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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=false, so the agent knows this is a safe, local, non-networking operation. The description adds the fact that the output is a copyable example, but says nothing about what happens when the model is unsupported or how validation failures surface. Some added value, no contradiction.

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 efficient sentence with the action and artifact front-loaded; nothing is repeated or wasted.

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 two-parameter, read-only generation tool with no output schema, the description plus the rich schema fields cover what an agent needs to invoke it. The only minor gap is that the return shape (a text snippet) is implied by "copyable" rather than stated.

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%, so both parameters, including the endpoint enum values and the model catalog requirement, are already fully documented in the schema. The description's mention of "OpenAI-compatible or native TokenLab endpoints" merely echoes the endpoint enum, adding no format or syntax detail. Baseline 3 applies.

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?

States a specific verb and artifact: "Generate a copyable cURL example" for named endpoint families. An agent immediately knows this produces example code rather than calling an API or comparing models, so it is distinguishable from the siblings (compare_tokenlab_models, open_tokenlab_model_explorer) even though they are not named.

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 statement of when to reach for this tool versus the sibling tools, nor any prerequisite (e.g. model must exist in the live catalog) or exclusion. Usage is only implied by the artifact type.

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