get_companies_with_anticompetitive_losses

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. While it mentions filtering criteria ('excluding zero or N/A values'), it lacks details on data sources, update frequency, potential limitations (e.g., date ranges, completeness), or what the output schema contains. For a tool with no annotations, this leaves significant gaps in understanding its behavior and reliability.

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 efficiently conveys the tool's purpose and key filtering rule ('excluding zero or N/A values'). It is front-loaded with the main action and avoids any redundant or verbose language, making it highly concise and effective.

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 that the tool has no parameters, 100% schema coverage, and an output schema exists, the description doesn't need to cover parameters or return values. However, with no annotations and a potentially complex data source (anti-competitive litigation losses), the description could benefit from more context on data scope or limitations to fully inform usage, leaving it adequate but with room for improvement.

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%, so no parameter documentation is needed. The description appropriately focuses on the tool's function without unnecessary parameter details, earning a baseline score of 4 for effectively handling a parameterless tool.

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') and target ('all listed companies that have reported monetary losses from anti-competitive litigation'), making the purpose explicit. However, it doesn't distinguish this tool from its sibling 'get_company_anticompetitive_litigation', which appears to be a related but different tool for company-specific data rather than aggregated company lists.

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 some usage context by specifying 'excluding zero or N/A values,' which indicates when data points are filtered out. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_company_anticompetitive_litigation' or other company-filtering tools, leaving the choice somewhat implied rather than clearly guided.

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