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Physics MCP Server

by IBM

calculate_static_friction

Calculate maximum static friction force and determine whether an object will slip under an applied horizontal force.

Instructions

Calculate maximum static friction force: f_s,max = μ_s × N.

Determines whether an object will slip under applied force.

Args:
    normal_force: Normal force in Newtons
    coefficient_static_friction: Coefficient of static friction μ_s
    applied_force: Applied horizontal force in Newtons (optional)

Returns:
    Dict containing:
        - max_static_friction: Maximum static friction in Newtons
        - will_slip: Whether object will slip (if applied_force provided)
        - friction_force: Actual friction force (if applied_force provided)

Example - Box on floor:
    result = await calculate_static_friction(
        normal_force=100,
        coefficient_static_friction=0.5,
        applied_force=40
    )
    # will_slip = False (40N < 50N max)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
normal_forceYes
coefficient_static_frictionYes
applied_forceNo

Implementation Reference

  • Core handler: computes f_s,max = μ_s × N, determines if object slips, returns actual friction force
    def calculate_static_friction(request: StaticFrictionRequest) -> StaticFrictionResponse:
        """Calculate maximum static friction force: f_s,max = μ_s × N.
    
        Args:
            request: Static friction request
    
        Returns:
            Maximum static friction and slip prediction
        """
        max_static_friction = request.coefficient_static_friction * request.normal_force
    
        will_slip = None
        friction_force = None
    
        if request.applied_force is not None:
            will_slip = request.applied_force > max_static_friction
            # Actual friction force equals applied force up to the maximum
            friction_force = min(request.applied_force, max_static_friction)
    
        return StaticFrictionResponse(
            max_static_friction=max_static_friction,
            will_slip=will_slip,
            friction_force=friction_force,
        )
  • MCP tool endpoint: async @tool-decorated function that wraps the core statics handler and exposes it via MCP protocol
    @tool  # type: ignore[arg-type]
    async def calculate_static_friction(
        normal_force: float,
        coefficient_static_friction: float,
        applied_force: float | None = None,
    ) -> dict:
        """Calculate maximum static friction force: f_s,max = μ_s × N.
    
        Determines whether an object will slip under applied force.
    
        Args:
            normal_force: Normal force in Newtons
            coefficient_static_friction: Coefficient of static friction μ_s
            applied_force: Applied horizontal force in Newtons (optional)
    
        Returns:
            Dict containing:
                - max_static_friction: Maximum static friction in Newtons
                - will_slip: Whether object will slip (if applied_force provided)
                - friction_force: Actual friction force (if applied_force provided)
    
        Example - Box on floor:
            result = await calculate_static_friction(
                normal_force=100,
                coefficient_static_friction=0.5,
                applied_force=40
            )
            # will_slip = False (40N < 50N max)
        """
        from ..statics import StaticFrictionRequest
        from ..statics import calculate_static_friction as calc_friction
    
        request = StaticFrictionRequest(
            normal_force=normal_force,
            coefficient_static_friction=coefficient_static_friction,
            applied_force=applied_force,
        )
        response = calc_friction(request)
        return response.model_dump()
  • Pydantic request model: normal_force (gt=0), coefficient_static_friction (ge=0), applied_force (optional)
    class StaticFrictionRequest(BaseModel):
        """Request for static friction calculation."""
    
        normal_force: float = Field(..., description="Normal force in Newtons", gt=0.0)
        coefficient_static_friction: float = Field(
            ..., description="Coefficient of static friction μ_s", ge=0.0
        )
        applied_force: Optional[float] = Field(
            None, description="Applied horizontal force in Newtons (optional)"
        )
  • Pydantic response model: max_static_friction, will_slip (optional), friction_force (optional)
    class StaticFrictionResponse(BaseModel):
        """Response for static friction calculation."""
    
        max_static_friction: float = Field(..., description="Maximum static friction force in Newtons")
        will_slip: Optional[bool] = Field(
            None, description="Whether object will slip (if applied_force provided)"
        )
        friction_force: Optional[float] = Field(
            None, description="Actual friction force in Newtons (if applied_force provided)"
        )
  • Registration: importing statics module triggers @tool decorator registration of calculate_static_friction
    # Import all tools modules to register their @tool decorated functions
    from .tools import (
        basic,
        rotational,
        oscillations,
        circular_motion,
        collisions,
        conservation,
        fluid as fluid_tools,
        kinematics_tools,
        statics,
        convert_units as unit_conversion_tools,
    )
    
    # Silence unused import warnings - these imports register @tool decorated functions
    _ = (
        basic,
        unit_conversion_tools,
        rotational,
        oscillations,
        circular_motion,
        collisions,
        conservation,
        fluid_tools,
        kinematics_tools,
        statics,
    )
Behavior5/5

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

With no annotations, the description fully discloses the tool's behavior: it computes static friction and optionally checks slip. It avoids any side effects, and the example clarifies the output format. No contradictions.

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 concise, well-structured with Args, Returns, and Example sections. Each sentence adds value, and the example illustrates usage efficiently 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 no output schema, the description documents the full return dictionary with fields and conditions. It also includes a concrete example. For a simple physics calculator, this is complete and covers all necessary context.

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 input schema has 0% description coverage, so the description compensates fully. It explains each parameter (normal_force, coefficient_static_friction, applied_force) with units and optionality, and provides example values. This adds significant meaning beyond the schema.

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 explicitly states the tool calculates maximum static friction force and determines slip condition. It provides the formula f_s,max = μ_s × N and an example, making the purpose highly clear and distinct from sibling tools like calculate_kinetic_energy or calculate_force.

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 includes when to use (to check if an object slips) and gives an example, but does not explicitly mention alternatives or when not to use (e.g., kinetic friction). Still, the context is clear enough for most 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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