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

Goes well beyond the readOnly/openWorld annotations by disclosing output shape and limits: dated records plus sources, one question to ask, and explicitly no verdict, score, rating or recommendation. It also names per-kind data limits (FMCSA coverage vs household-goods complaints for auto transport, unavailable USDA license status, BrokerCheck registration blocked by terms), states that missing kind or ambiguous identity returns candidates rather than a guess, and labels unavailable sources.

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 critical trigger sentence is correctly front-loaded, but the body is a dense, run-on enumeration of per-kind data sources that is hard to scan and reads like internal documentation. The information is non-redundant, yet the single-block format obscures the few facts an agent actually needs at call time.

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 9-parameter, multi-source lookup, the description is thorough: it covers coverage limits, US-only scope, the no-verdict stance, and degraded behavior for thin kinds, and an output schema exists so return values need not be re-explained. The one missing piece is explicit sibling disambiguation with check_mover, which is material for correct tool selection.

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 description coverage is 100%, so every identifier (name, city, state, usdot, mc, usda_license, crd, cfpb_company, kind) is already documented in the schema. The description adds only that any of the identifiers can serve as the search key and that an omitted kind triggers conservative resolution, which is real but marginal value on top of a fully documented schema.

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+resource (retrieving public records on a named US business) and enumerates the covered business kinds, so an agent knows exactly what class of question this answers. It does not, however, disambiguate against the sibling check_mover, despite listing movers as a covered kind, leaving a real selection ambiguity.

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?

Trigger conditions are unusually explicit: use when the user names a specific business and asks about legitimacy/licensing, or before signing a quote, paying a deposit, or paying a debt collector. Exclusions are also stated (no reviews, booking, payment, personal-character checks), but neither sibling tool is named as an alternative, so the routing to check_mover vs compare_businesses is left to inference.

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