chatgpt_list_thinking_levels

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

With no annotations provided, the description carries the full burden. It adds meaningful behavioral context by revealing the UI navigation path ('当前档位→高级→思考强度') and noting that only actually available levels are listed, implying account-based filtering. Although it doesn't explicitly declare read-only or state side effects, the verb 'list' strongly implies a safe, non-mutating operation.

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, compact sentence that front-loads the action '列出' and immediately specifies the resource and scope. It includes the helpful page hierarchy without any fluff or repetition, every word contributes meaning.

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 parameterless, no-output-schema list tool, this description is complete. It clearly states what is returned (account-available thinking intensity levels) and provides the UI context. An agent has enough information to invoke the tool and understand the result, even without an output schema.

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 schema is an empty object (100% coverage), so the baseline is 4. The description correctly avoids inventing parameter details and instead focuses on the output behavior, which is appropriate for a parameterless tool.

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 specifies the exact verb '列出' (list) and the resource '思考强度' (thinking intensity), along with the scope '账号实际可用' (actually available for the account). It also clearly distinguishes itself from sibling tools like chatgpt_select_thinking_level by using 'list' rather than 'select', making the purpose unmistakable.

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 that the tool is meant to view available thinking intensity levels before selection, but it does not explicitly state when to use it or mention alternatives. The sibling chatgpt_select_thinking_level is an obvious counterpart, but the usage context is only inferred, not directly expressed.

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