qlty_columnSummary

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

Annotations already provide readOnlyHint=true and idempotentHint=true, signaling safety. The description adds that the 'persist' materializes a volatile table and returns the table name, which is useful behavioral context beyond what annotations provide.

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, with two lines for purpose and a clear bullet-style list of parameters. It is front-loaded and contains no redundant or extraneous 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?

The description covers the main purpose and the 'persist' behavior. However, it does not specify what 'column summary statistics' include (e.g., count, min, max, nulls, etc.), which would be helpful given the absence of an output schema. Slightly incomplete but acceptable.

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 schema itself documents each parameter. The description repeats the same parameter descriptions verbatim, adding no new meaning. With full coverage, baseline of 3 is appropriate.

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 'Get column summary statistics for all columns in a table.' This verb+resource combination is distinct from sibling tools that focus on individual statistics (e.g., qlty_missingValues, qlty_standardDeviation).

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 versus alternatives. The description only states what it does, leaving usage decisions to the agent's inference. Given the existence of many similar tools, explicit context would help.

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