get-model-info

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

With no annotations, the description carries full burden. It discloses that the return includes pricing/cost params and limits, but it does not cover side-effect-free behavior, error cases, auth requirements, or rate limits. Minimal transparency beyond the literal return content.

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?

A single front-loaded sentence, no filler, every word earns its place. The key information (what it returns and for what resource) is at the beginning.

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 description is too thin for a tool with 7 parameters and no output schema. It hints at return content but does not explain return structure, possible error states, or how the extra parameters (mode, quality, batch_size, chars_count, video_duration) affect the result. The high parameter count and low schema coverage make the description inadequate.

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 provides zero parameter-level meaning. Schema description coverage is only 29% (2 of 7 params described), and the description does not compensate by explaining how to specify the model or what 'mode', 'quality', etc., affect the result. The required parameters are only implied by the phrase 'specific AI model'.

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 specific verb ('Return detailed information') and resource ('specific AI model'), and the parenthetical '(pricing/cost params, limits)' adds scope. This distinguishes it from siblings like list-models or list-ai-services.

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 phrase 'specific AI model' implies when to use (when you need details of one model rather than listing all), but no explicit alternatives or exclusions are mentioned. The usage context is implied rather than directly stated.

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