list_datasets

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, covering the safety and mutability profile. The description adds value by specifying the exact return structure (dataset name, data table name, API endpoint path, description) and the quantitative scope (53 datasets, 181 endpoints), which goes beyond what annotations provide.

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 zero redundancy. The primary action and resource are front-loaded, and the second sentence lists the exact return fields. Every word earns its place; no filler or irrelevant information.

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, read-only listing tool with no output schema, the description provides all necessary information: what it lists, the scope, and what it returns. An agent has everything needed to call it correctly, and the annotations cover the safety profile. No gaps exist.

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 input schema is trivially complete (100% coverage). The baseline for 0 parameters is 4, and the description correctly adds no parameter-specific details since none exist. There is nothing for the description to clarify about parameters.

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 a specific verb (list), a specific resource (all 53 U.S. Treasury Fiscal Data API datasets), and the exact output fields (dataset name, table name, endpoint path, description). It clearly distinguishes itself from the many sibling tools by being the Treasury-specific catalog listing tool, leaving no ambiguity about what it does.

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 clearly implies its use case (obtaining an overview of all Treasury datasets and endpoints) but does not explicitly mention when to choose this over alternatives like search_datasets or get_endpoint_fields. It offers no when-not guidance, though the purpose is unambiguous enough that an agent can infer the appropriate context.

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