Skip to main content
skillsmp

Menú

intuitive-os

Train, test and calibrate intuition as a measurable skill, spanning raw intuition capture before analytical contamination, five-layer separation (observation, interpretation, affect, intuition, decision), intuition provenance (expert pattern, weak signal, emotion, incentive signal, bias, noise), falsifiable probabilistic forecasting with resolution criteria, base rates and Bayesian updating, decision journaling and premortems, red-teaming a hunch, Brier scoring and calibration buckets by domain, pattern-card and mental-model libraries, and a 90-day observe/calibrate/compress curriculum. Use for gut-feel checks, should-I-trust-this-instinct questions, forecasting and prediction logging, decision protocols and reviews, separating decision quality from outcome quality, spotting bias in your own judgment, weak-signal analysis, overconfidence and calibration audits, and intuition training plans. Trigger words: intuition, gut feeling, instinct, hunch, calibration, forecast, prediction, Brier, base rate, decision jo

Ir a la instalación

Datos de origen

Repositorio
agentik-os/OmegaOS
Última actividad en el origen
14 de agosto de 2026 a las 07:41
Idioma detectado de SKILL.md
inglés
Estrellas
11
Forks
2

Opciones de instalación

De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.

Revisa los archivos de origen

Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.

Explorador de archivos
15 archivos

Mostrando SKILL.md

SKILL.md
Instrucciones de origen · Vista previa de solo lectura
name
intuitive-os
description
Train, test and calibrate intuition as a measurable skill, spanning raw intuition capture before analytical contamination, five-layer separation (observation, interpretation, affect, intuition, decision), intuition provenance (expert pattern, weak signal, emotion, incentive signal, bias, noise), falsifiable probabilistic forecasting with resolution criteria, base rates and Bayesian updating, decision journaling and premortems, red-teaming a hunch, Brier scoring and calibration buckets by domain, pattern-card and mental-model libraries, and a 90-day observe/calibrate/compress curriculum. Use for gut-feel checks, should-I-trust-this-instinct questions, forecasting and prediction logging, decision protocols and reviews, separating decision quality from outcome quality, spotting bias in your own judgment, weak-signal analysis, overconfidence and calibration audits, and intuition training plans. Trigger words: intuition, gut feeling, instinct, hunch, calibration, forecast, prediction, Brier, base rate, decision journal, premortem, red team, overconfidence, pattern recognition, mental models; FR: intuition, instinct, pronostic, calibrage, pari, journal de decision, biais, surconfiance.
# Intuitive OS Skill ## Non-negotiables 1. Intuition is a hypothesis or signal, never automatic truth. 2. Capture the raw intuition before analytical contamination. 3. Separate observation, interpretation, emotion, prediction, and decision. 4. Convert meaningful forecasts into probabilities when resolvable. 5. Preserve original predictions. Never rewrite history after outcomes. 6. Score domains separately. Expertise does not transfer automatically. 7. Seek disconfirming evidence and relevant base rates. 8. Distinguish decision quality from outcome quality. 9. Avoid pseudo-scientific body-language certainty and mind-reading. 10. For safety-critical, medical, legal, financial, or high-stakes decisions, intuition may generate questions but should not replace appropriate evidence or expert review. ## Modes CAPTURE, SIGNAL, PREDICT, DECIDE, RED_TEAM, REVIEW, TRAIN, PROFILE. ## Classification For every important intuition, consider: - expert pattern - weak signal - affect/emotion - incentive recognition - bias/stereotype - noise/unknown Multiple labels may coexist. Never force certainty. ## Minimum prediction record ID, timestamp, domain, proposition, probability, horizon/resolution date, observable signals, base rate if known, counter-evidence, decision/action, outcome, review. ## Calibration Prefer proper scoring such as Brier score for binary predictions. Also report calibration buckets (50-59, 60-69, etc.), sample size, and domain. Never imply statistical reliability from tiny samples. ## Learning loop Capture -> Explain signals -> Generate alternatives -> Estimate probability -> Decide -> Resolve -> Diagnose -> Update pattern library.
Ver en GitHub
Volver a la búsquedaVolver a la instalación