list_datasets

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

Annotations already provide readOnlyHint=true, so the description does not need to reiterate read-only behavior. The description adds factual details (53 datasets, 181 endpoints) but no additional behavioral traits beyond what annotations indicate.

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 consists of two concise sentences with no wasted words. It front-loads the key information about what the tool lists and what it returns.

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?

Given the tool has no parameters and no output schema, the description provides complete context: it lists all datasets and endpoints, and specifies the four fields in the return value. This is sufficient for an agent to understand the tool's functionality.

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 coverage is 100% (empty schema). According to guidelines, baseline is 4 for no parameters. The description does not need to add parameter meaning.

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 the tool lists all 53 U.S. Treasury Fiscal Data API datasets and their 181 endpoints, specifying the verb 'list' and the resource 'datasets and endpoints'. It distinguishes from sibling tools like 'query_fiscal_data' which query specific data.

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?

While the description clearly indicates the tool is for discovering available datasets and endpoints, it does not explicitly mention when not to use it or suggest alternatives such as 'search_datasets' for searching across datasets. This is a minor gap.

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