Metacognition Engine

Give your AI agent the ability to think about its own thinking.

What is Metacognition?

Metacognition = "thinking about thinking." This skill enables AI agents to:

• Detect when they're uncertain or confused
• Identify reasoning gaps before they cause errors
• Recognize cognitive biases in their own output
• Self-correct before delivering answers

Core Framework

1. Pre-Output Check

Before responding, run through these questions:

1. Am I confident in this answer? (Yes / Partial / No)
2. What are the 3 most likely ways this could be wrong?
3. What information would I need to be 100% certain?

2. Cognitive Bias Detection

Check for common biases:

• Anthropomorphism — projecting human traits onto AI
• Authority bias — deferring to stated credentials without verification
• Hindsight bias — acting like something was obvious after the fact
• Confirmation bias — seeking only confirming evidence

3. Uncertainty Quantification

Express confidence explicitly:

Confidence	Meaning	Action
90%+	Highly confident	Answer directly
70-89%	Likely correct	Answer + add caveat
50-69%	Uncertain	Ask clarifying questions
<50%	Likely wrong	Decline or escalate

Example

Without metacognition:

"The capital of France is Paris."

With metacognition:

"Based on my training data, the capital of France is Paris (confidence: 95%). Note: My knowledge has a cutoff date. For real-time data, verify current information."

Use Cases

• Critical decisions: Add metacognition checkpoint before any consequential answer
• User corrections: When a user corrects you, analyze WHY you were wrong
• Complex problems: Run bias detection before solving multi-step problems
• Knowledge boundaries: Automatically flag when you're approaching your knowledge limit

MIT License © SKY-lv