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

The description discloses several behavioral traits beyond what annotations provide: ambiguous names 'assert nothing and return figi_candidates', unresolved identifiers are explicitly listed under `unresolved`, and LEI/FIGI enrichment 'degrades gracefully' when external services are unavailable. It also notes that a call internally cascades through several lookup endpoints, setting expectations about latency. None of this contradicts the readOnly, idempotent, or non-destructive hints.

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 a single dense block mixing examples, acceptance criteria, edge cases, and source details, making it much longer than necessary. While it is front-loaded with the core statement and examples, the enormous parentheticals and nested caveats hurt scannability. A bulleted structure with tighter prose would preserve the information while improving clarity.

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 contents, and it does so thoroughly: it lists the identifiers for company (CIK, ticker, company_name, LEI, FIGI) and drug (RxCUI, ingredient, brand), and explains ambiguous and unresolved cases. It also covers failure modes like graceful degradation and input variants, making the tool callable correctly in nearly all situations.

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 the JSON schema documents both parameters fully, the description adds significant meaning beyond the schema: it enumerates accepted inputs for company ('ticker, CIK, ISIN, or company name') and drug ('brand or generic name'), and includes the critical instruction to pass the entity name exactly as printed rather than the full noun phrase. This warning prevents a common bond-lookup failure and is far more informative than the schema's brief descriptions.

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 trigger phrases and then states the core verb: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It clearly enumerates the two supported types and the exact data sources, making the tool's function unambiguous. It also positions itself as the first step ('Use FIRST whenever you have a name but need an ID'), distinguishing it from sibling lookup/entity tools.

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 positive usage guidance: 'Use FIRST whenever you have a name but need an ID.' It also specifies accepted input formats and warns about passing entity names exactly as printed, which is a concrete precondition for bond lookups. However, it never names sibling tools or states when not to use this tool, so there are no hard exclusions.

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