Self Reflection
A continuous self-improvement skill for AI agents that tracks mistakes, logs lessons learned, and builds institutional memory over time through structured feedback loops and regular performance reviews.
🚀 Self-Reflection enables AI agents to learn from mistakes and improve over time. The skill automatically triggers regular check-ins where agents pause, review recent performance, identify what went wrong, and document lessons learned in a memory log. This creates a continuous feedback loop that prevents repeating errors.
💡 Perfect for agents that handle complex tasks, customer interactions, or decision-making. Use it to build institutional knowledge, reduce failure rates, and ensure agents get smarter with each task. Ideal when consistency and reliability matter most.
✨ Unlike agents that reset with each session, Self-Reflection creates persistent learning. Your agent remembers what worked, what didn't, and adapts accordingly—turning experience into competitive advantage.
Requirements
No additional requirements.