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IBM

Physics MCP Server

by IBM

check_equilibrium

Checks if a system is in static equilibrium by verifying net force and net torque are zero. Input forces and their positions to test balance.

Instructions

Check complete static equilibrium: ΣF = 0 and Στ = 0.

For static equilibrium, both force and torque must be balanced.

Args:
    forces: List of force vectors [[x,y,z], ...] in N (or JSON string)
    force_positions: Positions where forces applied [[x,y,z], ...] (or JSON string)
    pivot_point: Pivot point for torque calculation [x,y,z] (default [0,0,0])
    tolerance: Tolerance for equilibrium check (default 0.01)

Returns:
    Dict containing:
        - force_balanced: Whether ΣF = 0
        - torque_balanced: Whether Στ = 0
        - in_equilibrium: Whether system is in static equilibrium
        - net_force: Net force [x, y, z] in N
        - net_torque: Net torque [x, y, z] in N⋅m

Example - Beam with two forces:
    result = await check_equilibrium(
        forces=[[0, 100, 0], [0, -100, 0]],
        force_positions=[[1, 0, 0], [2, 0, 0]]
    )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
forcesYes
force_positionsYes
pivot_pointNo
toleranceNo
Behavior4/5

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

With no annotations, the description thoroughly explains the equilibrium conditions and return values. It adds context about input formats and defaults, making the tool's behavior clear.

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 a purpose statement, Args/Returns sections, and an example. It is efficient and front-loaded.

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?

The description covers input, output, and an example sufficiently for a simple calculation tool. It could add notes on error handling or edge cases, but it's largely complete.

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?

Schema coverage is 0%, but the description adds detailed meaning: forces as vector lists with units, positions as coordinates, pivot default, tolerance default, and a concrete example. This fully compensates for the schema gap.

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 it checks static equilibrium (ΣF=0 and Στ=0), distinguishing it from sibling tools like 'check_force_balance' and 'check_torque_balance' which check only one condition.

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 implies usage for full equilibrium checks, and the presence of sibling tools for individual balances provides context. However, it lacks explicit when-to-use or when-not-to-use guidance.

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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