list_text_to_speech_generations

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

Annotations already declare read-only, idempotent, open-world, and non-destructive behavior, so the description does not need to repeat safety traits. However, it adds no operational context such as pagination mechanics, ordering, or result shape beyond what 'List' implies.

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 phrase is extremely short and front-loaded, but it is under-specified rather than concisely informative. Like the LOW calibration example, this is minimal wording that omits necessary context instead of earning its brevity.

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?

There is no output schema, so the description should help explain what is returned and how pagination works. Given four optional filter/pagination parameters and no required parameters, the definition is too sparse for an agent to understand result behavior confidently.

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%, so the baseline is 3 even with no parameter details in the description. The description adds no additional meaning for cursor, status, model_id, or page_size beyond the schema.

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 'List Speech Generations' essentially restates the tool name/title without adding scope, filters, or return details. It does not distinguish this listing tool from siblings such as list_image_generations, list_video_generations, or get_text_to_speech_generation.

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?

No guidance is given about when to use this tool versus alternatives like get_text_to_speech_generation or other list_* generation tools. It gives no filtering context beyond the schema, and no exclusions or prerequisites.

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