# LLM/Agent MCP Workflow Test Strategies
## 📋 Table of Contents
1. [Overview](#overview)
2. [Test Strategy Architecture](#test-strategy-architecture)
3. [Deterministic Validation Tests](#deterministic-validation-tests)
4. [Stochastic Validation Tests](#stochastic-validation-tests)
5. [Safety Guardrails & Red-Teaming](#safety-guardrails--red-teaming)
6. [Data Privacy & PII Protection](#data-privacy--pii-protection)
7. [Model Evaluation Suites](#model-evaluation-suites)
8. [Production Monitoring](#production-monitoring)
9. [Implementation Guide](#implementation-guide)
10. [Best Practices](#best-practices)
---
## Overview
This document outlines comprehensive test strategies for LLM/agent MCP (Model Context Protocol) workflows in the Zebrunner integration. Our testing approach covers deterministic and stochastic validations, safety guardrails, data privacy protection, and model evaluation metrics to ensure robust, secure, and high-quality AI-powered test management.
### Key Testing Objectives
- **Reliability**: Ensure consistent, predictable behavior across all MCP tools
- **Security**: Validate input sanitization, authentication, and authorization
- **Privacy**: Protect PII and ensure GDPR/CCPA compliance
- **Performance**: Monitor quality, latency, and cost metrics
- **Safety**: Implement guardrails against malicious inputs and edge cases
---
## Test Strategy Architecture
### Testing Pyramid Structure
```
🔺 Production Monitoring
🔺🔺 Model Evaluation Suites
🔺🔺🔺 Safety & Security Tests
🔺🔺🔺🔺 Stochastic Validation Tests
🔺🔺🔺🔺🔺 Deterministic Validation Tests
```
### Test Categories
| Category | Purpose | Scope | Frequency |
|----------|---------|-------|-----------|
| **Deterministic** | Validate predictable behaviors | Input validation, response formats | Every commit |
| **Stochastic** | Test probabilistic behaviors | Performance, retry mechanisms | Daily |
| **Safety** | Security and guardrail testing | Input sanitization, auth bypass | Weekly |
| **Privacy** | PII protection and compliance | Data masking, consent flows | Weekly |
| **Evaluation** | Quality and performance metrics | Response quality, latency, cost | Continuous |
| **Monitoring** | Production health and alerts | System health, business metrics | Real-time |
---
## Deterministic Validation Tests
### Purpose
Validate predictable, repeatable behaviors in MCP workflows to ensure consistency and reliability.
### Test Coverage
#### 1. Tool Parameter Validation
```typescript
// Example: Project Key Format Validation
const validProjectKeys = ['MCP', 'ANDROID', 'IOS', 'WEB123', 'API2024'];
const invalidProjectKeys = ['mcp', 'android-test', '123', '', 'test-case'];
// Validation Rule: /^[A-Z][A-Z0-9]*$/
```
#### 2. Response Format Consistency
- **JSON Structure**: Consistent field names and types
- **Pagination Metadata**: Standard format across all endpoints
- **Error Response Format**: Uniform error structure
#### 3. Data Transformation Accuracy
- **Type Preservation**: Ensure data types remain consistent
- **Null Handling**: Proper handling of null/undefined values
- **Field Mapping**: Accurate transformation between API and MCP formats
### Key Test Cases
| Test Case | Validation | Expected Result |
|-----------|------------|-----------------|
| Project Key Format | `/^[A-Z][A-Z0-9]*$/` | Accept: 'MCP', Reject: 'mcp' |
| Test Case Key Format | `/^[A-Z]+-\d+$/` | Accept: 'MCP-1', Reject: 'mcp-1' |
| Pagination Parameters | `page >= 0, size 1-200` | Valid ranges only |
| Response Structure | Required fields present | All expected fields exist |
---
## Stochastic Validation Tests
### Purpose
Validate probabilistic behaviors and edge cases under varying conditions.
