integrate_trapezoid

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 method but does not describe key behavioral traits such as error handling, numerical precision, performance characteristics (e.g., computational cost with n_steps), or what the output looks like (e.g., numeric result, error estimate). For a tool with no annotations, this is a significant gap in transparency.

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 concise and front-loaded with the core purpose in the first phrase. The additional context ('Domain: calculus, Category: general') is brief and relevant. There is no wasted verbiage, making it efficient, though it could be slightly more structured (e.g., separating usage notes).

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 (numerical integration with 4 parameters), lack of annotations, 0% schema description coverage, and no output schema, the description is incomplete. It does not cover parameter meanings, behavioral details, or output format, leaving significant gaps for an AI agent to understand and invoke the tool correctly. The minimal description is inadequate for the tool's requirements.

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 add any meaning beyond the schema, failing to explain what 'func' represents (e.g., mathematical expression string), the roles of 'a' and 'b' as integration limits, or the purpose of 'n_steps' (e.g., number of trapezoids, default 1000). With 4 parameters and no schema descriptions, the description provides no parameter semantics.

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: 'Calculate definite integral using the trapezoidal rule', specifying the verb ('calculate'), resource ('definite integral'), and method ('trapezoidal rule'). It distinguishes from siblings like 'integrate_midpoint' and 'integrate_simpson' by naming the specific numerical integration method. However, it does not explicitly differentiate from all siblings (e.g., general calculus tools), keeping it from a perfect score.

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 implies usage context with 'Domain: calculus, Category: general', suggesting it's for calculus problems. However, it lacks explicit guidance on when to use this tool versus alternatives like 'integrate_midpoint' or 'integrate_simpson', and does not mention prerequisites or exclusions. The context is implied but not detailed enough for full clarity.

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