Schedule uncertainty simulation

What does a real call return?

For task durations of 60 and 30 minutes, a 100-minute budget and 25% uncertainty, 82.5% of 100,000 scenarios met the budget. Under this model the exact probability is 1 − 25/144 ≈ 82.6%. The mean duration is 90.0 minutes and the empirical 95th percentile 105.8 minutes.

Recorded on 6 November 2026 through the public MCP endpoint, service release 0.17.1. Inputs and full responses, response SHA-256 b558af85cb81…. Verdict values are the literal values the tool returns. Run the same inputs yourself to compare; elapsed times vary, and a new release may change the figures.

Checked against

• Zero uncertainty reduces the total duration, success rate and empirical percentile to a deterministic hand-calculated sum.

Recorded on release 0.16.1. These checks cover the listed cases, not every input. Evidence cards.

How it works

Each task duration is perturbed independently within a uniform relative uncertainty range. Repeated scenarios produce a mean duration, empirical 95th percentile and fraction of scenarios meeting the budget.

Inputs and units

Pass selected durations, a time budget, sample count, seed and relative uncertainty. The direct tool accepts your own plan. The optional native composer uses a fixed sample count per candidate only when an exact duration bound is insufficient.

What the result contains

The probability estimate and duration summaries let an assistant compare a high-value plan with its sensitivity to delays. The output records the simulation assumptions.

Example MCP call

{
  "name": "simulate_plan",
  "arguments": {
    "durations": [
      60,
      30
    ],
    "budget": 100,
    "samples": 100000,
    "seed": 42,
    "uncertainty": 0.25
  }
}

Send this tool name and arguments through a connected MCP client. Discover the authoritative input schema with tools/list.

Call this engine in one command

Node.js 20+ and npm. This downloads a small remote MCP client; it does not install the engine locally.

npx --yes --package https://scorecompute.com/downloads/scorecompute-call-0.14.2.tgz scorecompute-call simulate_plan --arguments '{"durations":[60,30],"budget":100,"samples":100000,"seed":42,"uncertainty":0.25}'

Client download, PowerShell input and verification →

Cite this engine

Engine identified by source hash, source SHA-256 5631d8095efe…. Evidence recorded on release 0.16.1; the public service currently runs 0.17.1. Replace the access date when you cite it.

ScoreCompute. Schedule uncertainty simulation (simulate_plan), identified by source hash, source SHA-256 5631d8095efedcf272a21ec6a15df6425f8e5851f74f24af55436670dcbae6de. Evidence release 0.16.1, service release 0.17.1. https://scorecompute.com/engines/simulate-plan/ (accessed YYYY-MM-DD).

All engine citations · Evidence card

Execution and availability

ScoreCompute exposes this tool through MCP Streamable HTTP. Rust computation runs on a connected worker; the public website and MCP gateway run separately. Among these 22 scientific tools, CUDA is implemented for simulate_pi; the other scientific engines run on CPU. The separate contributor network runs two compiled public workloads: a π estimate and fixed synthetic schedule probes. Requests are bounded and concurrent work may be refused when capacity is occupied.

Record inputs, assumptions and returned provenance when sharing a result. The public observatory displays software client names and tool activity, without publishing calculation arguments or results.