qlty_univariateStatistics

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

Annotations already indicate readOnlyHint and idempotentHint. The description adds value by explaining the optional persist parameter that materializes results as a volatile table, which is beyond the annotation scope.

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?

Concise and front-loaded with purpose. Lists arguments clearly, though some repetition with schema exists. Generally efficient.

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?

Covers parameter usage and persist behavior, but lacks explanation of what 'full univariate statistics' includes or the return format. Since no output schema exists, more detail would be beneficial.

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 100%, so the description repeats parameter details without adding new meaning. Baseline of 3 is appropriate as no extra semantic enrichment provided.

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 'Get full univariate statistics for a column in a table', providing a specific verb and resource. It distinguishes itself from sibling tools like qlty_columnSummary or qlty_distinctCategories by indicating comprehensive statistics.

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?

No explicit guidance on when to use this tool over alternatives such as qlty_columnSummary. Lacks when-not-to-use or comparative context.

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