statistical_summary

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

With no annotations, the description carries the burden for behavioral context. It clearly indicates a read/compute operation that returns results and mentions default analysis of all numeric columns. However, it does not disclose whether it modifies the input file, needs specific permissions, or how it handles missing values.

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 concise and front-loaded with the purpose, followed by an organized Args list. Every sentence adds needed information without verbosity.

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 moderate-complexity tool with an output schema, the description covers parameters, default behavior, and test options. It does not address when it should be selected over sibling tools, but it provides enough information for invocation.

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%, but the description explains every parameter in detail: dataset_path format, columns default behavior, and accepted tests values. This fully compensates for the schema's lack of descriptions.

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 states a specific operation ('Perform statistical analysis') and lists supported tests, making the purpose clear. However, it does not explicitly distinguish this tool from sibling 'analyze_dataset'.

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?

There is no guidance about when to use this tool versus 'analyze_dataset' or 'clean_data'. The parameters are documented, but the description never states appropriate contexts, prerequisites, or situations where alternatives should be used.

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