ode_rk4

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so thoroughly. It explains that the endpoint xf is always reached, that tol flags whether the final error meets tolerance, and that the return includes a solution table, exact solution when SymPy can solve it, and per-step errors.

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 well-organized docstring with a one-line purpose statement followed by a compact Args/Returns breakdown. Every sentence adds information about parameters, constraints, or output, with no filler or redundancy.

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 absence of annotations and output schema, the description is remarkably complete. It covers the mathematical problem, all parameter meanings, constraints, the optional tolerance behavior, and the structure of the returned dictionary, including the caveat about SymPy's ability to provide an exact solution.

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. It does: every parameter is explained with meaningful semantics—ecuacion_str gets an example, x0/y0 are defined, xf must be > x0, h must be positive, tol is an optional tolerance flag, and precision is the rounding digits.

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 opens with a specific verb and resource: 'Solve an initial value problem y'(x) = f(x, y) with the Runge-Kutta 4 method.' This clearly states the operation and differentiates it from sibling ODE solvers like ode_euler and ode_heun by naming the specific numerical method.

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 clearly implies when to use the tool: for initial value problems where RK4 accuracy is desired, with constraints like xf > x0 and positive h. It does not explicitly state when not to use it or name alternatives, but the method name and context provide clear usage guidance.

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