openai_list_models

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

Annotations already declare readOnlyHint, idempotentHint and non-destructive, so safety is covered. The description adds the account-scoping detail, which is real context, but says nothing about pagination, ordering, rate limits or what the returned model objects contain.

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 short sentence with the scope qualifier placed at the end where it belongs. No waste, though also no front-loaded cue about authentication or output.

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 read-only listing tool with full annotation coverage and no output schema, the description is nearly adequate, but the one undocumented parameter (api_key, required) is the gap an agent will actually stumble on when invoking it.

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 one required parameter, api_key, with 0% schema description coverage, and the description never mentions it — not that it is required, not the expected format, not whether it can come from an environment default. The description does nothing to compensate for the schema gap.

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 resource ('List all OpenAI models') and scopes it to 'available to the account'. That is enough to distinguish it from sibling model-listing tools (anthropic_list_models, cohere_list_models), though it never names them.

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 gives no indication of when to call this versus alternatives, no prerequisites beyond the implicit account scope, and no exclusions. The agent must infer usage entirely from the name.

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