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

Beyond the readOnlyHint/idempotentHint annotations, the description richly discloses behavior: graceful degradation if GLEIF/OpenFIGI is unavailable, the figi_candidates behavior when a name matches multiple instruments, explicit unresolved identifiers rather than omission, acceptance of ticker/CIK/ISIN/name inputs, and internal cascading lookups. These details are substantive and align with 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 description is long but front-loaded with the key directive and example queries before diving into details. Every sentence adds useful information, such as edge cases, degredation behavior, and return semantics. It is not as tight as a two-sentence summary, but the density justifies most of the length.

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 full burden of explaining return behavior. It does so thoroughly: for drugs it lists RxCUI, ingredient, brand, and citation; for companies it covers figi_candidates, unresolved identifiers, and graceful fallback. Given the tool's complexity, the description leaves no critical operational question unanswered.

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?

The input schema already has 100% coverage with descriptions for both parameters, but the tool description adds substantial value: it explains the meaning of supported types (company vs drug), gives examples for the value parameter, warns against passing full noun phrases for bonds, and clarifies input forms like ISIN. This goes well beyond the schema's baseline.

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 verb and resource: resolve a user-spoken name to canonical/official identifiers required by other tools. It includes example queries that make the purpose unmistakable. However, it does not explicitly name sibling alternatives or differentiate itself from tools like entity_profile or compare_entities, so it stops short of full sibling differentiation.

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 when-to-use guidance: "Use FIRST whenever you have a name but need an ID," and provides concrete example phrasings. It does not, however, state when not to use the tool or name alternative tools for other situations, so it lacks the full when-not/alternatives coverage.

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