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

Annotations already convey non-destructive and open-world behavior. The description adds useful context: this is the strongest model and costs ~$0.05 per call, which helps an agent decide if it's worth the cost. It does not contradict annotations.

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 sentence with no fluff: it states the action, model tier, intended tasks, and cost. Every piece of information earns its place.

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 query tool with an output schema and annotations, this description is complete: it tells the agent which model is used, what kinds of questions it handles, and the cost. No additional return-value details are 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?

The single parameter 'q' is fully documented in the schema as 'Hard question' (100% coverage). The description does not add parameter-level details, so baseline 3 is appropriate.

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 identifies the tool as 'Ask the strongest Claude Opus model' and lists specific use cases ('complex analysis, code, reasoning'). This verb+resource phrasing distinguishes it from sibling tools like ask_ai or ai_vision.

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 phrase 'complex analysis, code, reasoning' provides clear guidance on which tasks warrant this tool, and the cost (~$0.05) signals it's a premium option. However, it does not explicitly name alternatives or state when not to use it.

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