AI Agent System Documentation

# AI Agent System Documentation

## Overview

ArchDesigner employs a sophisticated multi-agent AI system built on advanced Chain-of-Thought (CoT) reasoning patterns. Each agent is a specialized serverless function that performs specific tasks with high accuracy, transparency, and security.

**What is Chain-of-Thought (CoT) Reasoning?**  
Chain-of-Thought is an AI prompting technique where the model explicitly breaks down complex problems into step-by-step reasoning stages. Instead of jumping directly to an answer, the AI "shows its work" by progressing through logical stages (input gathering → analysis → problem identification → recommendations → output). This leads to more accurate, transparent, and debuggable AI decisions.

**Last Updated**: December 29, 2024  
**Version**: 0.0.0

---

## Table of Contents

- [Architecture Overview](#architecture-overview)
- [Core Agent Framework](#core-agent-framework)
- [Individual Agents](#individual-agents)
  - [Architecture Analysis Agent](#1-architecture-analysis-agent)
  - [Security Audit Agent](#2-security-audit-agent)
  - [Code Generation Agent](#3-code-generation-agent)
  - [CI/CD Pipeline Agent](#4-cicd-pipeline-agent)
  - [Documentation Agent](#5-documentation-agent)
  - [Health Check Agent](#6-health-check-agent)
  - [Security Scan Agent](#7-security-scan-agent)
  - [API Gateway Agent](#8-api-gateway-agent)
  - [Export Agent](#9-export-agent)
  - [Notification Agent](#10-notification-agent)
- [Chain-of-Thought (CoT) Framework](#chain-of-thought-cot-framework)
- [Security & Compliance](#security--compliance)
- [Best Practices](#best-practices)

---

## Architecture Overview

### Design Principles

1. **Single Responsibility**: Each agent focuses on one domain
2. **Chain-of-Thought Reasoning**: All agents use explicit multi-stage reasoning
3. **Security-First**: Input sanitization, validation, and audit logging
4. **Observable**: Comprehensive logging and metrics
5. **Validated Output**: Schema validation for all agent responses
6. **RBAC**: Role-based access control for all operations

### Technology Stack

- **Runtime**: Deno (secure JavaScript/TypeScript runtime)
- **Platform**: Base44 SDK v0.8.4
- **LLM Integration**: Base44 InvokeLLM (abstracted LLM provider)
- **Language**: TypeScript
- **Deployment**: Serverless functions on Base44 infrastructure

### Common Patterns

All agents follow this execution pattern:

```typescript
1. Request Authentication (Base44 Auth)
2. Input Validation (validateRequired, validateEnum)
3. Data Fetching (parallel where possible)
4. Authorization Check (enforceOwnership)
5. Input Sanitization (filterSensitiveForLLM, sanitiseString)
6. Audit Logging (auditLog)
7. CoT Reasoning Execution (executeAdvancedCoTReasoning)
8. Output Validation (validateCoTOutput)
9. Metrics & Logging (logger.metric)
10. Response Generation (createSuccessResponse)
```

---

## Core Agent Framework

### Chain-of-Thought (CoT) System

Every agent uses a 5-stage Chain-of-Thought reasoning process:

#### Stage 1: Input Gathering
- Collect and structure all relevant data
- Identify context and constraints
- List all available resources

#### Stage 2: Contextual Analysis
- Understand relationships and dependencies
- Assess current state vs. desired state
- Identify patterns and anti-patterns

#### Stage 3: Problem Identification
- Discover issues, gaps, and risks
- Prioritize by severity and impact
- Consider edge cases

#### Stage 4: Recommendation Generation
- Propose actionable solutions
- Provide rationale for each recommendation
- Include implementation steps

#### Stage 5: Output Formatting
- Structure results according to schema
- Include confidence scores
- Provide reasoning transparency

### Utilities Framework

All agents share a common utilities library (`functions/lib/utils.ts`):

