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IBM

Physics MCP Server

by IBM

step_simulation

Advance physics simulations by specified timesteps to calculate positions, velocities, and collision states of rigid bodies.

Instructions

Step the simulation forward in time.

Advances the physics simulation by running the integrator for N steps.
Returns the complete state of all bodies after stepping.

Args:
    sim_id: Simulation ID
    steps: Number of timesteps to simulate. Default 1.
        Example: steps=600 with dt=0.016 = 9.6 seconds of simulation
    dt: Optional timestep override (seconds). If None, uses config default.

Returns:
    SimulationStepResponse containing:
        - sim_id: Simulation identifier
        - time: Current simulation time in seconds
        - bodies: List of all body states with positions, velocities, contacts

Tips for LLMs:
    - Each body state includes position, orientation (quaternion), velocities
    - contacts array shows active collisions with impulse magnitudes
    - For real-time preview: steps=1, call repeatedly
    - For final result: steps=1000+, call once
    - Large step counts may timeout - limit to ~10,000 steps per call

Example:
    # Simulate 10 seconds at 60 FPS
    result = await step_simulation(
        sim_id=sim_id,
        steps=600  # 600 steps × 0.016s = 9.6s
    )
    for body in result.bodies:
        print(f"{body.id}: position={body.position}")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sim_idYes
stepsNo
dtNo
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly describes what the tool does (advances simulation, returns complete state), includes performance considerations (timeout warnings), and details the return format (SimulationStepResponse with sim_id, time, bodies including positions, velocities, contacts). This goes well beyond basic functionality.

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?

The description is well-structured with clear sections (purpose, args, returns, tips, example) and front-loaded key information. While comprehensive, some sentences in the tips section could be more concise (e.g., the real-time vs. final result guidance is slightly verbose). Overall, it's appropriately sized for a complex tool.

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 the tool's complexity (3 parameters, no annotations, no output schema), the description provides complete context. It covers purpose, parameters, return values, usage scenarios, performance limits, and includes a practical example. The 'Tips for LLMs' section adds valuable agent-specific guidance that compensates for the lack of structured output schema.

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?

Despite 0% schema description coverage, the description provides comprehensive parameter semantics. It explains 'sim_id' as 'Simulation ID', 'steps' with default values and practical examples ('Example: steps=600 with dt=0.016 = 9.6 seconds'), and 'dt' as 'Optional timestep override (seconds)' with conditional behavior. 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 the tool's purpose with specific verbs ('step forward in time', 'advances the physics simulation by running the integrator') and identifies the resource ('simulation'). It distinguishes itself from sibling tools like 'create_simulation' or 'destroy_simulation' by focusing on time progression rather than setup or teardown.

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 provides explicit guidance on when to use this tool vs. alternatives, including 'For real-time preview: steps=1, call repeatedly' and 'For final result: steps=1000+, call once'. It also warns about limitations ('Large step counts may timeout - limit to ~10,000 steps per call'), offering clear usage context.

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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