complex_divide

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. The description only states the calculation purpose without mentioning critical behaviors: it doesn't warn about division by zero (when b_real and b_imag are both zero), describe error handling, specify output format (e.g., real and imaginary parts), or note mathematical constraints. This is inadequate for a mutation-like operation (division) with zero annotation coverage.

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, efficient sentence in Chinese ('计算两个复数的商') that directly states the purpose without unnecessary words. It's appropriately sized and front-loaded, with zero waste—every word earns its place by conveying the core functionality.

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 complexity (mathematical operation with 4 parameters), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It lacks behavioral details (e.g., error cases like division by zero), parameter explanations, output information, and usage guidelines. For a tool performing division on complex numbers, this minimal description is insufficient to ensure correct agent 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?

Schema description coverage is 0%, so the schema provides no parameter documentation. The description adds minimal value by implying parameters represent two complex numbers (a and b), but doesn't explain that 'a_real', 'a_imag', 'b_real', and 'b_imag' correspond to real and imaginary components, their units, or valid ranges. It fails to compensate for the coverage gap, leaving parameters largely undocumented.

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 '计算两个复数的商' (calculates the quotient of two complex numbers) clearly states the verb (calculates) and resource (two complex numbers). It distinguishes from sibling tools like 'complex_add' or 'complex_multiply' by specifying division. However, it doesn't explicitly mention the mathematical operation name 'division' beyond '商' (quotient), which is slightly less specific than ideal.

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 (e.g., avoiding division by zero), compare to sibling tools like 'divide' (for real numbers) or 'complex_multiply', or specify contexts where complex division is appropriate. Usage is implied by the purpose but not explicitly stated.

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