profile_column

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

With no annotations, the description carries the transparency burden. It states the core behavior (shows frequent values with counts) and implies a read-only operation. However, it does not disclose edge-case behavior such as handling of nulls, the exact meaning of the 'top' parameter, or any limitations on output size. This is adequate but not comprehensive.

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 concise sentences, front-loaded with the action and followed by a purposeful rationale. Every word earns its place, with no fluff or repetition.

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 tool is simple and has an output schema, so return values are covered. However, the lack of parameter explanations and the omission of usage context around dataset_id/domain leaves gaps. The description is complete enough for a basic understanding but not for confident invocation without further inference.

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%, so the description must explain parameter meaning. It only hints at 'one column' and 'most frequent values' (implying top), but does not explain 'dataset_id', 'domain', or 'top' explicitly. The description fails to compensate for the complete lack of schema descriptions for any parameters.

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 the tool's function: 'Show the most frequent values of one column with counts' — a specific verb, resource, and output. It also distinguishes itself from siblings by focusing on column vocabulary rather than dataset search, schema retrieval, or arbitrary querying.

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 provides a clear use case: 'a quick way to learn a column's vocabulary before writing a where clause.' This implies when to use it relative to querying but does not explicitly name alternatives or exclusions. It gives enough context to know when it is appropriate.

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