get_companies_cumulative_voting

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a read operation ('Get companies'), implying it's non-destructive, but doesn't specify any behavioral traits such as data freshness, rate limits, authentication requirements, or potential side effects. For a tool with zero annotation coverage, this lack of additional context is a significant gap, leaving the agent uncertain about operational constraints.

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 a single, well-structured sentence that front-loads the key action ('Get companies') and specifies the criteria concisely. Every word earns its place by defining the scope without redundancy or fluff, making it highly efficient and easy for an agent to parse.

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 the tool's complexity (simple read operation with 0 parameters), schema coverage is 100%, and an output schema exists, the description is minimally adequate. It states what the tool does but lacks context on behavioral aspects, usage guidelines, or output interpretation. With no annotations and reliance on the output schema for return values, the description meets basic needs but leaves gaps in operational understanding.

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 tool has 0 parameters, and schema description coverage is 100%, meaning the input schema fully documents the absence of parameters. The description doesn't need to add parameter semantics, as there are none to explain. A baseline score of 4 is appropriate because the description efficiently states the tool's purpose without unnecessary parameter details, aligning with the schema's completeness.

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 action ('Get companies') and specifies the criteria ('that use cumulative voting, full roll-call voting, or nominee nomination systems for electing directors and supervisors'). It distinguishes itself from sibling tools by focusing on specific corporate governance voting systems, unlike other tools that cover different aspects like financial data, trading info, or other governance features. However, it doesn't explicitly contrast with the most similar sibling 'get_companies_with_independent_directors', which is also governance-related but targets a different criterion.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for application, or compare with sibling tools that might overlap in governance queries (e.g., 'get_companies_with_independent_directors'). The agent must infer usage based solely on the purpose statement, which is insufficient for optimal tool selection.

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