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

Even with readOnly, openWorld, and idempotent annotations already present, the description discloses significant extra behavior: internal cascading lookups, graceful degradation when GLEIF or OpenFIGI is unavailable, returning figi_candidates instead of asserting on ambiguity, and explicitly labeling unresolved identifiers. This is substantial value beyond the 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 core purpose and usage directive are front-loaded, and much of the detail is necessary for a complex tool. However, the company-type section is a very dense block of parenthetical caveats that could be restructured for easier scanning, so it is very good rather than maximally concise.

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 explaining what identifiers will be returned, how ambiguous names are handled, what appears under unresolved, and what happens when enrichment sources fail. Together with the strong parameter guidance, an agent has enough information to call the tool correctly across the described cases.

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 meaning the schema alone does not convey: accepted input formats (ticker, CIK, ISIN, name), the warning to pass only the entity name and never the full noun phrase, and operational explanations of the type enum. It also gives examples like 'ozempic' that clarify how value should be formatted.

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 names the specific verb 'resolve' and the object ('user-spoken NAME' to 'canonical/official identifiers'), and it opens with concrete example queries that make the purpose instantly recognizable. It also differentiates from siblings by framing the output as inputs other tools require, and it disambiguates from tools like lookup_city or lookup_zipcode by covering entity types rather than geographies.

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 an explicit routing rule: 'Use FIRST whenever you have a name but need an ID.' It also gives substantial context about supported types, input forms, and edge cases like bonds and ambiguous matches. It does not explicitly name alternative sibling tools or state when not to use it, so it falls just short of full exclusion guidance.

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