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

Beyond the annotations (readOnly, openWorld, idempotent, non-destructive), the description discloses meaningful runtime behavior: internal cascading through multiple lookup endpoints, graceful degradation when GLEIF/OpenFIGI are unavailable, explicit labeling of unresolved identifiers under `unresolved` rather than silent omission, and source attribution for each identifier. It also notes that non-equity instruments without tickers still resolve, setting accurate expectations about coverage.

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 information-dense and front-loaded with examples and the 'Use FIRST' directive, but the company-type section is a long, nested parenthetical with multiple em-dashes and semicolons that is hard to scan. Bullet points or shorter sentences would improve readability without losing content. Every sentence does contribute, but the structural compaction hurts clarity.

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 fully compensates by listing exactly what is returned for each type: CIK, ticker, company_name, LEI with ownership hierarchy, FIGI, and RxCUI with ingredients and citation link. It also covers input variations, unsupported or edge cases, degradation behavior, and the fact that one call replaces several manual lookups. An agent has enough context to call and interpret results 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?

Schema coverage is 100%, so the baseline is 3, but the description adds valuable semantic detail beyond the schema: accepted input forms (ticker, CIK, ISIN, company name; brand or generic drug name), concrete examples (AAPL, CH0038863350, ozempic), and the edge-case instruction to pass only the entity name, not the full noun phrase. It also clarifies that ISIN input maps to the legal entity via GLEIF, which is not obvious from the schema alone.

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 clear verb and resource: 'resolve a user-spoken NAME to the canonical/official identifiers other tools require as input.' It is rich with concrete query examples (ticker, CIK, LEI, RxCUI) and explicitly scopes the tool as the identifier-resolution entry point. The supported types (company, drug) and their outputs are clearly delineated, distinguishing it from sibling tools that work with already-resolved 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?

The instruction 'Use FIRST whenever you have a name but need an ID' provides an explicit when-to-use rule and positions this tool ahead of others in the workflow. It also signals that other tools consume the identifiers resolved here. However, it does not name an alternative tool or state explicit cases where another tool would be preferred (e.g., when you already have an ID and need a profile), so it stops short of full exclusion guidance.

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