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

The description adds substantial behavior beyond the read-only/idempotent annotations: it discloses ambiguity handling via figi_candidates, explicit unresolved identifier reporting, graceful degradation when GLEIF/OpenFIGI are unavailable, internal cascading lookups, and cross-source identity resolution. No contradiction with the annotations exists.

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 nearly every clause earns its place given the tool's complexity and the breadth of entity types and fallbacks. It is front-loaded with usage intent and the 'USE FIRST' directive; the main weakness is run-on parenthetical structure that could be organized more cleanly.

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 compensates by enumerating the key returns: CIK, ticker, company name, LEI, ownership, FIGI, unresolved identifiers, RxCUI, ingredient, brand, and citation. It also covers input variants, edge cases, and failure behavior, making the tool self-sufficient for an agent to select and invoke 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?

Even though the schema already documents both parameters well, the description adds meaningful semantic detail: it introduces ISIN as an accepted company input beyond the schema's ticker/CIK/name list, explains what each type resolves to, and clarifies that the value must be the entity name only, not the full noun phrase. This goes well beyond the baseline for high schema coverage.

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 natural-language queries and states the core action: resolve a user-spoken NAME to canonical/official identifiers other tools require as input. It names the two supported entity types and clarifies its role relative to downstream tools, making the tool's purpose unmistakable.

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 illustrates many invocation scenarios. It does not explicitly say when not to use it or name sibling tools like entity_profile as alternatives, so it stops short of a full when/when-not contrast.

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