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

Beyond the read-only/idempotent annotations, it discloses several important behaviors: ambiguous names return figi_candidates and assert nothing, unresolved identifiers are listed explicitly under unresolved, and LEI/FIGI enrichment degrades gracefully if upstream services fail. It also reveals internal cascade behavior and precise matching semantics (exact ticker map vs name search), which materially changes how an agent interprets results.

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 it is structured and front-loaded with a recognizable user-query preamble and a direct 'Use FIRST' directive. Some parentheticals are heavy, so it is not maximally concise, but few sentences are wasted.

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?

With no output schema, the description carries the burden of explaining what is returned; it does so in detail, including source labeling, unresolved fields, candidate lists, and graceful fallback. It also specifies coverage limitations (non-US issuers, non-equity instruments) and input constraints, so an agent can predict behavior across failure and ambiguity cases.

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 covers both parameters, the description significantly extends their meaning: it lists accepted input forms for company (ticker, CIK, ISIN, or name), explains how ISIN resolves via GLEIF, and warns against trailing security-class words for bond lookups with a concrete example. This is the kind of nuance an agent needs to pass values correctly.

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 concrete action—resolving user-spoken names to canonical/official identifiers—and specifies the entity types (company, drug) and identifier systems involved. It also distinguishes itself from generic entity-related siblings by framing the tool as the name-to-ID mapping step that feeds other tools.

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 explicit trigger conditions ('Use FIRST whenever you have a name but need an ID') and many example phrasings. It does not explicitly name a when-not-to-use alternative such as entity_profile, so the exclusion is only implied by the 'need an ID' condition.

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