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

With no annotations provided, the description carries the burden of disclosing behavioral traits. It mentions the tool is fully deterministic (no LLM), but does not confirm read-only status, authorization needs, or potential side effects. The description lacks transparency expected for a prediction tool.

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, with three short sentences front-loading purpose and key features. The compiler references add specificity without excessive length.

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?

Given three parameters, no coverage, and no annotations, the description is too sparse. It does not explain input requirements (e.g., ticker format), output structure despite an output schema existing, or edge cases. The agent lacks sufficient context to use the tool confidently.

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 description coverage is 0%, yet the description fails to explain any of the three parameters (ticker, agent_token, fiscal_year). It only references internal data sources without clarifying parameter meaning or constraints.

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 predicts Say-on-Pay risk for a company using deterministic compilers. It mentions the return type (trend phrase, peer cohort distribution note, etc.) and distinguishes itself from siblings like benchmark_executive_pay by emphasizing determinism and specific compilers. However, it could be more explicit about the exact output structure.

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 provided on when to use this tool versus alternatives such as benchmark_executive_pay or compare_companies. The description implies a use case for deterministic risk assessment but does not specify prerequisites or exclusions.

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