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

Annotations already declare readOnly/openWorld/idempotent, and the description adds substantial behavioral context: it cascades through multiple lookup endpoints, returns figi_candidates when ambiguity exists, reports unresolved identifiers explicitly, and degrades gracefully when GLEIF/OpenFIGI are unavailable while still returning EDGAR identifiers. This goes well beyond what annotations alone convey.

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 and dense, but the important guidance is front-loaded and organized with 'SUPPORTED TYPES' sections. The opening example list is somewhat redundant, and the parenthetical chains make it heavier than ideal, but nearly every sentence contributes operational value.

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 two required parameters and no output schema, the description is remarkably complete: it covers input formats, supported types, enrichment sources, ambiguity handling, unresolved results, degradation behavior, and even edge cases like non-US issuers. An agent has everything it needs 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?

Even though schema coverage is 100%, the description enriches both parameters significantly. It explains type-specific behavior, gives accepted formats for value (ticker, CIK, ISIN, company name, drug brand/generic), and warns emphatically to pass only the entity name, not the full noun phrase — critical detail absent from the schema.

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 user phrasings and a crisp statement: resolve a user-spoken NAME to the canonical/official identifiers other tools require as input. It enumerates supported entity types (company, drug) and specific identifier outputs, making the tool's job unambiguous and distinct from siblings like entity_profile.

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,' giving a clear trigger condition. It also explains how this tool replaces 2-3 manual lookups, but it does not explicitly name alternative tools or state when not to use it, so the guidance 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.