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whats2000

Isaac Sim MCP Server

by whats2000

step_simulation

Step simulation forward by a specified number of frames to inspect prim positions, velocities, and joint states. Debug robot behavior in a single call.

Instructions

Step the simulation forward by N frames, then observe prim and joint states.

This is the primary tool for debugging robot behavior. Use it instead of play_simulation + sleep + execute_script. The observe parameters let you inspect positions, velocities, and joint states in a single call.

Typical debug loop:

  1. set_joint_positions to command the robot

  2. step_simulation with observe_prims and observe_joints

  3. get_joint_config if drives are not tracking correctly

  4. get_physics_state if objects are not behaving as expected

  5. Adjust and repeat

Args: num_steps: Number of simulation frames to step. observe_prims: List of prim paths to observe (returns position + velocity). observe_joints: List of articulation prim paths to observe (returns joint positions).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
num_stepsNo
observe_primsNo
observe_jointsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Discloses that stepping simulation advances by N frames and observes states, which is the core behavior. Lacks mention of potential side effects (e.g., irreversible physics state changes) but is adequate for a simulation stepping tool. No annotations to contradict.

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?

Well-structured with a concise first sentence, then rationale for usage, a debug loop example, and parameter docs. Every sentence adds value 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 the tool has 3 optional parameters and an output schema, the description covers purpose, usage, parameters, and provides a typical workflow, making it fully sufficient for an AI agent to use 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?

Description includes an 'Args' section that clearly explains all three parameters (num_steps, observe_prims, observe_joints), adding meaning beyond the input schema which has no descriptions.

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?

Description uses specific verb 'step' and resource 'simulation', clearly states it's for debugging robot behavior, and distinguishes from siblings like play_simulation and execute_script.

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?

Explicitly recommends using instead of play_simulation + sleep + execute_script, and provides a typical debug loop with numbered steps, giving clear when-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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