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

Annotations already cover the safety profile (readOnlyHint=true, openWorldHint=false), so the description's job is to add context, and it does: it discloses the three payload components (parameters, pricing, example request) that an agent will receive. With no output schema, this return-content disclosure is the main behavioral value and it is concrete, though it says nothing about payload size or whether the example request is model-specific vs. generic.

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 short sentences with no filler: the first declares the return content, the second declares the call ordering and the reason for it. The most actionable information (call before create_generation) is placed where it will be read.

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 tool with no output schema, the description covers purpose, return content, and workflow position, and the schema covers the id source. An agent has everything needed to call it correctly and to know why it should.

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?

There is a single required parameter and schema coverage is 100%, with the schema itself directing the agent to list_models for the id. The description adds no additional meaning about the model identifier, so this is the baseline case where the schema does all the work.

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 resource (one model) and enumerates exactly what is returned: full parameter list, price table, and an example request. That content list distinguishes it from list_models, which only enumerates models, though the description never names that sibling explicitly.

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 an explicit sequencing rule — call this before create_generation because parameters differ between models — which is exactly the decision an agent needs. It stops short of stating when the call can be skipped (e.g., already-known parameters), so it is not a full when/when-not pair.

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