#### Security Utilities
- `sanitiseString()`: Clean and limit string inputs
- `sanitiseLLMInput()`: Prepare prompts for LLM
- `filterSensitiveForLLM()`: Remove sensitive data before LLM calls
- `enforceOwnership()`: RBAC ownership validation

#### Validation Utilities
- `validateRequired()`: Check required fields
- `validateEnum()`: Validate enum values
- `validateCoTOutput()`: Validate CoT reasoning output

#### Logging & Monitoring
- `createLogger()`: Structured logging with correlation IDs
- `generateCorrelationId()`: Unique request tracking
- `auditLog()`: Security audit trail

#### Response Formatting
- `createSuccessResponse()`: Standardized success format
- `createErrorResponse()`: Standardized error format
- `ErrorCodes`: Enumerated error codes

#### Advanced CoT
- `executeAdvancedCoTReasoning()`: Orchestrates 5-stage reasoning
- `buildCoTPrompt()`: Constructs explicit stage prompts
- `CoTStages`: Enumeration of reasoning stages

---

## Individual Agents

### 1. Architecture Analysis Agent

**File**: `functions/analyzeArchitecture.ts`  
**Endpoint**: `/analyzeArchitecture`  
**Purpose**: Comprehensive microservices architecture analysis and health assessment

#### Input Schema
```typescript
{
  project_id: string (required)
}
```

#### Functionality

**What it does**:
- Analyzes microservices architecture health (0-100 score)
- Identifies bottlenecks and single points of failure
- Detects security vulnerabilities in architecture
- Finds scalability limitations
- Recommends missing essential services
- Provides confidence-scored recommendations

**How it works**:
1. Fetches project and all associated services
2. Prepares sanitized context (service names, categories, technologies)
3. Executes 5-stage CoT reasoning:
   - **Input Gathering**: Lists all services and tech stacks
   - **Contextual Analysis**: Assesses relationships and patterns
   - **Problem Identification**: Finds architectural issues
   - **Recommendation Generation**: Suggests improvements
   - **Output Formatting**: Structures findings with scores
4. Validates output against schema
5. Returns health score, bottlenecks, security concerns, scalability issues, and missing services

#### Output Schema
```typescript
{
  health_score: number (0-100),
  reasoning_steps: Array<{
    stage: string,
    findings: string[],
    confidence: number
  }>,
  bottlenecks: Array<{
    service: string,
    issue: string,
    severity: 'critical' | 'high' | 'medium' | 'low',
    recommendation: string
  }>,
  security_concerns: Array<{
    title: string,
    description: string,
    priority: string
  }>,
  scalability: string[],
  performance: string[],
  missing_services: Array<{
    name: string,
    purpose: string,
    priority: string
  }>,
  overall_confidence: number
}
```

#### Decision Logic

**Health Score Calculation**:
- Deduct points for each bottleneck (severity-weighted)
- Deduct for security concerns (priority-weighted)
- Deduct for missing critical services
- Add points for good patterns and best practices
- Base score: 100, minimum: 0

**Why this matters**:
- Provides objective architecture quality metric
- Prioritizes technical debt remediation
- Prevents production issues before they occur
- Guides architecture evolution decisions

---

### 2. Security Audit Agent

**File**: `functions/securityAudit.ts`  
**Endpoint**: `/securityAudit`  
**Purpose**: OWASP Top 10 compliance checking and comprehensive security analysis

#### Input Schema
```typescript
{
  project_id: string (required),
  audit_type?: 'full' | 'static' | 'dynamic' | 'dependencies' | 'compliance',
  compliance_standards?: Array<'SOC2' | 'ISO27001' | 'HIPAA' | 'PCI-DSS' | 'GDPR' | 'NIST'>,
  include_remediation?: boolean,
  severity_threshold?: 'critical' | 'high' | 'medium' | 'low'
}
```

