List models

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the description is not burdened with restating those. It adds useful behavioral context by noting the tool is free and that results include limits and credit pricing, which helps the agent set expectations beyond the raw schema.

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 extremely concise, using one sentence plus a short standalone 'Free.' statement. It front-loads the core purpose and includes only necessary information, with no filler or repetition.

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 simple, zero-parameter, read-only listing tool, the description is complete enough. It names the resource, indicates what kind of data is returned (limits and credit pricing), and states cost behavior. No output schema exists, but the description sufficiently orients an agent.

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 tool has zero parameters, and the schema is empty with 100% coverage, so the baseline of 4 applies. The description adds no parameter detail because none is needed; it instead clarifies the content of the returned model listing.

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 'List' and the resource 'Paxa models', and adds valuable detail about what is included ('limits and credit pricing'). It is readily distinguishable from sibling tools like list_voices because it explicitly names models as the subject.

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?

There is no explicit guidance on when to use this tool versus alternatives, nor any mention of what it is not for. The description implies a simple informational listing, but provides no exclusions or decision criteria relative to sibling tools.

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