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

With no annotations, the description carries the burden of disclosing behavioral traits. It does disclose what information is returned (columns, numeric indicators, row count, provenance banner), which implies a read-only schema inspection. However, it never explicitly states that the tool has no side effects or what happens if the dataset is unavailable, leaving some ambiguity.

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 no filler. The output contents are front-loaded in the first sentence, and the crucial usage instruction ('Call this first') is in the second. Every word earns its place.

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 simple zero-parameter schema-introspection tool, the description is complete: it names the dataset, lists the returned information categories, and gives clear first-step guidance. With no output schema, it covers the essential return values well enough for an agent to invoke it correctly.

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 is empty, so there is no parameter semantics to document. The baseline for zero-parameter tools is 4, and the description appropriately focuses on what the call returns rather than inventing parameter details.

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 the resource ('the Amortlane dataset') and the specific outputs: columns, which are numeric, row count, and provenance banner. It lacks an explicit verb like 'retrieves' but is unambiguous and not tautological. It does not directly contrast with sibling tools, though the 'learn the schema' framing sets it apart.

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 instruction 'Call this first to learn the schema' gives explicit when-to-use guidance and establishes this as the entry point before other dataset tools. It does not name alternatives or state when not to use it, but for a zero-parameter introspective tool this is clear and useful context.

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