#### Functionality

**What it does**:
- **Static Code Analysis**: Scans for OWASP Top 10 vulnerabilities
- **Dynamic Runtime Checks**: Authentication, authorization, session management
- **Dependency Scanning**: CVE detection, outdated packages
- **Compliance Assessment**: SOC2, ISO 27001, HIPAA, PCI-DSS, GDPR, NIST
- **Remediation Guidance**: Actionable fixes with code examples
- **Exploit Scenarios**: Demonstrates security impact

**How it works**:
1. Fetches comprehensive project context (services, CI/CD, APIs, existing findings, code samples)
2. Prepares sanitized security context
3. Executes specialized CoT for each audit type:
   - **Static**: Code pattern analysis for vulnerabilities
   - **Dynamic**: Runtime security checks
   - **Dependencies**: CVE database cross-reference
   - **Compliance**: Multi-standard checklist validation
4. Generates prioritized findings with severity scoring
5. Creates remediation plans with code examples
6. Saves findings to SecurityFinding entity

#### OWASP Top 10 Coverage

1. **A01:2021 - Broken Access Control**
   - Checks: RBAC implementation, ownership validation, privilege escalation
   
2. **A02:2021 - Cryptographic Failures**
   - Checks: Encryption at rest/transit, key management, algorithm strength
   
3. **A03:2021 - Injection**
   - Checks: Input sanitization, parameterized queries, validation
   
4. **A04:2021 - Insecure Design**
   - Checks: Architecture patterns, threat modeling, security controls
   
5. **A05:2021 - Security Misconfiguration**
   - Checks: Default configs, unnecessary features, security headers
   
6. **A06:2021 - Vulnerable and Outdated Components**
   - Checks: Dependency versions, CVE presence, patch availability
   
7. **A07:2021 - Identification and Authentication Failures**
   - Checks: Password policies, MFA, session management, brute force protection
   
8. **A08:2021 - Software and Data Integrity Failures**
   - Checks: CI/CD security, unsigned packages, integrity validation
   
9. **A09:2021 - Security Logging and Monitoring Failures**
   - Checks: Audit logging, alerting, log retention, tampering detection
   
10. **A10:2021 - Server-Side Request Forgery (SSRF)**
    - Checks: URL validation, network segmentation, allowlists

#### Output Schema
```typescript
{
  audit_id: string,
  project_id: string,
  audit_type: string,
  overall_score: number (0-100),
  findings: Array<{
    id: string,
    severity: 'critical' | 'high' | 'medium' | 'low',
    category: string (OWASP category),
    title: string,
    description: string,
    affected_services: string[],
    exploit_scenario: string,
    remediation: {
      description: string,
      code_example: string,
      effort: 'low' | 'medium' | 'high',
      priority: number
    }
  }>,
  compliance_results: {
    [standard: string]: {
      passed: number,
      failed: number,
      percentage: number,
      requirements: Array<{
        id: string,
        description: string,
        status: 'pass' | 'fail' | 'warning',
        evidence: string
      }>
    }
  }
}
```

#### Decision Logic

**Severity Calculation**:
- **Critical**: Exploitable remotely, high impact, low complexity
- **High**: Exploitable, moderate impact or complexity
- **Medium**: Difficult to exploit or limited impact
- **Low**: Minimal risk, best practice violation

**Compliance Scoring**:
- Each standard has weighted requirements
- Must pass critical requirements for certification
- Percentage score = (passed / total) * 100

---

### 3. Code Generation Agent

**File**: `functions/generateCode.ts`  
**Endpoint**: `/generateCode`  
**Purpose**: Production-ready microservice scaffolding with tests and deployment configs

#### Input Schema
```typescript
{
  service_id: string (required),
  language?: 'typescript' | 'python' | 'go' | 'java' | 'rust',
  framework?: string, // e.g., 'express', 'fastapi', 'gin', 'spring-boot'
  include_tests?: boolean (default: true),
  include_docker?: boolean (default: true),
  include_api?: boolean (default: true),
  architecture_pattern?: 'microservices' | 'monolith' | 'serverless'
}
```

