get_company_quarterly_audit_variance

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

No annotations are provided, so the description carries full burden. It indicates a read operation ('obtain') but lacks details on permissions, rate limits, data freshness, or output format. While it hints at variance calculation, behavioral traits like error handling or response structure are omitted, making it insufficient for a tool with output schema.

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, dense sentence that efficiently conveys the tool's purpose, resource, filtering logic, and parameter use without redundancy. It is front-loaded with the core action and appropriately sized, with every word contributing to understanding.

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 output schema exists, the description needn't explain return values. However, with no annotations and a single parameter, it adequately covers the basic purpose and parameter semantics but lacks behavioral context and usage guidelines, leaving gaps in overall completeness for effective tool invocation.

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?

With 0% schema description coverage for the single parameter 'code', the description adds crucial meaning by specifying it as a 'stock code' for a 'listed company', clarifying its purpose beyond the generic schema. This compensates well for the lack of schema documentation, though it doesn't detail format 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 action ('obtain quarterly comprehensive income audited/reviewed figures') and resource ('for a listed company'), specifying the filtering condition ('differ from forecast by more than 10%') and identifier ('based on its stock code'). It distinguishes from siblings by focusing on audit variance rather than other financial or governance data, though it doesn't explicitly name alternatives.

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 explicit guidance on when to use this tool versus alternatives is provided. The description implies usage for variance analysis but doesn't mention prerequisites, exclusions, or compare with other tools like get_company_quarterly_earnings_forecast_achievement, leaving the agent to infer context from the tool name alone.

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