enaho_comparar

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

Annotations already declare the operation as read-only, idempotent, and non-destructive. The description adds valuable methodological context: it builds a linearized difference over the full survey design, accounting for covariance between domains. This goes beyond the annotations and clarifies the tool's statistical behavior.

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: a purpose-driven question, a clear list of outputs, and usage guidance with reasoning. Every sentence earns its place, and it is front-loaded with the core purpose.

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?

Given the tool's moderate complexity and the presence of an output schema, the description provides adequate context: purpose, outputs, and when to use it. It does not explain prerequisites, but those are captured in the schema and annotations.

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 high (89%), so parameters are well-documented in the schema itself. The description does not add parameter-specific details but aligns with the overall goal of comparing two groups, so the 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 clearly states the tool returns the difference, standard error, confidence interval, t-statistic, and p-value for comparing two groups. It also distinguishes itself from the ad-hoc approach of comparing overlapping confidence intervals, making its specific role clear.

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 explicitly advises using this tool instead of checking overlap of individual confidence intervals and explains why that shortcut fails. It does not reference sibling tools directly, but the when-to-use guidance is strong and specific.

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