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

Annotations already mark it read-only, open-world, idempotent, and non-destructive. The description goes well beyond by disclosing that identifiers are source-labelled, unresolved identifiers are explicitly listed rather than omitted, ambiguous name matches return figi_candidates and assert nothing, and that the tool cascades through several internal lookups to replace 2–3 manual steps. No contradiction with 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?

Although lengthy, every sentence earns its place. The description is front-loaded with example queries and the core purpose, then systematically covers types, input rules, edge cases, fallback behavior, and internal cascading. It is dense but not repetitive, delivering maximum signal per word.

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?

Given the absence of an output schema, the description fully explains return expectations: labelled identifiers, unresolved list, figi_candidates for ambiguous matches, and graceful degradation when GLEIF/OpenFIGI are down. For a tool handling two entity types with complex lookup chains, this leaves no gap that would prevent an agent from calling it 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?

The schema already covers both parameters at 100% description coverage. The description nonetheless adds critical guidance: for 'value', it explicitly instructs to pass the entity name only, warns against including security-class words for bonds, and gives concrete examples for both company and drug inputs. This goes far beyond the schema and prevents common misuses.

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 immediately gives concrete example queries and states the core purpose: resolve a user-spoken name to the canonical/official identifiers other tools require. It explicitly positions itself as the first step when you have a name but need an ID, sharply distinguishing it from likely siblings like entity_profile which would use an ID after resolution.

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 provides explicit when-to-use guidance ('Use FIRST whenever you have a name but need an ID'), describes the two supported entity types with input format expectations, and includes nuanced instructions like passing the issuer name exactly as printed for bonds and avoiding trailing security-class words. It also clarifies graceful degradation when external services are unavailable.

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