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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds meaningful behavioral context beyond these: it discloses the fallback from branch BIC to head office and explicitly states that this fallback is surfaced to the user ('and says so'). It also names the data source (official GLEIF mapping), which helps set trust expectations.

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 three sentences, each earning its place: first states the action and output, second gives examples and use cases, third explains the fallback nuance. It is front-loaded with the core purpose and contains no filler.

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 simple single-parameter lookup tool with no output schema, the description is sufficiently complete. It specifies the input format, output fields (LEI, legal name, jurisdiction, status), the data source, and an important edge-case behavior. An agent can confidently invoke this tool and interpret its results.

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?

The input schema already describes the 'bic' parameter with format examples and treatment of 8-character codes, so coverage is 100%. The description adds further semantic value by explaining the purpose of the input ('which legal entity is behind this BIC'), reinforcing the acceptable formats, and describing the fallback behavior that affects how the parameter is interpreted.

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 opens with a specific verb ('Resolve') and resource ('SWIFT/BIC ... to the bank's legal entity: LEI, registered legal name, jurisdiction, and status'), clearly distinguishing this from sibling tools like get_lei (which likely looks up by LEI directly) and isin_to_lei (which uses a different identifier). It also states the exact questions the tool answers.

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 provides clear usage context: it is for resolving BIC-to-LEI in KYC, due diligence, and payment scenarios. It does not explicitly name alternatives or exclusions, but the use case is specific enough that an agent can infer when to prefer this tool over generic entity lookups.

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