openai_list_rate_limits

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

No annotations are provided, so the description must carry the behavioral burden. The verb 'List' implies a read-only operation, and 'per-model rate limit configs' adds scope, but it does not disclose response behavior, pagination semantics beyond parameter names, or access requirements. Output schema may cover return details.

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 concise and front-loaded, with a clear one-line purpose followed by a compact Args list. Every sentence provides necessary information without filler.

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?

With four parameters and an output schema, the description adequately covers the tool's purpose, scope, and pagination parameters. It could explicitly state the read-only nature or typical use cases, but the essential information for correct invocation is present.

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 description includes an Args section explaining all four parameters: project_id is linked to openai_list_projects, after/before are described as pagination cursors, and limit is the maximum entries per page. This fully compensates for the 0% schema description coverage.

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?

Description states 'List per-model rate limit configs for a project' with a specific verb, resource, and scope. This clearly distinguishes it from siblings like openai_update_rate_limit or openai_list_project_api_keys.

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 implies use for listing rate limits but provides no explicit when-to-use guidance or comparisons with alternatives. The only contextual hint is 'see openai_list_projects' for project_id, indicating a prerequisite rather than use-case differentiation.

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