Calculate an agent evaluation sample size

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds meaningful behavioral context by explaining the dual outputs and warning against misinterpreting zero failures as proof of zero risk. This goes beyond what annotations alone communicate.

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 three sentences with no filler. It front-loads the core purpose, gives usage context, and adds a valuable statistical caution. Every sentence contributes to correct tool selection and invocation.

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?

With a rich output schema, complete input schema, and strong annotations, the description provides all necessary context: what the tool computes, when to reach for it, and a critical interpretation warning. Nothing material is missing for an agent to invoke it correctly.

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 fully documents all five parameters. The description mentions 'margin' and 'failure rate' conceptually and explains why the parameters matter, but it does not add formatting, units, or relationship details beyond the schema. 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 states a specific action ('Calculate two different samples') and identifies exactly what is calculated: sample size to detect at least one failure and sample size to estimate its rate. It clearly distinguishes this from the surrounding retrieval tools by focusing on statistical calculation for evaluation sample sizing.

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 gives explicit guidance: 'Use this when a user asks how many tests are enough.' It also includes a non-obvious interpretive caution about zero observed failures. However, it does not name alternative tools or explicitly state when not to use it, so it stops short of full exclusion guidance.

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