calculate_sample_size

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states the purpose, omitting details like whether the tool is read-only (it's a calculation, presumably safe), what inputs affect the calculation, or how results are returned.

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 very concise (one sentence), but it is under-specified. While brevity is valued, it lacks necessary detail about parameters and output, making it less helpful than it could be.

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?

The tool has three parameters with 0% schema coverage and no output schema. The description fails to explain the function's inputs, outputs, or assumptions, leaving the agent with insufficient information for correct invocation.

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 0%, yet the description provides no explanation of the three parameters (effect_size, confidence_level, power). It does not clarify enum options or numerical ranges, leaving the agent without meaningful semantic guidance beyond the 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 'How many calls needed for statistical validity' clearly indicates the tool calculates required sample size for statistical significance. It uses a specific verb ('calculate') and resource ('sample size'), effectively distinguishing it from sibling tools like 'test_hypothesis' or 'calculate_confidence_distribution'.

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?

No guidance is provided on when to use this tool versus alternatives like 'calculate_confidence_distribution' or prerequisites such as required effect size or confidence level. The description lacks any context for appropriate usage.

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