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

The annotations already mark the tool read-only and idempotent, and the description adds substantial behavioral detail beyond that: it cascades through multiple lookup endpoints, degrades gracefully when GLEIF or OpenFIGI is unavailable, returns ambiguous candidates via figi_candidates rather than asserting a match, and explicitly reports unresolved identifiers under unresolved. This gives the agent a clear model of both success and failure behavior.

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 it is structured with clear trigger examples, a stated usage rule, and supported-type sections. Nearly every clause adds useful context, though some details in the parentheticals could be tightened or moved to the schema without loss.

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 carries the responsibility of explaining expected results. It covers return behavior thoroughly: identifiers are labelled with their source, unresolved identifiers appear under unresolved, ambiguous matches return figi_candidates, drug results include RxCUI and brand/ingredient, and enrichment degradation is disclosed. This is sufficient for an agent to know what the tool will do and what it will receive.

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?

The schema already describes both parameters well and even includes formatting caveats for the value parameter, so the baseline is high. The description adds meaningful extras, such as accepting ISIN as an input form and explaining that an ISIN resolves to the legal entity that issued the security, which goes beyond the schema. However, the schema already carries much of the semantic burden, so this is strong but not exceptional.

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 triggers and a specific purpose: resolving a user-spoken name to the canonical/official identifiers other tools require as input. It further differentiates itself by enumerating supported entity types and by positioning itself as a first-step lookup ('Use FIRST whenever you have a name but need an ID') that replaces multiple manual lookups.

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 when-to-use guidance ('Use FIRST whenever you have a name but need an ID') and provides example user queries such as 'what's the ticker for...' and 'find the CIK for...'. It scopes supported types and inputs, but it does not name alternative sibling tools or explicitly state when NOT to use this tool, leaving the comparison to alternatives only implicit.

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