list_models

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

The description indicates a safe read operation with 'Return' and clarifies the scope as 'chat models exposed on the site'. However, with no annotations, it does not disclose potential edge cases, update frequency, or error behavior, and the parenthetical '(DeepSeek FR)' adds ambiguity rather than clarity.

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 that efficiently states the action and resource. The parenthetical note is minor and does not detract from the density of useful information.

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 zero-parameter list tool, the description adequately covers the purpose and scope. While it lacks details on the return structure or whether the list is cached or real-time, this is not critical for a straightforward listing operation.

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 input schema is empty. Baseline for no parameters is 4, and the description adds no parameter-related information, which is appropriate since none exist.

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 tool returns the canonical list of chat models with capability notes. It uses a specific verb ('Return') and resource ('canonical list of chat models'), and distinguishes itself from sibling tools (get_pricing, get_official_links) by focusing on model listings.

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?

The description provides no guidance on when to use this tool versus alternatives. It is purely declarative, with no mention of use cases, prerequisites, or exclusions.

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