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

Annotations already declare the safety profile (readOnly, idempotent, non-destructive, closed-world), lowering the bar. The description adds genuine context: it enumerates the covered leak datasets and discloses that results are match scores plus a review status, indicating probabilistic/fuzzy matching rather than definitive hits.

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?

Three tight sentences, front-loaded with what it does, then data coverage, then usage triggers. No filler and every sentence adds information an agent would otherwise have to infer.

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?

An output schema exists, so return-format detail is not required, and the description still notes the shape of results (match scores, review status). Data scope, entity coverage, and trigger conditions are all present for a single-parameter read tool.

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 a single required 'ticker' parameter fully described (with examples) in the schema. The description adds no format or semantics beyond that, so the baseline 3 is appropriate.

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 (Get), a specific resource (ICIJ Offshore Leaks Database matches), and the exact scope (directors and entities of an NZX company). Names the underlying data sources (Panama/Pandora/Paradise Papers, Bahamas Leaks), so an agent can distinguish it from generic graph or beneficial-ownership tools at a glance.

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?

Provides explicit when-to-use triggers (offshore exposure, shell companies, tax haven connections), which is strong guidance. However, it names no alternatives or exclusions, and several siblings (get_kyc_screening, get_beneficial_ownership, get_political_connections, get_hidden_connections) plausibly overlap, so routing between them 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.