#### Functionality

**What it does**:
- Generates complete microservice project structure
- Creates API endpoints based on service definition
- Generates database models and schemas
- Scaffolds unit and integration tests
- Produces Dockerfile and docker-compose.yml
- Creates CI/CD pipeline configurations
- Generates comprehensive README and API documentation

**How it works**:
1. Fetches service details and parent project context
2. Prepares safe code generation context
3. Executes CoT reasoning:
   - **Input Gathering**: Service requirements, APIs, technologies
   - **Contextual Analysis**: Best practices for language/framework
   - **Problem Identification**: Edge cases, error handling needs
   - **Recommendation Generation**: File structure, dependencies
   - **Output Formatting**: Complete codebase with docs
4. Validates generated code structure
5. Saves CodeGeneration entity for future reference

#### Generated File Types

**Source Files**:
- Main application entry point
- API route handlers
- Business logic/services
- Data models
- Middleware (auth, logging, error handling)
- Configuration management

**Test Files**:
- Unit tests for each module
- Integration tests for APIs
- Test fixtures and mocks
- Test utilities

**Configuration Files**:
- Package manager config (package.json, requirements.txt, go.mod)
- Environment variable templates (.env.example)
- Linter/formatter configs
- TypeScript/build configs

**Docker Files**:
- Multi-stage Dockerfile
- docker-compose.yml with dependencies
- .dockerignore

**Documentation**:
- README.md with setup instructions
- API documentation (Swagger/OpenAPI)
- Architecture decision records

#### Output Schema
```typescript
{
  files: Array<{
    path: string,
    content: string,
    description: string,
    type: 'source' | 'test' | 'config' | 'docker' | 'docs'
  }>,
  project_structure: string, // ASCII tree
  dependencies: {
    production: string[],
    development: string[]
  },
  setup_commands: string[], // Install and run instructions
  api_documentation: string, // Markdown API docs
  test_coverage_target: number // Expected coverage percentage
}
```

#### Decision Logic

**Language-Specific Patterns**:
- **TypeScript/Node.js**: Express, Fastify, NestJS patterns
- **Python**: FastAPI, Flask, Django patterns
- **Go**: Gin, Echo, Chi patterns
- **Java**: Spring Boot, Micronaut patterns

**Best Practices Enforced**:
- Dependency injection
- Environment-based configuration
- Structured logging
- Error handling middleware
- Input validation
- API versioning
- CORS and security headers
- Health check endpoints
- Graceful shutdown

---

### 4. CI/CD Pipeline Agent

**File**: `functions/generateCICD.ts`  
**Endpoint**: `/generateCICD`  
**Purpose**: Generate production-grade CI/CD pipeline configurations

#### Input Schema
```typescript
{
  project_id: string (required),
  platform: 'github-actions' | 'gitlab-ci' | 'jenkins' | 'circleci',
  include_security_scanning?: boolean (default: true),
  include_deployment?: boolean (default: true),
  deployment_target?: 'kubernetes' | 'docker-swarm' | 'aws' | 'azure' | 'gcp'
}
```

#### Functionality

**What it does**:
- Generates multi-stage CI/CD pipelines
- Includes lint, test, build, scan, deploy stages
- Configures security scanning (SAST, dependency scan, container scan)
- Sets up deployment automation
- Creates environment-specific configurations
- Adds secret management
- Implements rollback strategies

**Pipeline Stages**:
1. **Lint**: Code quality checks
2. **Test**: Unit and integration tests
3. **Build**: Compile and package
4. **Security Scan**: SAST, dependencies, secrets
5. **Container Build**: Docker image creation
6. **Deploy**: Environment-specific deployment
7. **Smoke Test**: Post-deployment validation

#### Output Schema
```typescript
{
  platform: string,
  config_files: Array<{
    filename: string,
    content: string,
    description: string
  }>,
  environment_variables: Array<{
    key: string,
    description: string,
    required: boolean,
    secret: boolean
  }>,
  setup_instructions: string
}
```

