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

The description goes well beyond the annotations by disclosing graceful degradation of LEI/FIGI enrichment, the internal multi-endpoint cascade, the handling of ambiguous matches via `figi_candidates`, and the explicit `unresolved` field. It also explains source labeling and ISIN-to-legal-entity mapping, giving an agent a rich behavioral model without contradicting the readOnly/openWorld/idempotent 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 dense and long, but it is logically structured: user utterances, core purpose, usage rule, supported types, then edge-case behavior. It front-loads the most important guidance ("Use FIRST whenever...") and organizes caveats in a readable way, though some parenthetical examples could be trimmed without losing meaning.

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 carries the burden of explaining return semantics, and it does cover key outputs: CIK, ticker, company_name, LEI, FIGI, RxCUI, unresolved identifiers, and `figi_candidates`. It could be slightly more explicit about the overall output shape, but for a complex resolution tool it provides enough operational and edge-case context for an agent 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 schema coverage is 100%, the description adds substantial meaning to the `value` parameter, including the crucial rule to pass only the entity name, the exact formatting for bond issuers, and a concrete caveat about trailing security-class words. It also enriches the `type` enum with real-world examples and cross-source behavior, so it clearly adds value beyond the schema.

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 clearly states the tool resolves user-spoken names into canonical identifiers, with a specific verb-resource pair and the input/output direction. It also distinguishes the tool from siblings by framing it as the provider of IDs that other tools require, and by detailing the two supported entity types. The opening examples make the intended use immediately recognizable.

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 says "Use FIRST whenever you have a name but need an ID," which is strong when-to-use guidance. It also clarifies supported entity types and input forms, but does not explicitly name alternative tools or state when not to use this tool beyond that implied rule, so it earns a 4 rather than a 5.

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