openai_list_service_accounts

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It adds pagination context by explaining 'after' as a cursor from a previous `last_id` and 'limit' as per-page maximum, which is useful. However, it does not disclose potential side effects (though list is read-only), permission requirements, or ordering/filtering behavior, leaving gaps.

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 well-structured: a one-line summary followed by an Args list. Every sentence adds value, and the parameter explanations are tight. It is front-loaded with the core action and avoids unnecessary verbosity.

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?

The tool has an output schema, so return values need not be explained. The description adequately covers the operation and pagination mechanism. However, it omits potential edge cases (e.g., behavior when no service accounts exist) or any mention of required permissions, which is a minor gap for a list operation of moderate complexity.

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 0%, but the Args section fully compensates by explaining each parameter: project_id with a reference to another tool, after with pagination cursor semantics, and limit with 'maximum number per page.' This adds significant meaning beyond the bare schema.

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 uses the specific verb 'List' and identifies the resource as 'service accounts in a project,' which clearly distinguishes it from sibling tools like openai_get_service_account (single) and openai_create_service_account (create). This makes the tool's purpose immediately obvious.

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 a cross-reference for project_id (see openai_list_projects), but it does not explicitly state when to use this tool versus alternatives like openai_get_service_account, nor does it mention any exclusions (e.g., 'for a single account, use get'). Usage is implied by the verb 'List' but not fully articulated.

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