math_calculus

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

No annotations are provided, and the description does not disclose behavioral traits such as state mutation, authentication needs, or error handling. As a read-only calculus tool, it likely has no side effects, but this is not explicitly stated.

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, with a one-line summary followed by a bulleted parameter list. Information is front-loaded. It could be more structured (e.g., separating operation list from parameter list) but remains efficient.

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 7 parameters, 1 required, and an output schema, the description covers parameter semantics but lacks explanation of the return value or examples of usage. It is adequate for a straightforward calculus tool but lacks completeness in guiding the agent on output interpretation.

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%, but the description adds meaningful explanations for each parameter with examples (e.g., 'x^2*sin(x)' for expression, 'integrate' for operation). It clarifies the role of each parameter beyond the schema's type 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?

Description clearly states the tool performs calculus operations (integration, differentiation, limits, series expansion, summation, product) with a specific verb and resource. It distinguishes from sibling tools like math_eval or math_solve which handle different mathematical tasks.

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?

Usage is implied through the listed operations, but there is no explicit guidance on when to use this tool versus alternatives (e.g., math_solve for equations, math_eval for expressions). No when-not scenarios or exceptions are mentioned.

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