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

Annotations already provide readOnly, openWorld, idempotent, and non-destructive hints. The description adds meaningful behavioral context beyond those hints: a sanctions hit is decisive, failing sources are noted but not fatal, and the read returns a verdict band plus signals, flags, and identifiers. It also clarifies the interpretative limits of absence and match.

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 longer than average but front-loads the purpose and uses each sentence for a distinct job: scope, sources, output, failure behavior, caveats, and positioning. A few phrases like 'premium cross-source synthesis' add limited value, but there is no wasteful repetition.

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?

Despite having no output schema, the description explains exactly what the caller receives: a verdict band, positive signals, flags to review, and resolved identifiers. It also covers source-failure handling and interpretive caveats, so combined with the parameter schema and annotations, the agent has enough context to invoke and interpret the tool 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 description coverage is 100%, so the parameters company, state, and ticker are already documented. The description does not add new parameter-level details beyond connecting the overall tool to its data sources; it stays at the baseline of relying on the schema for parameter semantics.

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 leads with a specific verb and resource: a one-call public-record trust read for a company, explicitly answering 'can I trust this company?' for KYB/vendor-diligence agents. It names the exact data sources joined and the verdict bands returned, making the tool's scope unmistakable and distinct from generic company-info or sanctions tools.

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 intended use case is clearly stated (KYB/vendor-diligence trust questions) and the description adds exclusions: it is not a credit report, background check, or endorsement, and absence of a record is not proof of wrongdoing. It does not name a specific sibling tool as the alternative, but the context and boundaries are clear.

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