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

Annotations (readOnlyHint=true, idempotentHint=true, etc.) already establish safety. The description goes beyond annotations by disclosing internal cascading behavior ('Each call cascades through several lookup endpoints'), the possibility of returning 'figi_candidates' when ambiguous, explicit 'unresolved' fields, and graceful degradation if GLEIF/OpenFIGI are down. These are non-obvious behavioral traits that help an agent predict outcomes.

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 long but information-dense; every sentence adds either usage context, behavior, or examples. It uses clear labels like 'USE FIRST' and 'SUPPORTED TYPES' to structure the abundance of detail. While not terse, the length is justified by the complexity of the tool and the need to disambiguate input formats.

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 that the tool has no output schema, the description compensates by explaining the expected resolution behavior, including identifier sources (SEC EDGAR, GLEIF, OpenFIGI, RxNorm), the meaning of 'figi_candidates', and the 'unresolved' list. It covers the two entity types thoroughly and addresses edge cases like non-equity instruments and ISIN-to-LEI mapping. An agent has enough context to call it 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?

Although the schema already documents both parameters with 100% coverage, the description adds vital usage nuance: for company values it lists accepted forms (ticker, CIK, ISIN, name), and for bonds it warns to pass the issuer name exactly as printed, not the full noun phrase, because trailing security-class words will fail to match. This guidance directly prevents common invocation errors.

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 concrete user phrasings and states a specific verb-resource pair: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It clearly differentiates itself from siblings by positioning itself as the identity-lookup step ('Use FIRST whenever you have a name but need an ID'), which distinguishes it from tools like entity_profile that might focus on retrieving existing profiles.

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 explicitly says 'Use FIRST whenever you have a name but need an ID,' giving a clear when-to-use condition. It also details supported types and input forms, and notes graceful degradation when external sources are unavailable. It does not explicitly name alternative tools or state when not to use it, but the 'FIRST' phrasing implies it is the precursor to other tools.

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