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

With no annotations provided, the description carries the full burden. It discloses the exact content returned (columns, numeric indicators, row count, provenance banner), making the tool's behavior transparent. It does not mention side effects or error conditions, but for a read-only schema overview tool, this is adequate and adds meaningful value beyond the empty schema.

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?

A single, well-structured sentence front-loads the output contents, then immediately gives the usage directive. Every word earns its place; there is no filler or repetition. It is an exemplar of concise, high-density documentation.

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 tool whose purpose is to provide an initial schema overview, the description fully covers what an agent needs: what it returns and when to invoke it. There are no missing prerequisites, constraints, or return-format expectations that would leave an agent uncertain.

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, and the schema description coverage is 100% (empty properties). The baseline for zero-parameter tools is 4, and the description does not need to explain parameters. It adds no redundant parameter information, which 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 states exactly what the tool returns: columns, numeric flags, row count, and provenance banner. It names the resource (Tenantvo dataset) and explicitly frames the tool as a schema-learning entry point. This clearly distinguishes it from siblings like dataset_provenance and dataset_stats, which focus on narrower aspects.

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 phrase 'Call this first to learn the schema' provides explicit when-to-use guidance, placing it as the initial step before other dataset tools. It does not name alternative tools or explicitly state when not to use it, but the directive is unambiguous and contextually sufficient.

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