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

Beyond the annotations, the description discloses that the answers are returned word for word and that two published answers give different drying times, both being returned. This is valuable behavioral context for a read-only FAQ lookup, warning the agent that results may contain unreconciled conflicting information.

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?

Two concise sentences front-load the tool's scope and then add the key behavioral caveat about conflicting drying times. There is no unnecessary wording.

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 zero-parameter FAQ lookup with an output schema, the description is complete enough: it identifies the information returned and explains the important verbatim behavior. The output schema can carry return-value details.

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 takes zero parameters, so there is no parameter meaning for the description to add. The baseline for a parameterless tool is appropriately met.

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 resource and scope: it returns how long washing and drying take and when the store is quietest, specifically as FAQ answers. It distinguishes this from live machine data by framing the output as published FAQ content, though it does not explicitly name sibling tools.

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?

Usage is implied by the mention of FAQ answers for duration and quietest times, but there is no explicit guidance on when to use this versus get_location_hours or get_machines. No exclusions or alternative-selection rules are provided.

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