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

The annotations already establish read-only, idempotent, open-world behavior, and the description goes well beyond them by disclosing internal cascading lookups, graceful degradation when GLEIF/OpenFIGI are unavailable, the fact that unresolved identifiers are explicitly listed under `unresolved`, and the `figi_candidates` behavior for ambiguous matches. This gives an agent an accurate model of what happens under failure and ambiguity. There is no contradiction with the 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?

The description is dense and front-loaded with purpose before diving into type-specific behavior, and nearly every sentence adds operational detail. However, it is a single long paragraph without bullet structuring, which makes the rich guidance harder to parse than necessary. Minor structural formatting would improve scannability without losing content.

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 only two parameters, no output schema, and read-only annotations, the description is remarkably complete. It explains accepted inputs, output components (identifiers, source labels, `unresolved`, `figi_candidates`), failure modes, edge cases for non-equity instruments, and integration with external sources. An agent has enough context to invoke the tool correctly and interpret its response.

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 describes both parameters and covers 100% of them, the description adds significant meaning: it details what `value` should be for a bond issuer versus a full noun phrase, explains the distinction between implied ticker mapping and name search, and specifies accepted input forms (ticker, CIK, ISIN, or name for company; brand/generic for drug). This materially helps the agent construct correct calls.

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 purpose: resolve a user-spoken name to canonical/official identifiers needed by other tools. It clearly enumerates supported entity types (company, drug) and the kinds of identifiers returned (CIK, LEI, FIGI, RxCUI), and the opening examples make the intent unmistakable. It also distinguishes itself by saying to use it FIRST when a name needs to become an ID, which sets it apart from siblings like entity_profile or compare_entities.

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 an explicit trigger condition: "Use FIRST whenever you have a name but need an ID." It also clarifies the relationship to other tools by saying these identifiers are what other tools require as input. However, it does not name any alternative tool for when this tool is NOT appropriate, so it falls short of the full when/when-not/alternatives guidance.

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