### Test Coverage
#### 1. Performance Under Load
```typescript
// Concurrent Request Testing
const concurrentRequests = 5;
const successRate = successful / total;
// Target: >= 80% success rate
```
#### 2. Retry Mechanisms
- **Exponential Backoff**: Validate increasing delays
- **Max Retry Limits**: Ensure proper failure handling
- **Circuit Breaker**: Test failure threshold behavior
#### 3. Timeout Handling
- **Request Timeouts**: Graceful handling of slow responses
- **Connection Timeouts**: Network failure recovery
- **Meaningful Error Messages**: Clear timeout communication
#### 4. Network Failure Recovery
- **Intermittent Failures**: Handle temporary network issues
- **Rate Limiting**: Proper backoff on rate limits
- **Service Degradation**: Graceful degradation strategies
### Performance Baselines
| Metric | Baseline | Tolerance |
|--------|----------|-----------|
| Response Time | 2000ms | ±500ms |
| Throughput | 100 req/min | ±20% |
| Error Rate | 1% | ±0.5% |
| Success Rate | 95% | ±5% |
---
## Safety Guardrails & Red-Teaming
### Purpose
Validate security measures and resistance to malicious attacks.
### Test Coverage
#### 1. Input Sanitization
```typescript
// SQL Injection Prevention
const sqlInjectionAttempts = [
"'; DROP TABLE test_cases; --",
"' OR '1'='1",
"'; SELECT * FROM users; --"
];
// XSS Prevention
const xssAttempts = [
"<script>alert('XSS')</script>",
"javascript:alert('XSS')",
"<img src=x onerror=alert('XSS')>"
];
```
#### 2. Authentication Security
- **Invalid Token Rejection**: Reject malformed/invalid tokens
- **Authorization Header Validation**: Proper Basic auth format
- **Bypass Attempt Prevention**: Detect and block bypass attempts
#### 3. Authorization Checks
- **Project-Level Access**: Enforce project boundaries
- **Privilege Escalation Prevention**: Block unauthorized actions
- **Read-Only Enforcement**: Ensure MCP remains read-only
#### 4. Rate Limiting
- **Burst Protection**: Enforce burst limits
- **Progressive Limiting**: Increase delays with abuse
- **Fair Usage**: Prevent resource monopolization
### Security Test Matrix
| Attack Vector | Test Method | Expected Defense |
|---------------|-------------|------------------|
| SQL Injection | Malicious SQL in inputs | Input validation rejection |
| XSS Attacks | Script injection attempts | HTML sanitization |
| Auth Bypass | Invalid credentials | Authentication failure |
| Path Traversal | Directory traversal attempts | Path validation |
| Rate Abuse | Rapid request bursts | Rate limiting activation |
---
## Data Privacy & PII Protection
### Purpose
Ensure comprehensive protection of personally identifiable information and compliance with privacy regulations.
