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

Annotations already establish read-only, idempotent, open-world behavior, and the description adds rich behavioral detail beyond them: internal cascading through multiple lookup endpoints, graceful degradation when GLEIF/OpenFIGI are unavailable, explicit `unresolved` reporting instead of silent omission, and asserting nothing when a name matches multiple instruments. This is substantial value beyond the structured 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 and the 'Use FIRST' directive, which is excellent. It is also dense and somewhat sprawling, with long nested parentheticals, but nearly every clause adds operational meaning, so it earns a high score despite not being tightly structured.

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?

For a tool with no output schema, the description thoroughly explains what will be returned: CIK, ticker, company_name, LEI with ownership, FIGI with candidates, source labels, unresolved identifiers, RxCUI plus ingredient/brand, and a citation link. It also covers edge cases such as non-equity instruments and ISIN-to-LEI resolution, making agent invocation and result interpretation feasible without additional lookups.

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 critical semantic guidance and format-level pitfalls: pass the entity name only, never the full noun phrase; for bonds use the issuer exactly as printed; accepted input forms include ticker, CIK, ISIN, or company name. This goes well beyond the schema's terse 'ticker, CIK, or name' description.

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 natural-language triggers and a clear verb+resource: resolve a user-spoken name to canonical/official identifiers. It further differentiates itself from sibling tools by stating that it produces the IDs other tools require as input, and it enumerates supported entity types (company, drug) with concrete identifier systems.

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 explicitly instructs the agent to use this tool 'FIRST whenever you have a name but need an ID,' which is a clear usage trigger. It does not explicitly name sibling alternatives or provide when-not-to-use conditions, but the stated purpose and supported types make the selection boundary reasonably clear.

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