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IBM

Physics MCP Server

by IBM

calculate_centripetal_force

Calculate the inward force needed to keep an object moving in a circular path using mass, velocity, and radius. Useful for analyzing car turns, satellite orbits, and centrifuges.

Instructions

Calculate centripetal force: F_c = m v² / r.

Force required to keep an object moving in a circle.
Always points toward the center of the circular path.

Args:
    mass: Mass in kg
    velocity: Speed (velocity magnitude) in m/s
    radius: Radius of circular path in meters

Returns:
    Dict containing:
        - centripetal_force: F_c in Newtons
        - centripetal_acceleration: a_c in m/s²

Tips for LLMs:
    - Not a new force - it's the net inward force (tension, friction, gravity)
    - Faster speed → much more force needed (v² relationship)
    - Tighter turn → more force needed
    - Use for: car turns, satellite orbits, centrifuges

Example - Car turning:
    result = await calculate_centripetal_force(
        mass=1500,  # kg
        velocity=20,  # m/s (72 km/h)
        radius=50  # meter turn radius
    )
    # F_c = 12000 N (provided by friction between tires and road)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
massYes
velocityYes
radiusYes
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 tool's behavior: it calculates force and acceleration, provides return format details, and includes practical examples. It doesn't mention error handling or computational limits, but covers core behavior thoroughly.

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 formula, explanation, parameters, returns, tips, and example. The information is front-loaded with the core formula first. Some redundancy exists (explaining v² relationship in both formula and tips), but overall efficient.

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 calculation tool with no annotations and no output schema, the description provides complete context: purpose, parameters with units, return format, usage guidance, and practical example. It addresses all necessary aspects for an AI agent to use it 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?

With 0% schema description coverage, the description fully compensates by clearly documenting all 3 parameters with units (kg, m/s, meters) and physical meanings. The Args section provides complete parameter semantics beyond what the bare schema offers.

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 purpose with the specific formula F_c = m v² / r and explains it's the force required for circular motion. It distinguishes from siblings like calculate_force (general) or calculate_normal_force by focusing specifically on centripetal dynamics.

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

Usage Guidelines5/5

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

The 'Tips for LLMs' section explicitly states when to use this tool ('car turns, satellite orbits, centrifuges') and provides conceptual guidance about when it applies (net inward force, not a new force). It differentiates from alternatives by focusing on circular motion scenarios.

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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