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

The description goes well beyond the readOnly/openWorld/idempotent annotations by disclosing graceful degradation ('if GLEIF or OpenFIGI is unavailable, the EDGAR identifiers still return'), ambiguity handling ('returns figi_candidates to pick from'), and the unresolved field ('an identifier that could NOT be resolved is stated explicitly under unresolved rather than omitted'). This gives an agent accurate expectations for edge cases.

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 but dense with useful information, and the first sentence front-loads the core purpose. The company-type section is a single massive parenthetical that is harder to scan, but nearly every sentence earns its place given the tool's complexity.

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 carefully explains return semantics: CIK/ticker/company name, LEI with ownership hierarchy, FIGI, RxCUI with citation, figi_candidates for ambiguous matches, and unresolved identifiers. It also covers input forms, ISIN mapping, non-US issuers, and graceful degradation, leaving little an agent needs to infer.

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 though schema coverage is 100%, the description substantially enriches both parameters. For value, it gives accepted formats (ticker, CIK, ISIN, or name), explicit examples ('AAPL', '0000320193', 'CH0038863350'), a bond-issuer subtlety ('NEW YORK ST DORM AUTH' vs trailing security-class words), and drug examples. For type, it explains what each enum value returns.

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 opens with concrete user phrasings and a specific verb-resource pair: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It clearly distinguishes this name-to-ID lookup role from siblings like entity_profile and compare_entities, and the supported types are enumerated with their identifier outputs.

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 trigger: 'Use FIRST whenever you have a name but need an ID.' It also explains that each call cascades and replaces 2-3 manual lookups, which implies a preferred usage position. However, it does not name specific alternative tools or provide explicit when-not-to-use conditions.

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