get_endpoint_fields

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

Annotations already declare readOnlyHint=true, and the description adds useful behavioral context: it returns schema-like metadata (field names, types, formats) rather than actual data, and it implies a non-mutating discovery action. No contradictions with annotations.

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?

Two short sentences provide complete information with no fluff. The main action and value are front-loaded, and 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 single-parameter, read-only metadata tool, the description is complete: it explains what the tool returns, when to use it, and why it matters. No output schema exists, but the description adequately conveys the return content. Low complexity means no further behavioral detail is necessary.

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 single parameter 'endpoint' is fully described in the schema with examples, covering 100% of the parameter documentation. The description adds no additional parameter-level detail beyond restating that the endpoint is Treasury-specific, so the schema carries the weight.

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 uses a specific verb ('Get') and resource ('field names, data types, and formats for a specific Treasury Fiscal Data API endpoint'), clearly distinguishing this discovery tool from data-query siblings like query_fiscal_data and list_datasets. The second sentence reinforces its purpose as a pre-query discovery step.

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 explicitly states the usage context: 'before querying data.' It does not name alternative tools or provide exclusion criteria, but the intended workflow is clear enough for an agent to choose this tool over data-fetching alternatives.

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