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IBM

Physics MCP Server

by IBM

calculate_kinetic_energy

Compute kinetic energy from mass and velocity components to analyze collisions, vehicle safety, and energy transfer.

Instructions

Calculate kinetic energy from mass and velocity (KE = ½mv²).

Computes the energy of motion for a moving object. Energy is scalar
(direction doesn't matter, only speed). Useful for collision analysis,
vehicle safety, and understanding energy transfer.

Args:
    mass: Mass in kilograms (must be positive)
    velocity_x: X component of velocity in m/s
    velocity_y: Y component of velocity in m/s
    velocity_z: Z component of velocity in m/s

Returns:
    KineticEnergyResponse containing:
        - kinetic_energy: Energy in Joules (J)
        - speed: Velocity magnitude in m/s

Tips for LLMs:
    - 1 Joule = 1 kg⋅m²/s² = energy to lift 102g by 1m on Earth
    - Kinetic energy doubles mass → doubles energy, doubles speed → 4× energy
    - Car at highway speed (~30 m/s, 1500 kg) ≈ 675,000 J
    - Use to compare impact severity or stopping distances

Example:
    # Energy of a 0.145kg baseball at 40 m/s
    result = await calculate_kinetic_energy(
        mass=0.145,
        velocity_x=40.0,
        velocity_y=0.0,
        velocity_z=0.0
    )
    print(f"Kinetic energy: {result.kinetic_energy:.1f} J")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
massYes
velocity_xYes
velocity_yYes
velocity_zYes
Behavior5/5

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

No annotations provided, but the description fully discloses behavior: kinetic energy is scalar, mass must be positive, velocity components in m/s, returns kinetic energy and speed. Comprehensive behavioral context.

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

Conciseness5/5

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

Well-structured with sections: description, args, returns, tips, example. Each section adds value, no fluff. Front-loaded with formula and purpose.

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?

Complete description for a 4-parameter tool with no output schema. Explains formula, units, scalar nature, tips, example, and return values thoroughly.

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 has 0% coverage, but the description explains each parameter (mass in kg, positive; velocity components in m/s) and provides an example and tips, adding significant meaning.

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?

Clearly states 'Calculate kinetic energy from mass and velocity (KE = ½mv²)' with a specific verb and resource. Distinguishes from sibling tools by focusing on kinetic energy.

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

Usage Guidelines4/5

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

Provides context for use (collision analysis, vehicle safety, energy transfer) but does not explicitly state when not to use or differentiate from other energy tools.

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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