### Test Coverage
#### 1. PII Detection & Masking
```typescript
// Email Masking
const maskEmail = (email: string) => {
const [local, domain] = email.split('@');
return `${local[0]}${'*'.repeat(local.length-2)}${local[local.length-1]}@${domain}`;
};
// Phone Number Masking
const maskPhone = (phone: string) => {
return phone.replace(/\d/g, (digit, index) =>
index < phone.length - 4 ? '*' : digit
);
};
```
#### 2. Data Retention Policies
- **Retention Periods**: Enforce data lifecycle management
- **Automated Purging**: Schedule-based data cleanup
- **Legal Hold Exceptions**: Handle litigation holds
#### 3. Access Control Enforcement
- **Role-Based Access Control (RBAC)**: Validate role permissions
- **Attribute-Based Access Control (ABAC)**: Context-aware access
- **Audit Logging**: Track all access attempts
#### 4. Consent Management
- **Consent Tracking**: Record user consent decisions
- **Consent Withdrawal**: Handle opt-out requests
- **Purpose Limitation**: Validate data usage against consent
#### 5. GDPR/CCPA Compliance
- **Data Subject Rights**: Right to access, rectify, erase, portability
- **Privacy by Design**: Built-in privacy protections
- **Cross-Border Transfers**: Validate transfer mechanisms
### Privacy Protection Matrix
| PII Type | Detection Pattern | Masking Strategy | Retention Policy |
|----------|-------------------|------------------|------------------|
| Email | `/\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z\|a-z]{2,}\b/g` | `u***r@domain.com` | 7 years |
| Phone | `/(\+?1?[-.\s]?)?\(?([0-9]{3})\)?[-.\s]?([0-9]{3})[-.\s]?([0-9]{4})/g` | `***-***-1234` | 3 years |
| SSN | `/\b\d{3}[-\s]?\d{2}[-\s]?\d{4}\b/g` | `***-**-1234` | 10 years |
| Credit Card | `/\b\d{4}[-\s]?\d{4}[-\s]?\d{4}[-\s]?\d{4}\b/g` | `****-****-****-1234` | 1 year |
---
## Model Evaluation Suites
### Purpose
Comprehensive evaluation of model quality, performance, and cost metrics.
### Test Coverage
#### 1. Quality Metrics
```typescript
// Quality Baseline Targets
const qualityBaseline = {
accuracy: 0.95, // 95% correct responses
completeness: 0.90, // 90% complete data
relevance: 0.85, // 85% relevant results
consistency: 0.95, // 95% consistent responses
userSatisfaction: 0.80 // 80% user satisfaction
};
```
#### 2. Performance Metrics
```typescript
// Performance Baseline Targets
const performanceBaseline = {
responseTime: 2000, // 2 seconds max
throughput: 100, // 100 requests/minute
errorRate: 0.01, // 1% error rate
cpuUsage: 0.7, // 70% CPU utilization
memoryUsage: 0.8, // 80% memory utilization
cost: 0.001 // $0.001 per request
};
```
#### 3. Scalability Testing
- **Load Testing**: Performance under increasing load
- **Stress Testing**: Breaking point identification
- **Volume Testing**: Large data set handling
- **Endurance Testing**: Long-running stability
#### 4. Cost Optimization
- **Cost Per Request**: Track operational costs
- **Resource Efficiency**: Optimize resource allocation
- **Cost Trends**: Monitor cost changes over time
### Evaluation Metrics Dashboard
| Metric Category | Key Indicators | Target Values | Monitoring Frequency |
|-----------------|----------------|---------------|---------------------|
| **Quality** | Accuracy, Completeness, Relevance | >90% | Hourly |
| **Performance** | Response Time, Throughput, Error Rate | <2s, >100/min, <1% | Real-time |
| **Cost** | Cost/Request, Resource Efficiency | <$0.001, >75% | Daily |
| **Scalability** | Load Capacity, Degradation Point | 500 concurrent, >200 load | Weekly |
---
## Production Monitoring
### Purpose
Continuous monitoring of system health, performance, and business metrics in production.
