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

Beyond the readOnly, openWorld, idempotent, and non-destructive annotations, the description discloses important behaviors: graceful degradation if GLEIF or OpenFIGI is unavailable, ambiguous matches returning figi_candidates, unresolved identifiers surfaced under `unresolved`, and source-labelled identifiers. This is substantial behavioral context that annotations alone would not provide.

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 information-dense and front-loaded with examples and the 'Use FIRST' rule, but it is structured as one long run-on paragraph with some redundancy, such as restating accepted inputs that the schema already documents. Most content earns its place, but readability and concise organization are sacrificed.

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?

There is no output schema, so the description compensates by explaining return behavior: candidate lists when ambiguity exists, explicit unresolved handling, source-labelled identifiers, and drug-specific outputs like RxCUI and brand. It also covers edge cases such as non-US issuers, non-equity instruments, and degraded enrichment. The description is highly complete for a tool of this complexity.

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 already 100%, and the description adds significant parameter-level meaning: concrete examples (AAPL, 0000320193, ozempic), the constraint to pass the entity name only, the warning about trailing security-class words, and ISIN-to-LEI behavior. This goes well beyond the schema's simple property descriptions.

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 explicitly states that the tool resolves user-spoken names to canonical/official identifiers that other tools require, and it enumerates the supported entity types (company and drug) with their identifier sources (EDGAR, GLEIF, OpenFIGI, RxNorm). This clearly differentiates it from siblings like compare_entities and entity_profile by centering on name-to-ID resolution.

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 usage rule: 'Use FIRST whenever you have a name but need an ID.' It also explains that the tool internally cascades through multiple lookup endpoints and replaces 2-3 manual lookups. It does not explicitly name sibling alternatives or state when not to use it, but the usage context is clear.

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