chatgpt_list_modes

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

No annotations are provided, so the description carries the full burden for behavioral disclosure. While 'list' implies a read operation, the description does not explicitly state that it has no side effects, requires no authentication, or does not modify state, which would be helpful.

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?

One concise sentence that efficiently conveys purpose without wordiness, front-loading the action and object.

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 0-param, simple list tool, the description suffices to explain what it returns. However, it doesn't explicitly describe the output format or any prerequisites (e.g., must be on a ChatGPT page), but this is minor.

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, so the schema is inherently complete. The description adds no param semantics needed, and per the rubric, 0 params gives a baseline of 4.

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 lists currently available modes at the top of the new ChatGPT page, with concrete examples ('Chat' and 'Work'). This distinguishes it from sibling list tools like chatgpt_list_models and chatgpt_list_thinking_levels.

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 usage (to see available modes before selection), but provides no explicit when-to-use guidance or comparison with sibling tools like chatgpt_select_mode or chatgpt_capabilities.

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