list_all_models

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

Discloses caching of 7 days and the 'raw' nature, which adds behavioral context. However, no annotations exist, and the description could provide more detail on data freshness, completeness, or performance implications.

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?

Extremely concise single sentence that conveys the tool's purpose and a key behavioral trait (caching). No wasted words.

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 listing tool with no parameters and no output schema, the description is adequate but lacks mention of potential pagination, data limits, or whether the list is exhaustive. The caching detail helps but completeness could be improved.

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?

No parameters exist in the schema, so the baseline is 4. The description adds no parameter info, which is acceptable since no parameters require explanation.

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 it lists all models across every brand/category and notes it is raw. This is specific and distinguishes from sibling tools like list_models_grouped, but does not explicitly differentiate.

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 on when to use this tool versus alternatives such as lookup_models or list_models_grouped. No when-not-to-use conditions provided.

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