---

### 5. Documentation Agent

**File**: `functions/generateDocumentation.ts`  
**Endpoint**: `/generateDocumentation`  
**Purpose**: Automated, comprehensive project documentation generation

#### Input Schema
```typescript
{
  project_id: string (required),
  doc_type: 'api' | 'architecture' | 'deployment' | 'status-report' | 'all',
  format?: 'markdown' | 'html' | 'pdf'
}
```

#### Functionality

**What it does**:
- Generates API documentation (OpenAPI/Swagger)
- Creates architecture documentation with diagrams
- Produces deployment guides
- Compiles status reports
- Generates README files
- Creates architecture decision records (ADRs)

#### Documentation Types

**API Documentation**:
- Endpoint specifications
- Request/response schemas
- Authentication requirements
- Error codes
- Rate limits
- Example requests

**Architecture Documentation**:
- System overview
- Service catalog
- Dependency maps
- Data flow diagrams
- Technology stack
- Design decisions

**Deployment Guides**:
- Prerequisites
- Step-by-step deployment
- Configuration instructions
- Troubleshooting
- Rollback procedures

#### Output Schema
```typescript
{
  document_id: string,
  title: string,
  content: string,
  format: string,
  metadata: {
    generated_at: string,
    version: string,
    services_documented: number
  }
}
```

---

### 6. Health Check Agent

**File**: `functions/projectHealthCheck.ts`  
**Endpoint**: `/projectHealthCheck`  
**Purpose**: Continuous project health monitoring and scoring

#### Input Schema
```typescript
{
  project_id: string (required)
}
```

#### Functionality

**What it does**:
- Calculates overall project health score (0-100)
- Monitors service availability
- Tracks technical debt
- Identifies stale components
- Measures test coverage
- Assesses documentation completeness

#### Health Metrics

**Service Health** (30%):
- All services have descriptions
- Technology stacks defined
- APIs documented
- Dependencies mapped

**Security Health** (25%):
- Recent security audit
- No critical vulnerabilities
- Compliance standards met
- Security scanning enabled

**Testing Health** (20%):
- Test coverage > 80%
- Tests passing
- Integration tests present

**Documentation Health** (15%):
- README exists
- API docs current
- Architecture documented

**CI/CD Health** (10%):
- Pipeline configured
- Deployments successful
- Security scans passing

#### Output Schema
```typescript
{
  health_score: number,
  metrics: {
    services: { score: number, details: object },
    security: { score: number, details: object },
    testing: { score: number, details: object },
    documentation: { score: number, details: object },
    cicd: { score: number, details: object }
  },
  recommendations: Array<{
    priority: string,
    action: string,
    impact: number
  }>
}
```

---

### 7. Security Scan Agent

**File**: `functions/securityScan.ts`  
**Endpoint**: `/securityScan`  
**Purpose**: Rapid vulnerability scanning and threat detection

#### Input Schema
```typescript
{
  project_id: string (required),
  scan_type: 'quick' | 'deep',
  target?: 'services' | 'dependencies' | 'infrastructure' | 'all'
}
```

#### Functionality

**What it does**:
- Quick vulnerability scans
- Dependency CVE checking
- Infrastructure misconfiguration detection
- Secret exposure detection
- License compliance checking

**Scan Types**:
- **Quick**: Fast scan of critical areas (< 30 seconds)
- **Deep**: Comprehensive scan (2-5 minutes)

#### Output Schema
```typescript
{
  scan_id: string,
  vulnerabilities_found: number,
  critical_count: number,
  high_count: number,
  medium_count: number,
  low_count: number,
  findings: Array<{
    id: string,
    severity: string,
    type: string,
    description: string,
    remediation: string
  }>
}
```

---

### 8. API Gateway Agent

**File**: `functions/apiGateway.ts`  
**Endpoint**: `/apiGateway`  
**Purpose**: API management, routing, and integration orchestration

#### Functionality

**What it does**:
- Manages API integrations
- Routes requests to services
- Handles authentication
- Implements rate limiting
- Provides API analytics

