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outcome-tracker

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Record the testable predictions inside a decision, then score them against reality later — so frameworks earn trust from outcomes, not vibes. Use when committing to a prioritisation, forecast, or plan (to log what it predicts), when asked to review what actually happened, or to compute how well-calibrated past RICE scores, forecasts, or bets have been. Produces a prediction record at decision time, and a calibration report with per-framework hit rates at review time.

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Nov 10, 2026
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MIT

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# Outcome Tracker Skill

Every prioritisation, forecast, and launch plan makes predictions — then everyone forgets to check them. This skill closes the loop: extract the predictions at decision time, park them somewhere durable, and score them against reality on a schedule. Over time it answers the question no one can answer today: *which of our frameworks actually predict outcomes?*

## What This Skill Produces

- **At decision time:** a prediction record — each claim made falsifiable, with a metric, a direction/target, a check-by date, and a stated confidence
- **At review time:** an outcome scoring of due predictions (hit / miss / partial / unresolvable), with what was learned
- **On demand:** a calibration report — per-framework and per-confidence-band hit rates from the accumulated records

## Required Inputs

Ask for (if not already provided):
- **Mode** — record (new decision), review (score due predictions), or calibrate (analyse the history)
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