ttest_independent

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

No annotations are provided, so the description carries the burden. It discloses the key behavioral constraint that exactly 2 groups are required, but does not mention assumptions (e.g., normality), equal variances, missing data handling, or the output structure. This is a useful but incomplete behavioral disclosure.

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 compact and well-structured: it opens with the test name, states the function, provides usage context, highlights the 2-group constraint, and ends with a clear example. Every sentence earns its place without unnecessary 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?

For a statistical test, the description covers the core purpose, usage, and key constraint, plus points to anova_test for more groups. It does not mention assumptions or return values, but an output schema exists, which likely documents the return structure. Given complexity and available structured data, this is reasonably complete.

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%, so the description must compensate. It clarifies that 'column' must be numeric and 'group_column' must have exactly 2 groups, plus provides an example with concrete values. It does not explain 'df_name', but that parameter is optional and likely standard across siblings.

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 an 'Independent two-sample t-test' that 'Compares means of a numeric column across two groups' and determines statistical significance. This is a specific verb+resource and distinguishes from sibling tests like anova_test by explicitly noting the 2-group requirement.

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?

It states 'Use to determine if the difference between two group means is statistically significant' and provides an explicit exclusion: 'Requires exactly 2 groups in group_column. For 3+ groups, use anova_test instead.' This is clear when-to-use and when-not-to-use guidance with an alternative.

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