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IBM

Physics MCP Server

by IBM

calculate_elastic_collision_3d

Calculate final velocities and verify conservation of momentum and kinetic energy in a perfectly elastic 3D collision.

Instructions

Calculate 3D elastic collision (perfect energy conservation).

Special case of collision where no kinetic energy is lost (e = 1.0).
Both momentum and energy are conserved.

Args:
    mass1: Mass of object 1 in kg
    velocity1: Velocity of object 1 [x, y, z] in m/s (or JSON string)
    mass2: Mass of object 2 in kg
    velocity2: Velocity of object 2 [x, y, z] in m/s (or JSON string)

Returns:
    Dict containing:
        - final_velocity1: Final velocity [x, y, z] in m/s
        - final_velocity2: Final velocity [x, y, z] in m/s
        - initial_momentum: Total momentum [x, y, z]
        - final_momentum: Total momentum [x, y, z]
        - initial_kinetic_energy: Total KE in Joules
        - final_kinetic_energy: Total KE in Joules

Tips for LLMs:
    - Ideal approximation for billiard balls, Newton's cradle
    - Both momentum and energy conserved
    - Equal masses + head-on → velocities exchange
    - Use for educational examples, idealized systems

Example - Pool balls:
    result = await calculate_elastic_collision_3d(
        mass1=0.17,  # kg (pool ball)
        velocity1=[2, 0, 0],  # 2 m/s
        mass2=0.17,  # kg
        velocity2=[0, 0, 0]  # stationary
    )
    # Result: ball 1 stops, ball 2 moves at 2 m/s

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mass1Yes
velocity1Yes
mass2Yes
velocity2Yes
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: it conserves both momentum and energy, returns final velocities and verification quantities. The example demonstrates expected behavior (ball 1 stops, ball 2 moves). No hidden side effects or destructive actions.

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?

The description is well-structured with clear sections (Args, Returns, Tips, Example). Every sentence adds value—no fluff. Front-loaded with main purpose, then details. Appropriate length for a physics tool with multiple parameters and a complex output.

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 no output schema, the description fully specifies return values (two velocity arrays, two momentum vectors, two energy values). It includes an example with realistic values and expected outcome, covering all necessary context for an AI agent to understand and use the tool correctly.

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?

All four parameters are explained with units, types, and input formats (list or JSON string). The schema has 0% description coverage, so the description compensates fully, adding meaning beyond bare schema like 'velocity of object 1 [x, y, z] in m/s (or JSON string)'.

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's function with specific verb and resource: 'Calculate 3D elastic collision (perfect energy conservation).' It distinguishes from siblings by explicitly noting it's the elastic version (e=1.0) and hints at 3D specificity, differentiating from potentially 2D siblings like 'calculate_elastic_collision'.

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?

The description provides when-to-use tips (e.g., 'Ideal approximation for billiard balls, Newton's cradle') and key physics behavior (equal masses exchange velocities). It does not explicitly mention when not to use or compare to inelastic version, but the special case note and example imply appropriate contexts.

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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