scorecompute✳
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RUST ENGINE / audit_statistics

GRIM and GRIMMER statistics checks

Screen reported means and standard deviations for arithmetic inconsistency under an integer-valued data model.

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How it works

GRIM tests whether an integer sum can produce a reported rounded mean at a given sample size. The standard-deviation screening also considers the possible sums compatible with rounding and necessary integer second-moment conditions.

Inputs and units

Provide sample size, reported mean, decimal precision, optional standard deviation and the minimum and maximum integer response values.

What the result contains

The result reports inconsistencies, nearest reachable quantities and the assumptions used. Consistent means that the implemented filters found no contradiction; it does not reconstruct or verify the original observations.

Example MCP call

{
  "name": "audit_statistics",
  "arguments": {
    "n": 10,
    "mean": 3.48,
    "decimals": 2,
    "min_value": 1,
    "max_value": 5
  }
}

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Method reference

GRIMMER methods, Anaya ↗

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. CUDA is implemented for simulate_pi; the other tools currently run on CPU. 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.

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