Browser integration tests require Playwright browsers which aren't installed in the publish workflow. Exclude these tests to allow publishing while still running all unit tests. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Agentic Quality Engineering Fleet
V3 (Main) | V2 Documentation | Changelog | Contributors | Issues | Discussions
V3 brings Domain-Driven Design architecture, 12 bounded contexts, 51 specialized QE agents, TinyDancer intelligent model routing, ReasoningBank learning with Dream cycles, HNSW vector search, and deep integration with Claude Flow and Agentic Flow.
🏗️ DDD Architecture | 🧠 ReasoningBank + Dream Cycles | 🎯 TinyDancer Model Routing | 🔍 HNSW Vector Search | 👑 Queen Coordinator | 📊 O(log n) Coverage | 🔗 Claude Flow Integration | 🎯 12 Bounded Contexts | 📚 61 QE Skills
⚡ Quick Start
Install & Initialize
# Install globally
npm install -g agentic-qe
# Initialize your project
cd your-project
aqe init --wizard
# Or with auto-configuration
aqe init --auto
# Add MCP server to Claude Code (optional)
claude mcp add agentic-qe npx agentic-qe mcp
# Verify connection
claude mcp list
Use from Claude Code CLI
Ask Claude to use QE agents directly from your terminal:
# Generate comprehensive tests with learning
claude "Use qe-test-architect to create tests for src/services/user-service.ts with 95% coverage"
# Run full quality pipeline with Queen coordination
claude "Use qe-queen-coordinator to orchestrate: test generation, coverage analysis, security scan, and quality gate"
# Detect flaky tests with root cause analysis
claude "Use qe-flaky-hunter to analyze the last 100 test runs and stabilize flaky tests"
What V3 provides:
- ✅ 12 DDD Bounded Contexts: Organized by business domain (test-generation, coverage-analysis, security-compliance, etc.)
- ✅ 51 QE Agents: Including Queen Coordinator for hierarchical orchestration (44 main + 7 TDD subagents)
- ✅ TinyDancer Model Routing: 3-tier intelligent routing (Haiku/Sonnet/Opus) for cost optimization
- ✅ ReasoningBank Learning: HNSW-indexed pattern storage with experience replay
- ✅ O(log n) Coverage Analysis: Sublinear algorithms for efficient gap detection
- ✅ Claude Flow Integration: Deep integration with MCP tools and swarm orchestration
- ✅ Memory Coordination: Cross-agent communication via
aqe/v3/*namespaces - ✅ V2 Backward Compatibility: All V2 agents map to V3 equivalents
- ✅ 61 QE Skills: Domain-specific skills for testing, security, accessibility, and more
🎯 Why AQE?
| Problem | AQE Solution |
|---|---|
| Writing comprehensive tests is tedious and time-consuming | AI agents generate tests automatically with pattern reuse across projects |
| Test suites become slow and expensive at scale | Sublinear O(log n) algorithms for coverage analysis and intelligent test selection |
| Flaky tests waste developer time debugging false failures | ML-powered detection with root cause analysis and fix recommendations |
| AI testing tools are expensive | TinyDancer 3-tier model routing reduces costs by matching task complexity to appropriate model |
| No memory between test runs—every analysis starts from scratch | ReasoningBank remembers patterns, strategies, and what works for your codebase |
| Agents waste tokens reading irrelevant code | Code Intelligence provides token reduction with semantic search and knowledge graphs |
| Quality engineering requires complex coordination | Queen Coordinator orchestrates 51 agents across 12 domains with consensus and MinCut topology |
| Tools don't understand your testing frameworks | Works with Jest, Cypress, Playwright, Vitest, Mocha, Jasmine, AVA |
✨ V3 Features
🏗️ Domain-Driven Design Architecture
V3 is built on 12 DDD Bounded Contexts, each with dedicated agents and clear responsibilities:
| Domain | Purpose | Key Agents |
|---|---|---|
| test-generation | AI-powered test creation | qe-test-architect, qe-tdd-specialist |
| test-execution | Parallel execution & retry | qe-parallel-executor, qe-retry-handler |
| coverage-analysis | O(log n) gap detection | qe-coverage-specialist, qe-gap-detector |
| quality-assessment | Quality gates & decisions | qe-quality-gate, qe-risk-assessor |
| defect-intelligence | Prediction & root cause | qe-defect-predictor, qe-root-cause-analyzer |
