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

With no annotations provided, the description carries the full burden of describing behavior. It discloses the specific output components—columns, numeric indicators, row count, and provenance banner—and positions the tool as a schema-learning step. It does not explicitly state that it is read-only, but this is strongly implied and low-risk for a zero-parameter metadata tool.

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 sentences with no wasted words. The core content is front-loaded, and the actionable guidance 'Call this first' is placed at the end, making the description compact and scannable.

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 schema-discovery tool with no output schema, the description is complete: it lists the key result types and tells the agent the intended invocation order. The sibling tool list provides enough surrounding context that nothing essential is missing.

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, so the schema already fully covers parameter semantics and the description has no parameter burden. The baseline of 4 for a zero-parameter tool is appropriate; no additional parameter explanation is needed.

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 what the tool provides: column names, numeric flags, row count, and the provenance banner, and explicitly frames it as the first call to learn the schema. It does not use an explicit verb like 'returns', and it does not directly contrast itself with siblings such as dataset_provenance, so it stops just short of full differentiation.

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 a clear situational directive: 'Call this first to learn the schema.' This tells the agent when to use the tool, but it does not mention when not to use it or name alternative tools for more specific metadata needs.

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