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

Annotations already declare the operation safe, idempotent, and non-destructive, and the description goes well beyond them: it explains graceful degradation when GLEIF/OpenFIGI are unavailable, explicit unresolved identifiers, ambiguity behavior via figi_candidates, source labeling of identifiers, and internal cascading lookups. No contradiction with annotations.

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 front-loaded with examples and the primary use instruction, and almost every sentence carries useful detail. However, it is a long, dense paragraph with deeply nested parentheticals and semicolons; breaking supported types and edge behaviors into bullets would improve scannability without losing information.

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?

With no output schema, the description explains what will be returned or not returned: CIK, ticker, company_name, LEI with ownership data, FIGI, figi_candidates when ambiguous, and unresolved identifiers. It also covers unsupported/edge cases like non-US issuers and non-equity instruments, and the drug path's return values, so an agent has enough context to call and interpret results 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 schema coverage is 100%, the description adds substantial meaning beyond the enum and type definitions: accepted input forms per entity type (ticker, CIK, ISIN, name), examples, the ISIN-to-legal-entity mapping, the exact issuer-as-printed rule, and the behavior for ambiguous bond names. This is more than the schema alone provides.

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 begins with concrete user utterances ('What's the ticker for...', 'find the CIK for...') and states the tool resolves names to canonical identifiers required by other tools. It names specific entity types and identifier systems (CIK, LEI, RxCUI, FIGI), clearly distinguishing its lookup role from sibling tools like entity_profile.

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 guidance: 'Use FIRST whenever you have a name but need an ID.' It also tells callers to pass only the entity name and why trailing security-class words fail. It stops short of naming alternative tools or exclusion conditions when resolution is not appropriate, so it is clear but not exhaustive.

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