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

Annotations already declare readOnly=true, openWorld=true, idempotent=true, destructive=false, so the safety profile is covered. The description goes well beyond that by disclosing multi-source cascading lookups, ambiguity handling through figi_candidates, explicit unresolved fields, ISIN-to-LEI mapping, and graceful degradation when GLEIF/OpenFIGI are unavailable. This is substantive behavioral context, not a repeat of 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 example queries, the 'Use FIRST' directive, and a clear SUPPORTED TYPES structure. However, it is quite long and some clauses are redundant or editorial, such as the extended bond-issuer explanation and the closing 'replaces 2-3 manual lookups' remark. It earns its density mostly, but not every sentence is strictly necessary.

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 behavior, and it does: named identifiers per type, source attribution, unresolved handling, ambiguity candidates, and failure modes. Both company and drug resolution paths are covered with examples. An agent can predict what it will receive and how to interpret edge 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?

Schema coverage is 100%, but the description still adds value beyond it by broadening accepted company inputs to include ISIN, which the schema's value description omits. It also explains semantic nuances like resolving non-equity instruments and why an ambiguous issuer name should return figi_candidates. The schema's 'entity name only' warning plus the description's identifier-source semantics together make parameter meaning unusually clear.

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 example queries and states the verb-resource pair clearly: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' Supported types ('company', 'drug') and the product of resolution (CIK, LEI, FIGI, RxCUI, etc.) make the tool unmistakable. It also implies differentiation from sibling tools like entity_profile or search_within by framing itself as the identifier-producing precursor.

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 gives an explicit trigger condition: 'Use FIRST whenever you have a name but need an ID.' This is strong guidance and explains why the tool exists relative to downstream tools. It does not explicitly name sibling tools or say when not to use it, so it falls just short of a 5.

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