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/calibrate-probability-forecast

Aggregate and iteratively recalibrate probabilistic forecasts, preserving uncertainty, calibration evidence, and unresolved forecaster disagreement.

From plugin
de-anthropocentric-research-engine
507200 skills

Claude Code

$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill calibrate-probability-forecast --agent claude-code

SKILL.md

calibrate-probability-forecast.SKILL.md
name: calibrate-probability-forecast
description: "Aggregate and iteratively recalibrate probabilistic forecasts, preserving uncertainty, calibration evidence, and unresolved forecaster disagreement."

calibrate-probability-forecast

Purpose

Aggregate probabilistic forecasts, compare them with outcomes, and recalibrate without hiding unresolved forecaster disagreement.

Input contract

required: [forecast_records, outcome_records, calibration_rule]
optional: [forecaster_metadata, prior_calibration, aggregation_method]
constraints: [each forecast has a target, probability, timestamp, horizon, and provenance]

Procedure

1. Align forecasts with realized outcomes at the declared horizon and freeze the evaluation set. 2. Compute calibration evidence by probability band and forecaster, preserving sample size and missing outcomes. 3. Update the aggregation or calibration rule only where outcome-linked error supports the change. 4. Emit recalibrated probabilities, calibration diagnostics, disagreement intervals, and the next review trigger.

Output contract

produces: [calibrated_forecasts, calibration_diagnostics, disagreement_report, review_trigger]
delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties, decisions, open_questions]

Quality gates

  • A-class gate: declared universe = all closed forecasts in the evaluation horizon; numerator = forecasts with outcome linkage and valid timestamp/probability; batch increment = one closed forecast; stopping reason = calibration error stabilizes or the closed set is exhausted; source references = forecast/outcome IDs and calibration runs; direction/threshold reason = recalibration moves probabilities toward observed frequencies only when the declared scoring rule shows systematic error.
  • Never collapse unresolved disagreement into a single certainty value.

Failure and counterexamples

Do not score forecasts whose outcomes are not yet observable. A changed probability without new outcome-linked evidence is a model revision, not calibration.

Provenance map

  • resolved: futures-calibration
Read more
@yogsoth-ai
Ships withde-anthropocentric-research-engine

A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.

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Questions about calibrate-probability-forecast.

Which coding agents can use calibrate-probability-forecast?
calibrate-probability-forecast installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.