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

Annotations already signal safe read-only behavior, and the description adds meaningful scope: only public models, reviewed official prompting sources, exact/current data, and explicit exclusions. This does not contradict the readOnlyHint and adds context beyond the 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?

Two sentences, both informative: the first front-loads the intended use and data categories, the second lists exclusions. There is no filler, repetition, or unnecessary detail.

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?

For a one-parameter read-only lookup, the description covers what data to expect, the constraint that the model must be public and known, and what not to use it for. The schema supplies the ID provenance, and sibling list/recommend tools are evident from context.

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% for the single id parameter, and the schema already states it is an exact public MaxVideoAI model ID returned by list_models or recommend_models. The description adds no further syntax, format, or meaning beyond what the schema provides.

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 names the exact resource ('one known public MaxVideoAI model') and the kind of data returned (capabilities, constraints, evidence, reviewed official prompting sources, links). It also distinguishes this from list/recommend siblings by requiring a known single model and explicitly excluding hidden models.

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?

It gives a clear when-to-use trigger ('when the user needs exact current capabilities...') and an explicit 'Do not use' list (pricing, generation, hidden models, provider guarantees). It does not name alternative tools to route to, though the schema's reference to list_models/recommend_models partially compensates.

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