---

### 9. Export Agent

**File**: `functions/exportProject.ts`  
**Endpoint**: `/exportProject`  
**Purpose**: Project export in multiple formats

#### Input Schema
```typescript
{
  project_id: string (required),
  format: 'json' | 'yaml' | 'zip' | 'terraform',
  include_code?: boolean,
  include_docs?: boolean
}
```

#### Functionality

**What it does**:
- Exports complete project definition
- Includes architecture, services, configurations
- Generates Infrastructure as Code (Terraform, CloudFormation)
- Creates importable archives
- Supports project migration

---

### 10. Notification Agent

**File**: `functions/sendNotification.ts`  
**Endpoint**: `/sendNotification`  
**Purpose**: Multi-channel notification delivery

#### Input Schema
```typescript
{
  user_id: string (required),
  channel: 'email' | 'whatsapp' | 'slack' | 'webhook',
  type: 'info' | 'warning' | 'error' | 'success',
  title: string,
  message: string,
  metadata?: object
}
```

#### Functionality

**What it does**:
- Sends notifications across multiple channels
- Supports Email, WhatsApp, Slack, webhooks
- Templates for common notification types
- Respects user notification preferences
- Includes retry logic for failed deliveries

---

## Chain-of-Thought (CoT) Framework

### CoT Philosophy

Chain-of-Thought reasoning makes AI decisions transparent, debuggable, and more accurate by breaking complex tasks into explicit stages.

### Implementation

All agents use `executeAdvancedCoTReasoning()` from utils:

```typescript
const result = await executeAdvancedCoTReasoning({
  task: 'task_name',
  context: { /* sanitized data */ },
  logger: logger,
  outputSchema: VALIDATION_SCHEMA,
  executor: async (ctx) => {
    // LLM invocation with explicit CoT prompt
  },
  validator: (result) => {
    // Business logic validation
  }
});
```

### CoT Stages

**Stage 1: Input Gathering**
- Lists all data points
- Identifies constraints
- Notes missing information

**Stage 2: Contextual Analysis**
- Analyzes relationships
- Considers best practices
- Evaluates patterns

**Stage 3: Problem Identification**
- Discovers issues
- Prioritizes problems
- Considers edge cases

**Stage 4: Recommendation Generation**
- Proposes solutions
- Provides rationale
- Includes implementation steps

**Stage 5: Output Formatting**
- Structures according to schema
- Adds confidence scores
- Includes reasoning trail

### Validation

Every CoT output is validated:
- **Schema Validation**: Required fields present and correctly typed
- **Business Logic Validation**: Values within acceptable ranges
- **Consistency Checks**: No contradictions in reasoning
- **Confidence Scoring**: Outputs confidence levels (0-1)

---

## Security & Compliance

### Input Security

**Sanitization**:
- `sanitiseString()`: Removes control characters, limits length
- `sanitiseLLMInput()`: Prepares safe prompts for LLM
- `filterSensitiveForLLM()`: Removes PII, secrets, sensitive data

**Validation**:
- Required field checking
- Enum validation
- Type checking
- Range validation

### Authentication & Authorization

**Authentication**:
- All endpoints require Base44 authentication
- JWT tokens validated on every request
- User identity attached to all operations

**Authorization**:
- RBAC enforcement with `enforceOwnership()`
- Project-level access control
- Operation-level permissions

### Audit Logging

Every agent operation is logged:
- User identity
- Operation type
- Resource accessed
- Timestamp
- Correlation ID for tracing

### Data Privacy

**LLM Data Handling**:
- Never send PII to LLM
- Filter sensitive fields before prompts
- Use sanitized, generic identifiers
- Log all LLM interactions

**Data Retention**:
- Audit logs retained for compliance
- Sensitive data encrypted at rest
- PII minimization principles

