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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds substantial behavioral context beyond those: internal cascading through multiple endpoints, graceful degradation when GLEIF/OpenFIGI are unavailable, EDGAR identifiers always returning, support for non-equity instruments, ISIN-to-LEI mapping, and explicit unresolved fields. This is far more than annotations alone 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 long but densely packed with useful examples, supported types, and explicit caveats. It is well-structured with 'SUPPORTED TYPES' and front-loaded with the 'Use FIRST' directive. Some parenthetical segments are heavy, but they carry important disambiguation detail that justifies their length.

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 sufficiently explains what the tool returns: canonical identifiers, RxCUI plus ingredient and brand for drugs, unresolved fields, figi_candidates, and ownership data. It also addresses failure/degradation behavior, which an agent needs to know when interpreting results. For a two-parameter tool, this is complete.

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%, so the baseline is 3, but the description adds critical meaning beyond the schema: it clarifies ISIN as an accepted company input, distinguishes between entity names and full noun phrases for bonds, and gives concrete examples for drug values. The warning about trailing security-class words matching nothing is especially valuable for correct invocation.

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 clearly states the tool's verb and resource: it resolves user-spoken names into canonical identifiers required by other tools. It distinguishes itself by specifying supported types (company, drug) and by framing itself as the first-step lookup tool before other tools, which separates it from siblings like entity_profile or compare_entities.

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 usage instruction: 'Use FIRST whenever you have a name but need an ID.' It also clarifies when it replaces multiple manual lookups and what input forms are accepted. It does not explicitly name sibling alternatives or state when not to use it, but the directive is strong and not misleading.

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