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

With no annotations, the description carries the full burden of disclosing behavior. It clearly indicates that the tool returns descriptive information about inputs, outputs, assumptions, and tables, and implies no calculation or mutation occurs. It stops short of explicitly stating it performs no side effects.

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, focused sentence that conveys all essential information without redundancy. It is front-loaded with what the tool covers and does not waste words.

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 descriptive tool, the description gives a solid overview of content coverage, including inputs, outputs, assumptions, and tables. It does not specify the return format or whether output is text, structured, or human-readable, but this is a minor gap given the tool's simplicity.

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, so the schema already exhaustively covers parameters. The description adds useful context by promising that the tool will explain inputs with units, ranges, and defaults, which is beyond the empty schema.

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 explaining the calculator's inputs, outputs, assumptions, and underlying tables. It distinguishes this from the sibling 'calculate' tool by describing an informational purpose, though it does not explicitly name the sibling it is not.

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 conveys that this tool is for learning about the calculator's behavior, which implies it should be used before or instead of performing a calculation. However, it does not explicitly state when to prefer this over 'calculate' or the enquiry-related sibling tools.

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