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Metacognitive Monitoring(MCM)
Self-awareness and monitoring of reasoning quality and confidence
In 30 seconds
- What
- Agent tracks its own reasoning quality, confidence levels, and knowledge gaps, then adjusts strategy or requests clarification based on self-assessment.
- When to use
- High-stakes decisions where wrong answers cause real harm and intermediate confidence checks can trigger additional data gathering or expert review.
- Watch out
- Confidence estimates often correlate poorly with actual accuracy; overconfident agents skip necessary verification steps despite high self-reported certainty.
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Metacognitive Monitoring: Overview
Self-awareness and monitoring of reasoning quality and confidence
- Reasoning quality assessment
- Confidence estimation
- Knowledge gap detection
- Strategy effectiveness monitoring
- Adaptive reasoning adjustment
- Error anticipation
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References
The papers, specifications, and repositories this pattern is based on.
- Teaching Large Language Models to Self-Debug (Chen et al., 2023)arXiv:2304.05128
- Self-Refine: Iterative Refinement with Self-Feedback (Madaan et al., 2023)arXiv:2303.17651
- Constitutional AI: Harmlessness from AI Feedback (Bai et al., 2022)arXiv:2212.08073
- LangChain Self-Correction Patterns
- DSPy Official Documentation
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