---

## Best Practices

### For Agent Development

1. **Always use CoT**: Never skip the 5-stage reasoning
2. **Validate everything**: Input, process, output
3. **Sanitize for LLM**: Never trust raw user input in prompts
4. **Log comprehensively**: Use structured logging with correlation IDs
5. **Handle errors gracefully**: Return standardized error responses
6. **Enforce RBAC**: Check ownership before operations
7. **Audit security operations**: Log all security-sensitive actions
8. **Provide confidence scores**: Be transparent about AI certainty
9. **Test extensively**: Unit tests, integration tests, security tests
10. **Document decisions**: Explain complex logic and trade-offs

### For Agent Usage

1. **Check authentication**: Ensure user is authenticated
2. **Validate inputs**: Use TypeScript types and runtime validation
3. **Handle errors**: Expect and handle ErrorCodes
4. **Monitor performance**: Track execution time metrics
5. **Review reasoning**: Examine CoT stages for transparency
6. **Trust but verify**: Review AI recommendations before applying
7. **Iterate on failures**: Use validation issues to improve prompts
8. **Respect rate limits**: Don't overwhelm LLM endpoints
9. **Cache when possible**: Reduce redundant LLM calls
10. **Provide feedback**: Report issues to improve agent quality

---

## Metrics & Monitoring

### Performance Metrics

Each agent tracks:
- **Execution Time**: Total time to complete
- **LLM Latency**: Time spent in LLM calls
- **Data Fetch Time**: Time to retrieve data
- **Validation Time**: Time to validate outputs

### Quality Metrics

- **Confidence Scores**: AI certainty in recommendations
- **Validation Pass Rate**: Percentage of valid outputs
- **User Acceptance**: How often users accept recommendations
- **Error Rate**: Frequency of errors

### Health Monitoring

- **Uptime**: Agent availability
- **Error Types**: Categorized error tracking
- **Rate Limiting**: Request throttling
- **Cost Tracking**: LLM token usage

---

## Troubleshooting

### Common Issues

**"Authentication required"**
- Ensure valid Base44 auth token in request
- Check token expiration

**"Project not found"**
- Verify project_id exists
- Check user has access to project

**"Validation failed"**
- Review required fields in input schema
- Check data types match expected

**"LLM invocation failed"**
- Check LLM rate limits
- Verify prompt isn't too long
- Review LLM error messages

**"Ownership validation failed"**
- User doesn't own the resource
- Check RBAC permissions

### Debugging

**Enable verbose logging**:
```typescript
logger.info('Debug message', { detailed_context });
```

**Check correlation ID**:
- All logs include correlation_id
- Trace entire request flow

**Review CoT stages**:
- Examine reasoning_steps in response
- Identify where logic diverged

**Validate schemas**:
- Ensure output matches expected schema
- Check validation_issues in response

---

## Future Enhancements

### Planned Features

1. **Multi-Agent Orchestration**: Agents collaborate on complex tasks
2. **Agent Marketplace**: Community-contributed specialized agents
3. **Custom Agent Creation**: Visual agent builder
4. **Agent Analytics**: Performance dashboards
5. **Predictive Agents**: ML-based forecasting
6. **Conversational Agents**: Natural language interaction
7. **Agent Chaining**: Sequential agent execution
8. **Parallel Execution**: Run multiple agents concurrently
9. **Agent Versioning**: A/B test agent improvements
10. **Self-Improving Agents**: Learn from feedback

---

## Contributing

To add a new agent:

1. Create new TypeScript file in `functions/`
2. Import utilities from `functions/lib/utils.ts`
3. Implement 5-stage CoT reasoning
4. Add input/output schemas
5. Include comprehensive validation
6. Add error handling
7. Write unit tests
8. Document in this file
9. Add to API documentation
10. Submit pull request

---

## Support

For agent-related issues:
- **GitHub Issues**: [archdesigner/issues](https://github.com/Krosebrook/archdesigner/issues)
- **Documentation**: [README.md](./README.md)
- **API Reference**: [API_DOCS.md](./API_DOCS.md)

---

**Maintained by**: Krosebrook Team  
**License**: See LICENSE file  
**Version**: 0.0.0  
**Last Updated**: December 29, 2024