kojikubota/Self-Evolving-Agent-Prompt

Self-Evolving Knowledge Curation Agent Prompt

A sophisticated prompt-based framework for creating self-evolving knowledge curation agents capable of highly intelligent dialogue, operating purely through prompts without external modules while maintaining contextual awareness and adaptive learning capabilities.

Overview

The Self-Evolving Knowledge Curation Agent is an advanced prompt framework designed to create AI agents that can engage in intelligent dialogue while continuously evolving their knowledge structures and interaction patterns within a single session. The system emphasizes efficient knowledge management, adaptive learning, and sophisticated dialogue strategies.

Key Features

• Dynamic Session Management: Single-session focused memory system
• Adaptive Knowledge Structures: Real-time concept evolution
• Intelligent Dialogue Strategy: Context-aware response generation
• Self-Critical Analysis: Continuous self-improvement
• Emergent Learning: Pattern recognition and knowledge synthesis
• Resource Optimization: Efficient token and memory usage

Core Components

1. Memory Management

• Session-based Memory
• Knowledge Base Structure
• Context Management
• Information Compression

2. Basic Principles

• Knowledge Structuring
• Dialogue Strategy
• Response Generation
• Quality Assurance

3. Operational Framework

• Input Analysis
• Context Evaluation
• Strategy Decision
• Response Generation
• Quality Check

Usage Guide

Basic Interactions

To effectively utilize the Self-Evolving Agent:

1. Session Initialization

"Begin new conversation session"
"Set initial knowledge context"

2. Knowledge Interaction

"Request explanation of [concept]"
"Explore relationships between [concepts]"

3. Feedback Integration

"Provide feedback on explanation"
"Request adjustment of detail level"

Advanced Usage

For sophisticated knowledge curation:

"Trigger metacognitive analysis"
"Request concept evolution exploration"
"Initiate creative problem-solving sequence"

Target Applications

Application Area	Description
Knowledge Curation	Dynamic information organization
Educational Dialogue	Adaptive learning assistance
Problem Solving	Creative solution generation
Concept Analysis	Deep knowledge exploration

Evaluation Framework

Performance Metrics

Knowledge Integration: 1-5
Dialogue Effectiveness: 1-5
Adaptation Capability: 1-5
Resource Efficiency: 1-5

Limitations and Considerations

• Single-session memory constraints
• No external resource access
• Token usage optimization
• Privacy and security boundaries
• Ethical consideration framework

Future Development

The framework aims to evolve through:

• Enhanced pattern recognition
• Advanced knowledge synthesis
• Improved metacognitive functions
• Expanded creative capabilities
• Refined self-evolution mechanisms

Security and Ethics

• Privacy-focused processing
• Ethical decision-making
• Transparent reasoning
• Responsible knowledge curation
• User safety considerations

Contributing

Contributions to enhance the framework are welcome. Please ensure to:

1. Follow the prompt-based architecture
2. Maintain session integrity
3. Optimize resource usage
4. Document thoroughly
5. Consider ethical implications