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IBM

Physics MCP Server

by IBM

calculate_terminal_velocity

Calculate terminal velocity by balancing drag and weight forces: input mass, area, fluid density, and drag coefficient to get terminal speed, time to 95%, and drag force.

Instructions

Calculate terminal velocity when drag equals weight.

At terminal velocity, forces balance:
    F_drag = F_weight
    v_terminal = √(2mg / ρC_dA)

Args:
    mass: Object mass in kg
    cross_sectional_area: Area perpendicular to fall direction in m²
    fluid_density: Fluid density in kg/m³ (air=1.225, water=1000)
    drag_coefficient: Drag coefficient (sphere=0.47, skydiver=1.0)
    gravity: Gravitational acceleration in m/s² (default 9.81)

Returns:
    Terminal velocity, time to 95%, and drag force at terminal

Example - Skydiver terminal velocity:
    result = await calculate_terminal_velocity(
        mass=70,  # kg
        cross_sectional_area=0.7,  # m² (belly-down position)
        fluid_density=1.225,  # air
        drag_coefficient=1.0,  # human
    )
    # v_terminal ≈ 54 m/s (120 mph)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
massYes
cross_sectional_areaYes
fluid_densityYes
drag_coefficientNo
gravityNo
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It explains the calculation, returns (terminal velocity, time to 95%, drag force), and includes an example output. This is adequate for a pure calculation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a summary, formula, parameter list, and example. It is somewhat lengthy but front-loaded with the core purpose, and every part adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity and lack of output schema, the description is complete: it covers inputs, formula, return values, and an example. No major gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0%, so the description fully compensates by defining each parameter, providing typical values (e.g., fluid density for air/water, drag coefficients), and listing defaults. This adds significant meaning beyond the input schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates terminal velocity when drag equals weight, with the formula provided. It is specific to terminal velocity, distinguishing it from sibling physics tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context (when drag balances weight) and an example, but does not explicitly state when to use this tool versus alternatives like calculate_drag_force or calculate_projectile_with_drag.

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

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