's nature. However, it does not disclose the return format (e.g., a list of strings), language constraints, or how max_results affects the behavior. It is partially transparent but lacks completeness.

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 tool's purpose. It contains no filler or redundant information, making it appropriately concise and well-structured.

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 tool's simplicity (one parameter, no output schema, no annotations), the description provides a basic understanding of its purpose and the nature of its suggestions. However, it does not specify the return format, the word source, or how it relates to sibling tools, leaving some gaps in context for an agent to invoke it 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 input schema provides only the parameter name 'max_results' with a default of 15 and no description. The tool description does not mention this parameter at all, so it adds no explicit meaning beyond the schema. There is an implied connection between 'strong opening guesses' and limiting results, but the description fails to clarify the exact role of max_results.

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 function: suggesting strong opening guesses. It uses the specific verb 'suggest' and identifies the resource as guesses for starting words. It distinguishes itself from siblings by focusing on 'opening guesses' rather than general word suggestions or validation, though it could be more explicit about the word game context.

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?

There is no explicit guidance on when to use this tool versus the sibling tools suggest_words or validate_word. The description implies it is for opening guesses, but it does not clarify when to choose this over alternatives, nor does it provide any exclusions or prerequisites. The agent is left to infer usage context.

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