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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive hints. The description adds substantial behavioral context beyond these hints: it cascades through multiple lookup endpoints, degrades gracefully when LEI/FIGI enrichment is unavailable, returns unresolved identifiers explicitly, and returns figi_candidates when a match is ambiguous. This is rich, useful transparency that helps an agent understand side effects and failure modes.

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 well-structured, front-loading user intents and the 'Use FIRST' directive, then elaborating on types and edge cases. Every sentence adds operational value, though the density is high enough that it could benefit from more explicit section breaks. It is appropriately sized for a tool with this 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?

There is no output schema, so the description must carry the burden of explaining return behavior. It does so impressively: identifiers are labelled with sources, unresolved identifiers are explicit, ambiguous matches return figi_candidates, and drug results include RxCUI, ingredient, brand, and a citation. An agent has enough context to call the tool correctly and interpret its result.

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 100%, but the description adds significant meaning beyond the schema. It explains the exact form of the value parameter ('Pass the ENTITY NAME ONLY'), gives concrete examples (AAPL, 0000320193, 'NEW YORK ST DORM AUTH'), and warns against trailing security-class words. It also clarifies what each type accepts (ticker/CIK/ISIN/name for company; brand/generic for drug).

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 verb and resource: resolving user-spoken names to canonical/official identifiers, with explicit supported types ('company', 'drug') and examples like 'ticker for', 'CIK for', 'RX CUI'. It clearly differentiates itself from siblings by emphasizing its role as the identity-resolution step that feeds IDs to 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?

The description gives an explicit trigger: 'Use FIRST whenever you have a name but need an ID.' It also clarifies acceptable inputs for each type and provides formatting caveats (e.g., pass the issuer name only, not the full noun phrase). It does not, however, name alternative sibling tools or state when NOT to use this tool, so it falls short of a full 5.

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