get_executive_compensation

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

With no annotations provided, the description carries the full burden. It adds meaningful behavioral details: data source (proxy statements), included fields, conditional availability of CEO-to-median pay ratio, and historical ticker resolution ('FB' resolves to META). It omits error behavior or rate limits, but the core read-only behavior is well disclosed.

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 concise and front-loaded with the purpose, followed by precise argument details. Every sentence adds value; there is no redundant or vague phrasing.

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?

An output schema exists, so return values are covered. The description explains source, fields, identifier formats, and special cases, but the missing year parameter semantics and lack of usage context prevent a perfect score. It remains reasonably complete for a simple lookup tool.

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 0%, so the description must explain parameters. It thoroughly documents ticker, including examples and accepted formats, but completely omits the year parameter. This leaves ambiguity about fiscal year selection and default behavior—a clear gap.

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 retrieves executive compensation (salary, bonus, stock awards, total) from proxy statements, naming specific data fields. This distinguishes it from sibling tools like get_financials or get_company, which cover broader or different financial data.

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?

No guidance is given on when to use this tool versus alternatives. It does not mention exclusions or compare to related finance tools, though it does provide accepted identifier formats. The dimension requires explicit when/when-not/alternative guidance, which is absent.

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