testing-patterns
Testing patterns for Vercel AI SDK including mock providers, streaming tests, tool calling tests, snapshot testing, and test coverage strategies. Use when implementing tests, creating test suites, mocking AI providers, or when user mentions testing, mocks, test coverage, AI testing, streaming tests, or tool testing.
When & Why to Use This Skill
This Claude skill provides a comprehensive framework for testing Vercel AI SDK applications, offering specialized patterns for mock providers, streaming responses, and tool-calling validation. It enables developers to build robust AI features by providing ready-to-use templates for unit, integration, and snapshot testing, ensuring high reliability and performance of AI-driven workflows.
Use Cases
- Case 1: Implementing mock language model providers to perform fast and cost-effective unit testing without making real API calls.
- Case 2: Validating the integrity of streaming responses and complex tool-calling sequences to ensure consistent agent behavior.
- Case 3: Setting up snapshot testing to monitor AI-generated outputs over time and prevent regressions in response quality.
- Case 4: Automating test coverage analysis for AI features to ensure critical paths like error handling and tool execution are fully verified.
| name | testing-patterns |
|---|---|
| description | Testing patterns for Vercel AI SDK including mock providers, streaming tests, tool calling tests, snapshot testing, and test coverage strategies. Use when implementing tests, creating test suites, mocking AI providers, or when user mentions testing, mocks, test coverage, AI testing, streaming tests, or tool testing. |
| allowed-tools | Read, Write, Bash, Grep, Glob |
Testing Patterns for Vercel AI SDK
Purpose: Provide comprehensive testing templates, mock providers, and testing strategies for Vercel AI SDK applications.
Activation Triggers:
- Writing tests for AI features
- Creating mock AI providers
- Testing streaming responses
- Testing tool calling functionality
- Implementing test coverage
- Snapshot testing for AI outputs
Key Resources:
templates/mock-provider.ts- Mock language model implementationtemplates/streaming-test.ts- Test streaming responsestemplates/tool-calling-test.ts- Test tool executiontemplates/snapshot-test.ts- Snapshot testing for outputsscripts/generate-test-suite.sh- Generate test scaffoldsscripts/run-coverage.sh- Run tests with coverageexamples/- Complete test suites for different features
Mock Provider Pattern
Template: templates/mock-provider.ts
import { createMockLanguageModelV1 } from 'ai/test'
const mockProvider = createMockLanguageModelV1({
doGenerate: async ({ prompt, mode }) => ({
text: 'Mocked response'
finishReason: 'stop'
usage: { promptTokens: 10, completionTokens: 20 }
})
doStream: async function* ({ prompt, mode }) {
yield { type: 'text-delta', textDelta: 'Mocked ' }
yield { type: 'text-delta', textDelta: 'streaming ' }
yield { type: 'text-delta', textDelta: 'response' }
yield {
type: 'finish'
finishReason: 'stop'
usage: { promptTokens: 10, completionTokens: 20 }
}
}
})
Testing Strategies
1. Unit Tests (Mock Providers)
Test AI functions without real API calls
2. Integration Tests (Real Providers)
Test with real providers in CI (with rate limits)
3. Snapshot Tests
Ensure consistent outputs over time
4. E2E Tests
Test complete user flows with mocks
Test Coverage Goals
- Core Functions: >90%
- Error Handling: >80%
- Tool Calling: 100%
- Streaming: >85%
Resources
Templates:
mock-provider.ts- Complete mock implementationstreaming-test.ts- Streaming test patternstool-calling-test.ts- Tool execution testssnapshot-test.ts- Snapshot testing setup
Scripts:
generate-test-suite.sh- Scaffold testsrun-coverage.sh- Run with coverage
Examples:
complete-test-suite.test.ts- Full test suite example
Testing Frameworks: Vitest, Jest, Node Test Runner SDK Version: Vercel AI SDK 5+ Coverage Tool: c8, nyc, or built-in coverage
Best Practice: Use mock providers for fast, reliable tests