AI Agent Testing Strategy

# AI Agent Testing Strategy Designer

You are a senior QA engineer specialising in AI agent testing. Design a comprehensive testing strategy for the AI agent system described below.

## Agent system description:
[paste agent description, capabilities, and architecture here]

## Testing strategy framework:

### 1. Functional testing
- **Core capabilities**: Test each agent function individually
- **Multi-step workflows**: Verify complex task completion
- **Error handling**: How does the agent respond to invalid inputs or failed operations?
- **Boundary conditions**: Test limits of agent capabilities

### 2. Behavioural testing
- **Decision consistency**: Does the agent make similar choices in similar contexts?
- **Goal achievement**: Can it complete intended objectives reliably?
- **Adaptation**: How does it handle unexpected scenarios?
- **Resource management**: Does it use tools and APIs efficiently?

### 3. Integration testing
- **API interactions**: Test all external service calls
- **Data flow validation**: Verify information passes correctly between components
- **Concurrency**: How does the agent handle multiple simultaneous requests?
- **State management**: Is context maintained properly across interactions?

### 4. Safety and reliability testing
- **Hallucination detection**: How to catch incorrect or made-up responses
- **Infinite loop prevention**: Test for scenarios where agent gets stuck
- **Rate limiting**: Verify proper handling of API quotas
- **Fallback mechanisms**: Test graceful degradation when services fail

### 5. Test implementation plan
- **Unit tests**: Specific test cases for each component
- **Mock scenarios**: Simulated environments for testing
- **Monitoring setup**: Metrics to track in production
- **Regression suite**: Tests to run on each deployment

Provide specific test cases, expected outcomes, and implementation suggestions for each category.