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

With annotations already declaring readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, the description adds valuable behavioral context beyond them: ambiguous names return no assertion and provide figi_candidates, unresolved identifiers are explicitly listed under `unresolved`, enrichment from GLEIF/OpenFIGI degrades gracefully, and the tool cascades through multiple lookup endpoints. This is exactly the kind of behavior an agent needs to anticipate.

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 actionable detail and organized with clear signposts ('Use FIRST', 'SUPPORTED TYPES', 'LEI/FIGI enrichment'). It front-loads usage examples and priority guidance before edge-case detail. A few sentences are more verbose than strictly necessary, but the length is justified by the complexity of the resolution behavior.

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?

For a tool with no output schema, the description fully compensates by explaining return behavior, including figi_candidates on ambiguity, explicit `unresolved` fields, source-labelled identifiers, graceful degradation when external services are down, and specific return contents for both supported types (e.g., RxCUI, ingredient, brand, citation). It also covers input edge cases thoroughly, so an agent has everything needed to invoke it 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?

Although schema coverage is 100%, the description substantially enriches parameter meaning. For `value`, it explains that the entity name must be passed exactly as printed, warns against including trailing security-class words like 'revenue bonds', and gives concrete accepted formats (ticker, CIK, ISIN, brand/generic name). For `type`, it expands on the enum values with real-world resolution behavior that the schema alone does not convey.

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 ('resolve') and resource ('user-spoken NAME to the canonical/official identifiers'), and it differentiates the tool by explaining that it feeds identifiers to other tools. It also lists concrete query patterns ('ticker', 'CIK', 'LEI', 'RxCUI') and supported entity types, making its purpose unmistakable relative to siblings.

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 explicit usage guidance: 'Use FIRST whenever you have a name but need an ID.' It illustrates the triggering conditions with natural-language examples and explains that it replaces 2-3 manual lookups. It does not explicitly name sibling tools to avoid or state when not to use it, but the 'Use FIRST' instruction provides clear contextual direction.

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