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

The description adds rich behavioral detail beyond annotations: matching is deterministic and normalised (case/accent/punctuation insensitive), entity names match reliably but person names with transliteration variants may not, an empty result is not a guarantee of clearance, and false positives are possible. It also explains the meaning of 'lists_screened' and 'as_at' output fields. This substantially exceeds the annotations' readOnly/openWorld/idempotent hints.

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 well-structured and front-loaded: purpose, use case, matching behavior, caveats, and output fields. Every sentence contributes substantive information; there is no fluff or repetition. The length is justified by the complexity of the tool's behavior.

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?

Given the tool's complexity (sanctions screening with nuanced matching and result interpretation) and the presence of an output schema, the description covers all critical aspects: which lists are screened, matching details, interpretation of results, and meaning of key output fields. It is complete and self-contained.

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 is 3. The description adds semantics for the 'name' parameter by explaining how matching behaves (normalised exact/alias match, transliteration caveats), which is not in the schema. It also clarifies that 'entity_type' filters person vs entity, consistent with the schema. This adds value beyond the structured field descriptions.

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 clearly states the tool's function: 'Screen a name against the UK (OFSI), US (OFAC), EU and UN consolidated sanctions lists.' It uses a specific verb ('screen') and specific resource (sanctions lists), and is distinct from sibling tools which focus on company/gazette/land data. The title reinforces the purpose.

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 description gives explicit usage context: 'Use it to check whether a counterparty — or its officers / persons with significant control — appears on a sanctions list.' It also provides important caveats about what the tool is not for: 'This is a screening aid, not a compliance determination.' While it doesn't name alternative tools (none exist among siblings), the when-to-use and when-not-to-use guidance is clear.

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