complex_argument

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 states the calculation and unit (radians) but lacks details on edge cases (e.g., handling of zero or negative real/imaginary parts), error conditions, output format, or performance considerations. For a mathematical tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.

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 of a mathematical function with no annotations and no output schema, the description is incomplete. It doesn't explain the return value (e.g., a number in radians, possibly with range like -π to π), error handling, or how it interacts with sibling tools. For a tool with 2 parameters and no structured support, more context is needed to ensure reliable use.

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 input schema has 0% description coverage, documenting only the parameter names and types (real and imag as numbers). The description doesn't add any parameter-specific information beyond implying they represent the real and imaginary parts of a complex number. Since the schema coverage is low, the description partially compensates by clarifying the overall purpose, but it doesn't detail parameter semantics, constraints, or examples.

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's purpose: '计算复数的幅角（以弧度为单位）' translates to 'Calculate the argument (phase angle) of a complex number in radians.' This specifies the verb (calculate), resource (complex number argument), and unit (radians). However, it doesn't explicitly distinguish this from sibling tools like 'complex_magnitude' or 'complex_polar', which might handle related complex number operations.

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 sibling tools like 'complex_polar' (which might return polar coordinates including the argument) or 'atan2' (which could compute angles in other contexts), nor does it specify prerequisites or exclusions for usage.

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