chatgpt_select_mode

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

With no annotations, the description is responsible for behavioral disclosure. It does reveal that the tool verifies the selected state after selecting, which is an extra behavioral detail. Nevertheless, it omits side effects, error handling, or permission requirements, leaving some ambiguity for a state-changing 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, front-loaded sentence that efficiently conveys action, resource, examples, and verification behavior without any 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?

For a simple one-parameter selection tool, the description covers what it does, how to verify, and gives examples. It lacks explicit return value or failure behavior details, but given the tool's simplicity and schema coverage, it is nearly complete.

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 schema already describes the mode parameter and recommends listing modes first, and the tool description adds concrete examples ('聊天' or '工作'), enriching the meaning beyond the schema. With 100% schema coverage and added examples, the parameter is well defined.

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 selects a mode from the ChatGPT page top (e.g., 'Chat' or 'Work') and verifies the selection. It distinguishes from sibling tools like chatgpt_list_modes (listing) and chatgpt_select_model (model selection) by specifying the resource as 'mode'.

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 schema description advises calling chatgpt_list_modes first, giving clear context on the proper sequence. However, it does not explicitly state when to avoid this tool or compare it to other selection tools like chatgpt_select_model, so it misses full exclusion guidance.

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