### Monitoring Categories
#### 1. Health Check Monitoring
```typescript
const healthChecks = {
database: { status: 'healthy', responseTime: 50 },
api: { status: 'healthy', responseTime: 200 },
cache: { status: 'healthy', responseTime: 10 },
externalServices: { status: 'degraded', responseTime: 5000 }
};
```
#### 2. Performance Monitoring
- **Key Performance Indicators (KPIs)**
- **Distributed Tracing**
- **Application Performance Monitoring (APM)**
- **Real User Monitoring (RUM)**
#### 3. Business Metrics Monitoring
- **Test Cases Created/Validated**
- **User Engagement Metrics**
- **API Usage Patterns**
- **Data Quality Scores**
#### 4. Alert Configuration
```typescript
const alertThresholds = {
responseTime: { warning: 2000, critical: 5000 },
errorRate: { warning: 0.05, critical: 0.10 },
cpuUsage: { warning: 0.80, critical: 0.95 },
memoryUsage: { warning: 0.85, critical: 0.95 }
};
```
### SLA Monitoring
| SLA Metric | Target | Measurement | Alert Threshold |
|------------|--------|-------------|-----------------|
| Availability | 99.9% | Uptime monitoring | <99.5% |
| Response Time | <2s | P95 response time | >3s |
| Error Rate | <1% | Error percentage | >2% |
| Throughput | >100 req/min | Request rate | <80 req/min |
---
## Implementation Guide
### 1. Test Environment Setup
#### Prerequisites
```bash
# Install dependencies
npm install
# Set up environment variables
cp .env.example .env
# Configure ZEBRUNNER_URL, ZEBRUNNER_LOGIN, ZEBRUNNER_TOKEN
```
#### Test Structure
```
tests/
├── llm-agent/
│ ├── deterministic-workflow-tests.ts
│ └── stochastic-workflow-tests.ts
├── security/
│ ├── safety-guardrails.test.ts
│ └── data-privacy-tests.ts
├── evaluation/
│ └── model-evaluation-suite.ts
├── monitoring/
│ └── production-monitoring.ts
└── helpers/
└── credentials.ts
```
### 2. Running Tests
#### Individual Test Suites
```bash
# Deterministic tests
npm run test:deterministic
# Stochastic tests
npm run test:stochastic
# Security tests
npm run test:security
# Privacy tests
npm run test:privacy
# Evaluation tests
npm run test:evaluation
# Monitoring tests
npm run test:monitoring
```
#### Complete Test Suite
```bash
# Run all LLM/Agent workflow tests
npm run test:llm-workflows
# Run with coverage
npm run test:llm-workflows -- --coverage
# Run in watch mode
npm run test:llm-workflows -- --watch
```
### 3. Test Configuration
#### Test Runner Configuration
```typescript
const testConfigs: Record<string, TestConfig> = {
deterministic: {
name: 'Deterministic Workflow Tests',
pattern: 'tests/llm-agent/deterministic-*.test.ts',
description: 'Predictable behavior validation',
requiresBuild: false,
requiresEnv: false
},
stochastic: {
name: 'Stochastic Workflow Tests',
pattern: 'tests/llm-agent/stochastic-*.test.ts',
description: 'Probabilistic behavior validation',
requiresBuild: false,
requiresEnv: true
},
security: {
name: 'Security & Safety Tests',
pattern: 'tests/security/**/*.test.ts',
description: 'Security guardrails and red-teaming',
requiresBuild: false,
requiresEnv: false
},
privacy: {
name: 'Data Privacy Tests',
pattern: 'tests/security/data-privacy-tests.ts',
description: 'PII protection and compliance',
requiresBuild: false,
requiresEnv: true
},
evaluation: {
name: 'Model Evaluation Suite',
pattern: 'tests/evaluation/**/*.test.ts',
description: 'Quality, latency, and cost evaluation',
requiresBuild: false,
requiresEnv: true
},
monitoring: {
name: 'Production Monitoring',
pattern: 'tests/monitoring/**/*.test.ts',
description: 'Health checks and monitoring validation',
requiresBuild: false,
requiresEnv: false
}
};
```
### 4. CI/CD Integration
#### GitHub Actions Workflow
```yaml
name: LLM/Agent MCP Workflow Tests
on:
push:
branches: [ main, develop ]
pull_request:
branches: [ main ]
schedule:
- cron: '0 2 * * *' # Daily at 2 AM
jobs:
deterministic-tests:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-node@v3
