statistics_summary

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

Since no annotations are provided, this description must fully convey behavior. It lists exactly which statistics are computed (mean, median, population and sample variance/standard deviation, min, max), which discloses the tool's outputs. It does not mention edge cases, but for a pure statistics function the output set is sufficient.

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 two sentences: the first specifies the tool's function and output list, the second gives usage guidance. Every clause is informative and no redundant or vague wording exists.

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?

With a full input schema and an output schema present, the description does not need to detail return values or parameter formats. It covers purpose, usage preference, and output scope, which is complete for a tool of this simplicity in the given context.

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 input schema fully documents both parameters (data and session) with descriptions, so the schema already covers semantics. The description does not add parameter-specific details, but the schema's 100% coverage makes the baseline of 3 appropriate; no additional explanation is needed.

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 begins with 'Descriptive statistics for a list of numbers' which clearly states the tool's function and output scope (mean, median, variances, etc.). It also names an alternative sibling (evaluate_sage) with a preference note, distinguishing it from that general-purpose tool.

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 instructs 'Prefer this over evaluate_sage for summary statistics,' giving a direct usage guideline. It also implies the tool is for numeric list input and provides summary stats, setting clear when-to-use context.

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