describe

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

With no annotations and no output schema, the description carries the full burden; it does disclose the exact return set (mean, sample std, quartiles, skew, kurtosis), which is genuinely useful. It says nothing about how the alternative string form of the input is interpreted, how missing values are handled, or what happens with empty/constant samples.

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?

One sentence, no filler, with the statistic list embedded where it is most useful. Nothing could be cut without losing information.

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?

Return values are covered, but for a tool with no annotations, no output schema, and an ambiguous anyOf input, the definition leaves the input contract undefined. An agent could call it with a wrong string form and have no way to know.

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% and the single parameter is an anyOf of number-array or string, so the schema alone leaves real ambiguity. The description never clarifies whether the string is a file path, a column name, or delimited values, so it fails to compensate for the coverage gap.

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?

States a specific verb (Return) and resource (descriptive statistics) and enumerates exactly which statistics are produced, which is more informative than most sibling stats tools like 'distribution' or 'correlation'. It does not, however, differentiate itself from the near-named sibling describe_file, leaving an agent to guess whether this expects raw data or a file.

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 phrase 'for a sample' hints at the intended input, but there is no explicit when-to-use guidance, no prerequisites, and no routing to alternatives such as describe_file, distribution, or analyze_dataset. The agent gets no help choosing this over its several overlapping siblings.

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