numerical_integration

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 mentions the trapezoidal rule, which implies an approximation method with potential error, but does not disclose accuracy limitations, computational complexity, or error handling. The description lacks details on what the tool returns (e.g., a numerical value, error estimate) or any constraints like input validation.

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 purpose without unnecessary words. It is 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 numerical integration with 5 parameters, 0% schema coverage, no annotations, and no output schema, the description is incomplete. It fails to explain parameter semantics, behavioral traits like accuracy or limitations, and what the tool returns, leaving significant gaps for an AI agent to use it correctly.

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 description must compensate for undocumented parameters. It does not explain any of the 5 parameters (function_type, coefficients, lower_bound, upper_bound, intervals), leaving their meanings, formats, and relationships unclear. For example, it does not clarify how 'function_type' and 'coefficients' define the function to integrate.

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: '使用梯形法则计算函数的定积分' (Calculate the definite integral of a function using the trapezoidal rule). It specifies the verb (calculate), resource (definite integral), and method (trapezoidal rule), but does not differentiate from sibling tools like 'numerical_derivative' or 'bisection_method' beyond the mathematical operation.

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 does not mention when numerical integration is preferred over analytical methods, or how it compares to other numerical methods available in the sibling list (e.g., 'newton_method' for root-finding). Usage is implied by the mathematical context 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.