​

Agent Development Protocol

​

Introduction

​

Agent System Architecture

​

Core Agent Framework

​

Agent Types and Roles

​

Development Lifecycle

​

Agent Development Process

​

Development Phases

​

Prompt Engineering Framework

​

System Message Architecture

1. Identity and Role: Core identity and purpose
2. Personality and Voice: Tone, style, and expression patterns
3. Core Capabilities: Primary functions and skills
4. Knowledge Access: Information sources and retrieval patterns
5. Interaction Patterns: Conversational flows and techniques
6. Guardrails and Limitations: Boundaries and safety measures
7. Performance Guidelines: Quality and effectiveness standards

​

Example System Message Structure

# AGENT IDENTITY: [Agent Name]

## ROLE
[Concise description of the agent's role in the ecosystem]

## PERSONALITY
[Description of personality, tone, and communication style]

## CORE CAPABILITIES
- [Capability 1]: [Description]
- [Capability 2]: [Description]
- [Capability 3]: [Description]

## KNOWLEDGE ACCESS
[Description of knowledge sources and how they should be used]

## INTERACTION GUIDELINES
[Guidelines for conversation flow, response structure, etc.]

## LIMITATIONS AND BOUNDARIES
[Clear boundaries on what the agent should not do/discuss]

## PERFORMANCE STANDARDS
[Standards for response quality, helpfulness, etc.]

​

Few-Shot Examples

1. Example Selection Criteria
   • Represent common use cases
   • Demonstrate ideal response patterns
   • Illustrate edge case handling
   • Show appropriate tool usage
2. Example Structure
   Copy

   USER: [Example user input]
   
   AGENT: [Ideal agent response demonstrating desired behavior]
   

3. Coverage Requirements
   • Basic information requests
   • Complex problem-solving scenarios
   • Emotional or sensitive topics
   • Tool usage scenarios
   • Multi-turn conversations

​

Knowledge Management

​

Knowledge Architecture

​

Retrieval Augmented Generation (RAG)

1. Vector Database Integration
   • Document chunking strategy
   • Embedding model selection
   • Query construction techniques
   • Result ranking and filtering
2. Knowledge Integration
   • Contextual insertion of retrieved information
   • Source attribution and transparency
   • Conflict resolution between sources
   • Confidence-based reasoning
3. Knowledge Freshness
   • Update frequency for knowledge bases
   • Versioning of critical information
   • Timestamp-based relevance assessment
   • Automated knowledge refresh triggers

​

Tool Use Framework

​

Tool Architecture

​

Tool Types

​

Tool Definition Standard

interface Tool {
  name: string;              // Unique tool identifier
  description: string;       // Clear description of tool purpose
  parameters: Parameter[];   // Required and optional parameters
  returns: ReturnType;       // Output structure and type
  permissions: Permission[]; // Required access permissions
  examples: Example[];       // Usage examples
}

​

Memory System

​

Memory Architecture

1. Short-term Conversation Memory
   • Current conversation history
   • Recent user preferences and choices
   • Session-specific context
2. Long-term User Memory
   • Persistent user preferences
   • Historical interactions
   • Relationship development
3. Episodic Memory
   • Significant interaction events
   • Previous problem resolutions
   • User milestone achievements

​

Memory Integration

​

Testing and Evaluation

​

Evaluation Framework

​

Test Suite Architecture

1. Automated Evaluations
   • Unit tests for specific capabilities
   • Regression tests for established functionality
   • Performance benchmarks
   • Safety and boundary tests
2. Human Evaluation
   • Expert review panels
   • User testing sessions
   • Comparative evaluations
   • Blind A/B testing

​

Security and Safety

​

Guardrails Implementation

1. Input Filtering
   • Harmful content detection
   • Intent classification
   • Topic boundary enforcement
   • Privacy protection
2. Output Monitoring
   • Toxic content filtering
   • Fact-checking for critical domains
   • Uncertainty signaling
   • Response diversity
3. Operational Safeguards
   • Rate limiting
   • Authentication requirements
   • Permission-based tool access
   • Audit logging

​

Ethical Use Guidelines

1. Transparency: Clear identification as AI system
2. Honesty: Accurate representation of capabilities
3. Privacy: Minimal data usage and strong protection
4. Inclusivity: Design for diverse user needs
5. Human-centricity: Augment rather than replace
6. Accessibility: Usable by people of all abilities

​

Integration Patterns

​

Agent-to-Platform Integration

​

Inter-Agent Communication

1. Handoff Protocol
   • Context preservation
   • Purpose specification
   • Identity transparency
   • Continuity management
2. Consultation Pattern
   • Capability identification
   • Query formulation
   • Response integration
   • Attribution preservation

​

Implementation Resources

​

Version Control and Management

​

Agent Versioning

1. Major Version: Significant personality or capability changes
2. Minor Version: New features or capability enhancements
3. Patch Version: Bug fixes and minor improvements

​

Change Management

1. Proposal and Specification
2. Impact Analysis
3. Development and Testing
4. Gradual Rollout (A/B Testing)
5. Full Deployment
6. Monitoring and Validation

​

Future Development Roadmap

1. Enhanced Personalization
   • Deeper user preference integration
   • Adaptive personality traits
   • Learning from interaction patterns
2. Multimodal Capabilities
   • Image understanding and generation
   • Audio processing and generation
   • Interactive visualization
3. Advanced Reasoning
   • Complex problem decomposition
   • Multi-step planning
   • Verification and self-correction
4. Collaborative Intelligence
   • Agent teaming frameworks
   • Specialized agent cooperation
   • Human-AI collaboration patterns