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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description reveals substantial behavior: each call cascades through multiple lookup endpoints, enrichment degrades gracefully when GLEIF/OpenFIGI are unavailable, and identifiers that cannot be resolved are explicitly returned under `unresolved`. It also explains the `figi_candidates` behavior when a name matches multiple instruments. No contradiction with annotations exists.

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 front-loaded with user-facing example queries before diving into details. Most sentences earn their place by explaining edge cases or disambiguation behavior. Some parenthetical elaborations could be tightened, but the structure is largely purposeful and organized around supported types.

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 is expected to convey return behavior, and it does: it mentions `figi_candidates`, `unresolved`, source-labelled identifiers, and the RxNorm citation URL. It covers graceful degradation and multi-endpoint cascading. Minor gaps remain about the exact response shape for drug lookups and full company results, but the description is strong enough for an agent to invoke the tool 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 the schema already covers both parameters 100%, the description adds important semantics: it defines what value formats are accepted for each type, explains that ISINs resolve to the issuing legal entity, and provides a concrete warning to pass only the entity name (with a bond issuer example). This goes well beyond the schema's baseline 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 states a specific verb-resource pair: resolve a user-spoken name to canonical/official identifiers. It enumerates supported entity types (company, drug) and gives concrete example queries. It also differentiates itself by saying it is the first tool to use when you have a name but need an ID, which distinguishes it from search/lookup siblings.

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 says 'Use FIRST whenever you have a name but need an ID' and gives trigger phrases for when to invoke it. It also explains what input shapes are accepted (ticker, CIK, ISIN, name) and warns against passing full noun phrases. It does not explicitly name alternate tools or state when-not-to-use conditions, 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.