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

The description adds a key behavioral detail beyond the annotations: the operation carries a monetary cost (~$0.03). It also clarifies that the response will be concise. It does not contradict the annotations (readOnlyHint false, openWorldHint true, destructiveHint false), though it could mention rate limits or side effects.

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 with no filler; every clause ('ask', model, concise answer, cost) earns its place.

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 tool with an output schema present, the description is complete: it identifies the model, the input type, the response style, and the cost. There is no missing structural information that would prevent correct invocation.

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?

With 100% schema description coverage and a single 'q' parameter already described as 'Your question', the tool description adds little new semantic detail beyond reinforcing that the question can be anything. Baseline 3 is appropriate.

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 uses a specific verb ('Ask') with a clear resource ('OpenAI GPT-5.2') and scope ('any question'), and notes the response format ('concise answer'). The model name differentiates it from sibling ask_* tools, making the purpose unmistakable.

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 provided on when to choose this over sibling tools like ask_ai, ask_gemini, or ask_grok; it only states generic 'any question' usage. Without exclusions or alternative references, an agent must guess based on the model name alone.

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