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

Annotations already mark readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds meaningful behavior beyond that: internal cascading lookups, graceful degradation when GLEIF/OpenFIGI are unavailable, ambiguous FIGI results returned as 'figi_candidates' rather than asserted, and unresolved identifiers explicitly listed under 'unresolved' rather than omitted. This is rich, non-obvious behavioral context.

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 dense and somewhat run-on, especially inside the 'company' parenthetical, but it is front-loaded with purpose and usage, then structured by supported types. Every major point earns its place given the tool's complexity; a small structural cleanup would make it a 5.

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 convey what the agent can expect. It covers supported input types, output identifiers (CIK, LEI, FIGI, RxCUI, ingredient, brand), fallback behavior, ambiguity handling, and cross-source coverage. For a resolver of this complexity, the contextual picture is complete enough for correct invocation.

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 substantially exceeds that baseline. It explains the 'type' enum with detailed output expectations per type, and enriches 'value' with per-type examples and a critical constraint: pass the entity name exactly as printed and never the full noun phrase (e.g., 'NEW YORK ST DORM AUTH' not 'revenue bonds'). This prevents a real failure mode.

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 names a specific verb ('resolve') and resource (user-spoken names to canonical identifiers), and enumerates supported entity types ('company', 'drug') and concrete identifier outputs (CIK, LEI, FIGI, RxCUI). It distinguishes itself from other tools by stating it supplies the IDs that 'other tools require as input', and the detailed examples ('ticker for…', 'CIK for…') make the 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 explicit direction: 'Use FIRST whenever you have a name but need an ID.' This is strong when-to-use guidance. It does not explicitly name sibling alternatives or say when not to use it, but the condition is clear enough that an agent can route appropriately without confusion.

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