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

Annotations already declare this as read-only, idempotent, non-destructive, and open-world, and the description adds substantial behavioral context beyond those: it explains internal cascading through multiple lookup endpoints, graceful degradation when GLEIF or OpenFIGI are unavailable, explicit reporting of unresolved identifiers, and the figi_candidates behavior when a name matches multiple instruments. This is rich, honest disclosure of edge cases and failure behavior.

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 nearly every sentence adds operational value. It front-loads the core purpose and usage rule before diving into supported types and edge cases. The main drawback is the heavy use of parenthetical asides and long semicolon chains, which reduces scannability, though not enough to undermine its usefulness.

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 tool has no output schema and covers two entity types with multiple identifier sources, the description is remarkably complete. It discloses return-value behavior (source labels, unresolved fields, figi_candidates), failure modes, acceptable input formats, and enrichment fallbacks. There is no obvious missing context an agent would need to invoke this 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 schema coverage is 100%, the description significantly extends the parameter meaning. It explains that value should be the entity name only, gives concrete input examples (ticker, CIK, ISIN, brand/generic drug name), and warns about trailing security-class words in bond names causing lookup failures. This is precisely the kind of practical detail an agent needs beyond the raw 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 names a specific verb and resource ('resolve a user-spoken NAME to canonical/official identifiers') and gives many concrete examples. It clearly conveys that this is a name-to-ID lookup tool, though it does not explicitly name a sibling tool for comparison, so its differentiation from tools like entity_profile is implied rather than stated.

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 instruction 'Use FIRST whenever you have a name but need an ID' provides a clear trigger condition for using this tool. It also distinguishes supported types and explains when enrichment may degrade. However, it does not explicitly say when NOT to use this tool or name alternative tools, so it stops short of full when/when-not guidance.

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