bonferroni_correction

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

No annotations are provided, so the description must carry the burden. It correctly labels the tool as conservative. However, it does not disclose other behavioral traits like whether it handles an empty array, returns adjusted p-values, or requires specific input validation beyond the schema.

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 a single, short sentence with no wasted words. It states the action, the purpose, and the trade-off (conservative) in a front-loaded manner.

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 simplicity (2 parameters, no output schema, no nested objects), the description is largely complete for its purpose. It lacks information on return format or error handling, but for a statistical adjustment function, the core use case is well covered. The sibling context helps fill gaps.

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 does not describe the parameters individually, but the parameter names ('p_values', 'alpha') are self-explanatory for a user familiar with the topic. The default value of alpha (0.05) is in the schema. The description adds context about the adjustment purpose but not parameter details, warranting a 4 given the straightforward parameters.

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 it adjusts p-values for multiple comparisons to control family-wise error rate. It specifies the tool's conservative nature and distinguishes it from the Benjamini-Hochberg correction sibling by stating the use case (any false positive is costly).

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 states when to use this tool: 'use when any false positive among the batch is costly'. It also implies when not to use it by contrasting with less conservative methods. The sibling tool name 'benjamini_hochberg_correction' provides a clear alternative.

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