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

The description adds substantial behavioral context beyond the annotations: it explains that lookups cascade through several endpoints, that LEI/FIGI enrichment degrades gracefully when upstream sources are unavailable, that ambiguous matches return figi_candidates rather than asserting an answer, and that unresolved identifiers are listed explicitly. This is precisely the kind of behavioral disclosure annotations do not capture.

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 content is valuable but delivered as one very long, dense paragraph with heavy parentheticals, making it harder to scan. It is front-loaded with trigger phrases and the core directive, but the structure would benefit from bullets or separation between the company and drug cases.

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?

Despite having no output schema, the description tells the agent what results to expect: canonical IDs by source, figi_candidates on ambiguity, unresolved fields, and graceful degradation. It covers input constraints, edge cases, and internal behavior thoroughly enough for correct invocation.

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?

Schema coverage is 100%, so the baseline is 3, but the description goes well beyond the schema. It adds accepted input forms (ticker, CIK, ISIN, name), the crucial instruction to pass the entity name only rather than the full noun phrase, and detailed caveats for bond issuers. This materially reduces the chance of parameter misuse.

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 clearly states a specific verb and resource: resolving a user-spoken name into canonical/official identifiers that other tools require. It differentiates itself from siblings like entity_profile by positioning itself as the first-step lookup tool and enumerating supported types. The trigger-phrase examples make the purpose immediately recognizable.

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 explicit guidance on when to use the tool: "Use FIRST whenever you have a name but need an ID," with concrete query examples for each supported type. It does not explicitly name alternative tools or state when not to use it, so it stops short of full when/when-not coverage.

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