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

The annotations already mark it read-only, open-world, and idempotent, and the description adds significant behavioral context: multi-source cascading lookups, graceful degradation when GLEIF or OpenFIGI is unavailable, explicit `unresolved` reporting, and ambiguous matches returning `figi_candidates`. This is much richer than the annotations alone.

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 and dense with many parenthetical asides, but it is front-loaded with usage examples and organized by type. Every sentence conveys functional information, so the length is mostly justified by the tool's complexity.

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 compensates by naming the returned identifiers (CIK, ticker, LEI, FIGI, RxCUI), the `unresolved` field, `figi_candidates` behavior, and source labeling. It also covers edge cases such as non-equity instruments, ISIN-to-LEI mapping, and partial enrichment failures, so an agent has nearly everything needed to select and invoke it.

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 fully, the description adds essential semantics: accepted input forms for company and drug, the ISIN-to-LEI behavior, and a precise warning to pass only the legal entity name as printed rather than the full noun phrase. This materially helps an agent call the tool correctly.

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-spoken queries and states a clear verb-resource pair: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It also enumerates supported entity types and the exact identifiers returned, making it easy to distinguish from sibling tools that are not name-to-ID resolvers.

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?

It explicitly instructs 'Use FIRST whenever you have a name but need an ID,' and gives context that it replaces 2-3 manual lookups. It does not explicitly name an alternative tool or state when not to use it, but the supported types and accepted input forms provide strong situational guidance.

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