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

With no annotations, the description carries the disclosure burden; it does convey that this is a read-only schema-discovery operation and lists the returned information categories. However, it does not explicitly state that no parameters are needed or describe how the listed items are represented, so some behavioral context is left implicit.

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, with the concrete outputs leading and the actionable call-instruction ('Call this first') immediately after. No filler or repetition of the tool name.

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 parameterless introspection tool with no output schema, the description covers what information will be revealed and when to invoke it. The only minor gap is that 'provenance banner' is a domain-specific term that is named but not explained, and the exact return shape is not described.

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 takes zero parameters and the schema description coverage is effectively complete, so there is little for the description to add. The baseline for a parameterless tool is 4, and the description naturally needs no parameter-specific detail.

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 enumerates the tool's exact outputs: columns, numeric-field indicators, row count, and provenance banner, and frames it as the first schema-introspection step. This clearly distinguishes it from siblings like dataset_compare or dataset_search, which operate on data rather than describe structure.

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?

It explicitly instructs the agent to call this first to learn the schema, giving a clear when-to-use signal. It does not name alternatives or state when not to use it, so it stops short of a full routing rule.

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