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

Annotations already declare readOnly/openWorld/idempotent, but the description goes well beyond them: it lists the returned fields, specifies error codes (400 invalid input, 404 unknown document), and discloses a hard behavioral constraint the agent cannot infer anywhere else — a $0.001 USDC x402 charge per call with the retry convention params._meta["x402/payment"] and an equivalent HTTP endpoint. That is exactly the kind of gating and cost information an agent needs before invoking.

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 a single dense paragraph, but it is front-loaded with purpose before capability, return shape, errors, and payment. Each sentence carries distinct information; the only mild density cost is that pricing and transport details sit in the same block as the functional description.

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?

There is no output schema, yet the description enumerates the returned fields thoroughly enough that the agent knows what to expect, and it covers the two things most likely to break a call: error codes and the payment/retry protocol. For an 8-parameter, zero-required search tool this is complete.

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 50%, and the description restates the meaning of the well-documented parameters (keyword, agency, type, publication date, document number) without adding format detail. It leaves 'limit' and 'order' — including the maximum of 50 and the newest/oldest/relevance options — unaddressed, so it only partially compensates for the coverage gap. A 3 is the appropriate baseline-plus level.

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 names a specific verb and resource ('Federal Register search for US rules, proposed rules, notices and presidential documents') and enumerates the filter axes plus a distinct single-document mode ('or one document by number'). An agent can tell exactly what corpus is being searched and that this tool has no overlapping sibling in the provided list.

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?

It supplies usage context ('useful for regulatory monitoring and compliance research') and internally distinguishes bulk search from single-document retrieval via document_number. It stops short of explicit when-not-to-use guidance or naming an alternative tool, so it falls short of a 5.

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