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

Annotations already declare readOnly/idempotent/non-destructive and closed-world, yet the description adds substantial context: the two source registries and their year ranges, domain-based identity so name changes unify, matching normalization rules, no merging of multiple candidates, and the contents of each match. It also states the critical caveat that registration is self-reported and California-only, so a non-match is not a negative finding — behavior an agent cannot infer from 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?

Purpose and sources are front-loaded, and nearly every clause carries operative information. It is, however, a long, heavily comma-joined paragraph; the enumeration of returned fields could be tightened without losing meaning.

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?

With no output schema, the description takes on the burden of describing returns and does so (filings, collection categories, sale/share recipients, governing laws, consumer-request counts, name history, broker page). Any parameter is optional, both are documented, and the non-match interpretation caveat is present — nothing material is missing for correct invocation or interpretation.

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%, so baseline would be 3, but the description goes well beyond field definitions: it explains that matching is by registrable domain or by normalised legal name/DBA/prior name, that case, punctuation and legal suffixes are ignored, and that matching is exact after normalization. That tells an agent how to shape inputs and what recall to expect, which the schema does not.

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?

States a specific verb+resource (checks whether a business is registered as a data broker) plus the exact source (MORVS California Data Broker Register) and the coverage window. An agent can distinguish it from the sibling data_broker_diff, which presumably compares registries rather than checking a single business.

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?

Gives explicit input options ('Give a business name, a website domain or URL, or both') and an explicit exclusion ('Businesses only; queries shaped like a personal name are not run'). It stops short of naming the sibling data_broker_diff as the alternative for comparison work, so routing between the two is only implied by scope.

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