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

The description goes well beyond the read-only/idempotent annotations by disclosing graceful degradation when GLEIF/OpenFIGI are unavailable, ambiguity handling via 'figi_candidates', explicit reporting of unresolved identifiers, and the fact that one call replaces 2-3 manual lookups. These are non-obvious behaviors an agent needs to trust the result.

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 front-loaded with example queries and the core 'resolve name to ID' instruction, then moves into supported types and degradation behavior. It is dense and long, with some repetition in the example list, but the length is largely justified by the amount of behavioral nuance needed for correct use.

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 the absence of an output schema, the description tells the agent what to expect: source-labelled identifiers, an 'unresolved' field, 'figi_candidates' for ambiguity, and RxCUI/ingredient/brand results for drugs. Along with annotations and full parameter coverage, this is complete enough for correct selection and 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?

Even with 100% schema coverage, the description adds critical parameter semantics: pass only the entity name, for a bond use the issuer exactly as printed and not the full noun phrase, accepted input forms for each entity type, and the ISIN-to-LEI behavior. This is exactly the kind of guidance an agent cannot infer from the schema alone.

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 action: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' The example queries ('What's the ticker for...', 'find the CIK for...') make the purpose immediately recognizable and distinguish it from lookup/profile tools because it is positioned as the name-to-ID gateway.

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?

It gives an explicit trigger: 'Use FIRST whenever you have a name but need an ID.' It also routes by entity type ('company' vs 'drug') and explains what kinds of names it can handle. However, it does not explicitly name alternative tools or state when not to use it, so it falls just short of full alternative/exclusion guidance.

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