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IBM

Physics MCP Server

by IBM

calculate_angular_acceleration

Calculate angular acceleration from torque and moment of inertia using α = τ/I. Determine rotational acceleration for motors, flywheels, and spinning objects.

Instructions

Calculate angular acceleration: α = τ / I.

Angular acceleration is the rotational equivalent of linear acceleration.
Determined by net torque and moment of inertia.

Args:
    torque: Torque magnitude in N⋅m
    moment_of_inertia: Moment of inertia in kg⋅m²

Returns:
    Dict containing:
        - angular_acceleration: α in rad/s²

Tips for LLMs:
    - Rotational version of F = ma → τ = Iα
    - Larger I means slower angular acceleration for same torque
    - Use for: motor acceleration, spinning up flywheels

Example - Motor accelerating a wheel:
    result = await calculate_angular_acceleration(
        torque=10.0,  # N⋅m
        moment_of_inertia=0.5  # kg⋅m²
    )
    # α = 20 rad/s²

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
torqueYes
moment_of_inertiaYes
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by explaining the calculation behavior, providing the formula, units, and example. It clarifies the rotational physics context and practical applications, though it doesn't mention computational limits 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?

Perfectly structured with formula, explanation, parameter definitions, return specification, usage tips, and a practical example - all in well-organized sections with zero wasted text. Every sentence adds value and the most critical information (formula) comes first.

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?

For a 2-parameter calculation tool with no annotations and no output schema, the description provides complete context: purpose, physics background, parameter semantics, return format, usage guidance, and a working example. Nothing essential is missing for an AI agent to correctly invoke this tool.

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 has 0% description coverage, but the description fully compensates by clearly defining both parameters with their physical meanings (torque magnitude, moment of inertia), units (N⋅m, kg⋅m²), and their role in the calculation. The example further illustrates proper usage.

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 angular acceleration using the formula α = τ / I, specifying it's the rotational equivalent of linear acceleration. It distinguishes from siblings like calculate_torque or calculate_moment_of_inertia by focusing on the derived acceleration quantity rather than inputs or other physics calculations.

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 'Tips for LLMs' section provides clear context for when to use this tool (motor acceleration, spinning up flywheels) and explains the physical relationship (τ = Iα). However, it doesn't explicitly state when NOT to use it or name specific alternative tools among the many physics calculation siblings.

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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