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Physics MCP Server

by IBM

check_energy_conservation

Verify whether total mechanical energy is conserved or dissipated in a physics process. Helps validate simulation results and analyze energy transfer with tolerance-based checks.

Instructions

Verify conservation of energy in a physics process.

Checks whether total mechanical energy is conserved (or correctly dissipated).
Useful for validating simulation results and understanding energy transfer.

Args:
    initial_kinetic_energy: Initial KE in Joules
    final_kinetic_energy: Final KE in Joules
    initial_potential_energy: Initial PE in Joules
    final_potential_energy: Final PE in Joules
    expected_energy_loss: Expected energy loss (from friction, etc.) in Joules
    tolerance: Tolerance for conservation check (fraction, default 0.01 = 1%)

Returns:
    Dict containing:
        - initial_total_energy: Initial total energy in Joules
        - final_total_energy: Final total energy in Joules
        - energy_difference: Energy difference in Joules
        - energy_difference_percent: % difference
        - is_conserved: Whether energy is conserved within tolerance
        - expected_loss: Expected energy loss in Joules
        - actual_loss: Actual energy loss in Joules

Tips for LLMs:
    - In isolated systems, total energy is conserved
    - With friction/damping, expect energy loss
    - Small numerical errors are normal in simulations
    - Use to validate simulation accuracy

Example - Bouncing ball with energy loss:
    result = await check_energy_conservation(
        initial_kinetic_energy=0,
        final_kinetic_energy=0,
        initial_potential_energy=10,  # J (at 1m height)
        final_potential_energy=6.4,  # J (bounced to 0.64m)
        expected_energy_loss=3.6,  # 36% loss (e=0.8)
        tolerance=0.01
    )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
initial_kinetic_energyYes
final_kinetic_energyYes
initial_potential_energyYes
final_potential_energyYes
expected_energy_lossNo
toleranceNo
Behavior4/5

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

No annotations provided, but description fully explains the tool's behavior: checks conservation, returns detailed results. No side effects mentioned, but it's a read-only verification.

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?

Well-structured with sections, but slightly long due to example and tips. Front-loads purpose efficiently.

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

Completeness4/5

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

Comprehensive with return value description and example. Lacks error handling info, but output schema not provided.

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?

Each parameter is described with units and purpose in the Args section. Schema coverage is 0%, so description carries full burden and does it well.

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 it verifies energy conservation in physics processes. Differentiates from siblings like check_momentum_conservation by focusing on 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 tips for when to use (isolated systems, friction, numerical errors) and example usage. Does not explicitly mention when not to use or compare to alternatives.

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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