get_endpoint_fields

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds what the caller will receive — field names, data types, and formats — which is meaningful behavioral context beyond the 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 with no filler. The first sentence front-loads the exact operation and result, and the second justifies the tool's purpose. 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 single-parameter, read-only metadata lookup with full schema coverage, the description is complete. It states the input (endpoint), the output (fields, types, formats), and when to use it, leaving no critical gap an agent would need to call 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?

Schema coverage is 100%, with the endpoint parameter already described and illustrated with concrete examples. The description adds no new parameter semantics, but it does not need to because the schema carries the full burden.

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') with a precise resource ('field names, data types, and formats for a specific Treasury Fiscal Data API endpoint'). It clearly positions this as a metadata-discovery operation, distinguishable from data-querying siblings like query_fiscal_data and list_datasets.

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 states it should be used 'before querying data,' giving clear usage context tied to the query workflow. It does not explicitly name excluded alternatives, but the 'before querying' framing makes the intended timing and purpose clear enough.

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