power_for_two_proportion_test

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

Adds meaningful context beyond annotations: p1 and p2 are interchangeable (only difference matters), returns a float in [alpha, 1], and uses a two-proportion z-test. No contradiction with the readOnly/idempotent/non-destructive hints.

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?

Three sentences, front-loaded with purpose, and every sentence carries useful information (purpose, parameter semantics, alternative, return range). No fluff or irrelevant detail.

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 description adequately covers purpose, usage guidance, parameter nuance, and return range. It does not mention statistical assumptions (e.g., normal approximation) or clarify the output schema further, but the presence of an output schema and strong annotations makes this acceptable.

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 schema already provides 100% parameter descriptions, so the baseline is 3. The description adds the insight that p1 and p2 are interchangeable and clarifies that n_per_group is per group, but does not fundamentally extend the schema's meaning.

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 tool computes statistical power for a two-proportion z-test, specifying the resource (two proportions) and the test type. It also distinguishes itself from the sibling sample-size tool by naming sample_size_for_two_proportion_test.

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?

Explicitly tells when to use this tool (detect difference between two proportions) and provides a clear alternative: 'Use sample_size_for_two_proportion_test instead to solve for n given a target power.' Also notes p1/p2 interchangeability, reducing misuse.

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