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IBM

Physics MCP Server

by IBM

calculate_elastic_collision

Compute final velocities after a 1D elastic collision using conservation of momentum and energy. Input masses and initial velocities to determine post-collision motion.

Instructions

Calculate final velocities after a 1D elastic collision.

Uses conservation of momentum and energy to solve for final velocities.
Assumes perfectly elastic collision (no energy loss).

Args:
    mass1: Mass of first object in kg
    velocity1: Initial velocity of first object in m/s (1D)
    mass2: Mass of second object in kg
    velocity2: Initial velocity of second object in m/s (1D)

Returns:
    Dict containing:
        - final_velocity1: Final velocity of object 1 in m/s
        - final_velocity2: Final velocity of object 2 in m/s
        - initial_kinetic_energy: Total KE before (J)
        - final_kinetic_energy: Total KE after (J) - should equal initial
        - initial_momentum: Total momentum before (kg⋅m/s)
        - final_momentum: Total momentum after (kg⋅m/s) - should equal initial

Example - Pool ball collision:
    result = await calculate_elastic_collision(
        mass1=0.17,      # kg (pool ball)
        velocity1=2.0,   # m/s (moving right)
        mass2=0.17,      # kg (pool ball)
        velocity2=0.0    # m/s (stationary)
    )
    # Result: ball 1 stops, ball 2 moves at 2.0 m/s

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mass1Yes
velocity1Yes
mass2Yes
velocity2Yes
Behavior4/5

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. It effectively describes the tool's behavior: it's a calculation tool (implied non-destructive), specifies the physics model used (conservation laws), states key assumptions (perfectly elastic, 1D), and outlines the return structure with detailed metrics. However, it doesn't mention potential limitations like numerical precision or error handling.

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 and front-loaded with the core purpose, followed by assumptions, parameter details, return values, and a practical example. Every sentence adds value: the first defines the tool, the second explains the method, the third states assumptions, and the rest provide essential implementation details without redundancy.

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 moderate complexity (physics calculation), no annotations, 0% schema coverage, and no output schema, the description is highly complete. It covers purpose, assumptions, parameter semantics, return structure with detailed metrics, and includes a practical example. This compensates fully for the lack of structured data.

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?

The schema description coverage is 0%, so the description must fully compensate. It provides clear semantic meaning for all 4 parameters (mass1, velocity1, mass2, velocity2), including units (kg, m/s), dimensionality (1D), and their roles as initial conditions. The example further clarifies usage with concrete values and context.

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 specific verb ('calculate') and resource ('final velocities after a 1D elastic collision'), distinguishing it from siblings like 'calculate_elastic_collision_3d' (3D version) and 'calculate_inelastic_collision_3d' (inelastic type). It explicitly mentions the underlying physics principles (conservation of momentum and energy) and the key assumption (perfectly elastic).

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 clear context for when to use this tool (1D elastic collisions with no energy loss), but does not explicitly mention when not to use it or name specific alternatives. It implies usage by contrasting with 3D or inelastic scenarios through sibling tool names, but lacks explicit exclusions or named alternatives in the text.

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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