ThrustLab

Sweep a powertrain

sweep_powertrain

Solve a powertrain across a throttle or airspeed range, up to 25 points.

`sweep.steps` is the NUMBER OF POINTS, not a step size: start 40, stop 100,
steps 4 gives 40, 60, 80 and 100. One sweep beats a loop of single points.
The points come back in `result.points` with the share URL; no second call
is needed to read them.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "powertrain": "<powertrain>",
      "sweep": "<sweep>"
    },
    "name": "sweep_powertrain"
  }
}

Input Schema

Name	Required	Description	Default
`sweep`	Yes
`powertrain`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 2, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare this is not read-only, not destructive, not idempotent, and closed-world. The description adds useful behavioral context: the result comes back in result.points with a share URL, so no second call is needed to read the points.

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 front-loaded with purpose and range, then immediately addresses the steps ambiguity with a worked example. Every sentence earns its place, and there is no filler.

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 nested schemas and the presence of an output schema, the description provides exactly the extra clarification an agent needs: the range limit, the steps-as-points semantics, and the fact that the result is returned directly. Safety behavior is covered by annotations.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The top-level schema properties have no descriptions, so the description carries extra burden. It clarifies the most error-prone parameter with a concrete example: sweep.steps is the number of points, not a step size, and start 40, stop 100, steps 4 yields 40, 60, 80, 100.

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?

States a specific verb and resource: solve/sweep a powertrain across a throttle or airspeed range. It also distinguishes itself from a loop of single-point simulations, which is the key alternative an agent would otherwise choose.

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?

Clearly recommends using one sweep instead of a loop of single points, giving context for when this tool is appropriate. It does not explicitly name the simulate_powertrain sibling as the alternative, so the routing guidance is strong but not exhaustive.

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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