{"skill":{"slug":"bookforge-learning-calibration-audit","displayName":"Learning Calibration Audit","summary":"Diagnose and correct false confidence in learning mastery using cognitive science research. Use when you feel confident about a topic but keep failing tests,...","tags":{"bookforge":"1.0.0","calibration":"1.0.0","cognitive-bias":"1.0.0","cognitive-psychology":"1.0.0","dunning-kruger":"1.0.0","evidence-based-learning":"1.0.0","latest":"1.0.0","learning-science":"1.0.0","metacognition":"1.0.0","overconfidence":"1.0.0","self-assessment":"1.0.0","study-skills":"1.0.0","training-design":"1.0.0"},"stats":{"comments":0,"downloads":64,"installsAllTime":0,"installsCurrent":0,"stars":0,"versions":1},"createdAt":1776416155956,"updatedAt":1776416211611},"latestVersion":{"version":"1.0.0","createdAt":1776416155956,"changelog":"Initial release: Provides a comprehensive skill for diagnosing and correcting false confidence in learning mastery using evidence-based cognitive science methods.\n\n- Identifies which of seven cognitive distortions (e.g., fluency illusion, hindsight bias, Dunning-Kruger) are inflating self-assessment accuracy.\n- Distinguishes reliable mastery indicators from unreliable ones to spot calibration issues.\n- Recommends calibration instruments (like self-quizzing, peer instruction) matched to each detected distortion.\n- Designs a dynamic, iterative testing cycle to assess, target, and retest learning gaps.\n- Produces a detailed calibration report with identified distortions, recommended interventions, and a retest schedule.\n- Applicable to students, professionals, trainers, and anyone seeking to audit their learning mastery across various contexts.","license":"MIT-0"},"metadata":{"os":null,"systems":null},"owner":{"handle":"quochungto","userId":"s176b6gfk8djgcz320d83ta4e184bx1v","displayName":"Hung Quoc To","image":"https://avatars.githubusercontent.com/u/88069966?v=4"},"moderation":null}