ask_chatgpt

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what the tool does but doesn't describe important behavioral traits like response format, rate limits, authentication needs, or whether this is a read-only vs. state-changing operation. The description is functional but lacks operational context.

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 perfectly concise with two clear options in a single sentence. Every word earns its place, and the structure is front-loaded with the primary purpose. No wasted words or unnecessary elaboration.

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 tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what kind of response to expect, how ChatGPT will be invoked, or any operational constraints. Given the complexity of interacting with an AI model and the lack of structured output documentation, more context is needed.

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 100%, so the schema already fully documents both parameters. The description mentions 'context entry' which aligns with context_id and 'question' which aligns with the question parameter, but adds no additional semantic meaning beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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's purpose with specific verbs ('ask a question' and 'get a general second opinion') and identifies the target resource ('ChatGPT'). It distinguishes from some siblings like context_* and todo_* tools but doesn't explicitly differentiate from other AI assistants (ask_claude, ask_deepseek, ask_gemini).

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 when to use this tool (to ask ChatGPT about context entries or for general second opinions) but doesn't provide explicit guidance on when to choose ChatGPT over other AI assistants or when not to use it. No alternatives or exclusions are mentioned.

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