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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, and the description does not contradict them. It adds significant behavioral detail beyond annotations: graceful degradation when GLEIF/OpenFIGI is unavailable, explicit unresolved identifiers, returning figi_candidates on ambiguity, source labeling, and internal cascading across lookup endpoints.

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 long, but nearly every sentence carries operational value—usage directives, supported types, ambiguity handling, degradation behavior, and input caveats are all included. It is front-loaded with 'Use FIRST' and the core purpose. Slight verbosity in phrases like 'cross-source identity spine' keeps it from a perfect score.

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 no output schema, the description thoroughly explains return contents: CIK, ticker, company_name, LEI, FIGI, RxCUI, ingredient, brand, citation, source labels, unresolved identifiers, and figi_candidates. It also covers input formats, edge cases like non-US issuers and non-equity instruments, and failure behavior. An agent has everything needed to call 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?

Although schema coverage is 100%, the description adds meaning well beyond the schema: it explains the 'value' parameter must be the entity name only, warns that trailing security-class words like 'revenue bonds' will fail FIGI matching, and gives concrete examples for both company and drug types. This materially improves an agent's ability to 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 verb and resource: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It includes concrete query examples, names the supported entity types, and explicitly positions itself as the first step when an ID is needed, distinguishing it from sibling tools like entity_profile and search_within.

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 context: 'Use FIRST whenever you have a name but need an ID.' It also clarifies scope by saying it 'replaces 2-3 manual lookups' and describes what inputs are accepted. It does not explicitly exclude alternatives like entity_profile or compare_entities, but the 'Use FIRST' directive provides clear routing guidance.

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