- run: npm ci
- run: npm run test:deterministic
stochastic-tests:
runs-on: ubuntu-latest
needs: deterministic-tests
steps:
- uses: actions/checkout@v3
- uses: actions/setup-node@v3
- run: npm ci
- run: npm run test:stochastic
env:
ZEBRUNNER_URL: ${{ secrets.ZEBRUNNER_URL }}
ZEBRUNNER_LOGIN: ${{ secrets.ZEBRUNNER_LOGIN }}
ZEBRUNNER_TOKEN: ${{ secrets.ZEBRUNNER_TOKEN }}
security-tests:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-node@v3
- run: npm ci
- run: npm run test:security
privacy-tests:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-node@v3
- run: npm ci
- run: npm run test:privacy
env:
ZEBRUNNER_URL: ${{ secrets.ZEBRUNNER_URL }}
ZEBRUNNER_LOGIN: ${{ secrets.ZEBRUNNER_LOGIN }}
ZEBRUNNER_TOKEN: ${{ secrets.ZEBRUNNER_TOKEN }}
evaluation-tests:
runs-on: ubuntu-latest
if: github.event_name == 'schedule'
steps:
- uses: actions/checkout@v3
- uses: actions/setup-node@v3
- run: npm ci
- run: npm run test:evaluation
env:
ZEBRUNNER_URL: ${{ secrets.ZEBRUNNER_URL }}
ZEBRUNNER_LOGIN: ${{ secrets.ZEBRUNNER_LOGIN }}
ZEBRUNNER_TOKEN: ${{ secrets.ZEBRUNNER_TOKEN }}
```
---
## Best Practices
### 1. Test Design Principles
#### FIRST Principles
- **Fast**: Tests should run quickly
- **Independent**: Tests should not depend on each other
- **Repeatable**: Tests should produce consistent results
- **Self-Validating**: Tests should have clear pass/fail criteria
- **Timely**: Tests should be written alongside code
#### Test Pyramid Guidelines
- **70% Unit Tests**: Fast, isolated component tests
- **20% Integration Tests**: API and service interaction tests
- **10% E2E Tests**: Full workflow validation
### 2. Security Testing Best Practices
#### Input Validation
- Test boundary conditions
- Validate all user inputs
- Use parameterized queries
- Implement proper encoding
#### Authentication & Authorization
- Test with invalid credentials
- Verify session management
- Check privilege escalation
- Audit access attempts
### 3. Privacy Testing Best Practices
#### PII Protection
- Identify all PII data flows
- Test masking algorithms
- Validate retention policies
- Verify consent mechanisms
#### Compliance Testing
- Test data subject rights
- Validate cross-border transfers
- Check privacy notices
- Audit data processing
### 4. Performance Testing Best Practices
#### Load Testing Strategy
- Start with baseline tests
- Gradually increase load
- Monitor resource utilization
- Identify breaking points
#### Monitoring Strategy
- Define clear SLAs
- Set appropriate thresholds
- Implement alerting
- Track trends over time
### 5. Continuous Improvement
#### Metrics Collection
- Collect comprehensive metrics
- Analyze trends and patterns
- Identify improvement opportunities
- Implement feedback loops
#### Test Maintenance
- Regularly review test coverage
- Update tests for new features
- Remove obsolete tests
- Refactor for maintainability
---
## Conclusion
This comprehensive test strategy ensures that your MCP Zebrunner integration maintains high standards for reliability, security, privacy, and performance. By implementing these test suites, you'll have:
- **Robust Validation**: Both deterministic and stochastic test coverage
- **Security Assurance**: Comprehensive safety guardrails and red-teaming
- **Privacy Protection**: Full PII protection and compliance validation
- **Quality Metrics**: Continuous evaluation of model performance
- **Production Readiness**: Real-time monitoring and alerting
The test strategy is designed to be:
- **Scalable**: Easy to extend with new test cases
- **Maintainable**: Clear structure and documentation
- **Automated**: Full CI/CD integration
- **Comprehensive**: Coverage of all critical aspects
Regular execution of these test suites will help maintain the highest standards of quality, security, and performance for your LLM/agent MCP workflows.