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IBM

Physics MCP Server

by IBM

calculate_average_speed

Calculate average speed from position vectors and time values, returning total distance, elapsed time, and displacement.

Instructions

Calculate average speed along a path.

Average speed = total distance / total time
(Distance is path length, not displacement)

Args:
    positions: Position vectors [[x,y,z], ...] in meters (or JSON string)
    times: Time values in seconds (or JSON string)

Returns:
    Dict containing:
        - average_speed: Average speed in m/s
        - total_distance: Total path length in meters
        - total_time: Total elapsed time in seconds
        - displacement_magnitude: Straight-line displacement in meters
        - displacement: Displacement vector [x,y,z] in meters

Example - Car on winding road:
    result = await calculate_average_speed(
        positions=[[0,0,0], [10,5,0], [20,10,0], [15,20,0]],
        times=[0, 10, 20, 30]
    )

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
positionsYes
timesYes
Behavior4/5

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

No annotations are provided, so the description fully assumes the burden. It explains the calculations and return dictionary fields. It does not mention side effects or permissions, but for a stateless calculation tool this is sufficient.

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, front-loaded with purpose, and uses a clear structure with Args, Returns, and an Example section. Every sentence adds value.

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?

Despite lacking an output schema, the description comprehensively details all return fields. Given the tool's simplicity and the presence of many similar sibling tools, the description is 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?

With 0% schema description coverage, the description fully compensates by explaining that positions are position vectors and times are time values, including units and acceptable formats (list or JSON string). The example further clarifies 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 'Calculate average speed along a path' and provides the formula. It distinguishes from sibling tools like calculate_instantaneous_velocity by focusing on average over a segment.

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

Usage Guidelines3/5

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

The description includes the formula and return values but does not explicitly advise when to use this tool versus alternatives like calculate_instantaneous_velocity. Usage is implied but not contrasted.

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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