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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose the tool's informational content and implies a read-only schema-introspection purpose. But it does not explicitly state that the tool has no side effects, does not mutate data, or what the response structure looks like beyond listing the data elements. For a zero-parameter metadata tool, this is adequate but not rich.

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 short sentences: the first states exactly what information is returned, and the second gives a crisp usage directive. Every word earns its place, and the key phrase 'Call this first' is prominently placed at the end of the second sentence for actionability. This is an example of efficient, front-loaded writing.

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 zero-parameter, no-output-schema introspection tool, the description is largely complete: it lists all substantive return elements and provides an explicit calling order. The main minor omission is that it does not describe how the returned column info is formatted (e.g., array of objects vs. simple lists), but given the tool's low complexity and simple purpose, this is a small gap rather than a critical one.

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?

The tool has zero parameters, so the baseline is 4 per the rubric. The schema is empty and fully described by its coverage of 100%, and the description correctly avoids inventing parameter details. There is nothing missing in parameter semantics because there are no parameters to document.

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 identifies what the tool exposes: columns, numeric columns, row count, and provenance banner for the Focusvo dataset. It also signals its role as the schema-discovery entry point, which distinguishes it from the sibling tools like dataset_stats or dataset_row. The lack of an explicit verb ('returns', 'lists') is a minor gap, but the noun-phrase style is still specific and unambiguous.

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 gives an explicit usage instruction: 'Call this first to learn the schema.' This establishes a clear workflow context and tells the agent when in the sequence this tool belongs. However, it does not explicitly state when not to use it or mention alternatives among the sibling tools, so it stops short of full exclusion/alternative guidance.

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