dynamic_2d_linear_solve

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

With no annotations provided, the description carries the transparency burden. It explains the mathematical model, parameter roles, and the return value (classification, eigenvalues, nullclines, analytic solution, trajectories). It does not mention potential side effects like plotting or numerical integration method, but the core behavior is disclosed clearly enough for an agent to understand what the tool does.

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 compact and well-structured, starting with a clear purpose statement followed by Args and Returns sections. Every line provides necessary information without redundancy or filler, making it easy for an agent to parse.

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?

The tool has 16 parameters, no output schema, and no annotations, yet the description covers the core aspects: what the tool solves, what parameters mean, and what it returns. It lacks details on the numerical integration method or whether a plot is generated, but the mention of a phase portrait window and returned trajectories gives enough context for a reasonably complete understanding. Given the complexity, this is solid but not exhaustive.

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 define the 16 parameters. It groups them meaningfully: a,b,c,d as entries of A; e,f as forcing vector; x0,y0,t0,t_fin,h as initial condition and integration grid; x_min..y_max as phase portrait window; cantidad_trayectorias as number of sample trajectories. This is helpful, though it could be more precise (e.g., explicitly stating h is the step size). Overall it compensates well for the lack of schema descriptions.

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 explicitly states 'Solve and classify the linear 2D system X' = A·X + B' which clearly identifies the tool's function and distinguishes it from sibling tools like dynamic_2d_nonlinear_solve and dynamic_2d_conservative_solve. The verb 'solve and classify' plus the mathematical form is specific and unambiguous.

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 for linear 2D systems with constant coefficients, but it does not explicitly state when to use this tool instead of alternatives like dynamic_2d_nonlinear_solve or the ODE solver siblings (e.g., ode_rk4). There are no explicit exclusions or alternative recommendations, so guidance is only implied.

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