| requirements-validation | BDD & testability | qe-requirements-validator, qe-bdd-generator |
| code-intelligence | Knowledge graph & search | qe-code-intelligence, qe-kg-builder |
| security-compliance | SAST/DAST & audit | qe-security-scanner, qe-security-auditor |
| contract-testing | API contracts & GraphQL | qe-contract-validator, qe-graphql-tester |
| visual-accessibility | Visual regression & a11y | qe-visual-tester, qe-accessibility-auditor |
| chaos-resilience | Chaos engineering & load | qe-chaos-engineer, qe-load-tester |
| learning-optimization | Cross-domain learning | qe-learning-coordinator, qe-pattern-learner |
🌐 Browser Automation Integration (v3.1.0)
V3.1.0 adds full browser automation support via @claude-flow/browser integration:
| Component | Description |
|---|---|
| BrowserSwarmCoordinator | Parallel multi-viewport testing (4x faster) |
| BrowserSecurityScanner | URL validation, PII detection with auto-masking |
| 9 Workflow Templates | YAML-based reusable browser workflows |
| TrajectoryAdapter | SONA learning integration with HNSW indexing |
Available Workflow Templates:
login-flow,oauth-flow- Authentication testingform-validation,navigation-flow- User journey testingvisual-regression,accessibility-audit- Quality validationperformance-audit,api-integration,scraping-workflow- Advanced workflows
# Use browser automation from Claude Code
claude "Use security-visual-testing skill to test https://example.com across mobile, tablet, desktop viewports"
# Load and execute a workflow template
aqe workflow load login-flow --vars '{"username": "test", "password": "secret"}'
👑 Queen Coordinator & Hierarchical Orchestration
The qe-queen-coordinator manages the entire fleet with intelligent task distribution:
qe-queen-coordinator
(Queen)
|
+--------------------+--------------------+
| | |
TEST DOMAIN QUALITY DOMAIN LEARNING DOMAIN
(test-generation) (quality-assessment) (learning-optimization)
| | |
- test-architect - quality-gate - learning-coordinator
- tdd-specialist - risk-assessor - pattern-learner
- integration-tester - deployment-advisor - transfer-specialist
Capabilities:
- Orchestrate 51 QE agents concurrently across 12 domains
- TinyDancer 3-tier model routing (Haiku/Sonnet/Opus) with confidence-based decisions
- Byzantine fault-tolerant consensus for critical quality decisions
- MinCut graph-based topology optimization for self-healing coordination
- Memory-backed cross-agent communication with HNSW vector search
- Work stealing with adaptive load balancing (3-5x throughput improvement)
claude "Use qe-queen-coordinator to orchestrate release validation for v2.1.0 with 90% coverage target"
🧠 ReasoningBank Learning System
V3 agents learn and improve through the ReasoningBank pattern storage:
| Component | Description |
|---|---|
| Experience Storage | Store successful patterns with confidence scores |
| HNSW Indexing | Fast O(log n) similarity search for pattern matching |
| Experience Replay | Learn from past successes and failures |
| Cross-Project Transfer | Share patterns between projects |
# Check what agents have learned
aqe memory search --query "test patterns" --namespace learning
# View learning metrics
aqe hooks metrics --v3-dashboard
🌙 Dream Cycles & Neural Learning
V3 introduces Dream cycles for neural consolidation and continuous improvement:
| Feature | Description |
|---|---|
| Dream Cycles | Background neural consolidation (30s max) with spreading activation |
| 9 RL Algorithms | Q-Learning, SARSA, DQN, PPO, A2C, DDPG, Actor-Critic, Policy Gradient, Decision Transformer |
| SONA Integration | Self-Optimizing Neural Architecture with <0.05ms adaptation |
| Novelty Scoring | Prioritize learning from novel patterns |
| Concept Graphs | Build semantic connections between quality patterns |
# Trigger dream cycle for pattern consolidation
aqe hooks intelligence --mode dream --consolidate
# View learning trajectory
aqe hooks intelligence trajectory-start --task "optimize coverage"
🎯 TinyDancer Intelligent Model Routing
TinyDancer (ADR-026) provides 3-tier intelligent model routing for cost optimization:
| Complexity Score | Model | Use Cases |
|---|---|---|
| 0-20 (Simple) | Haiku | Syntax fixes, type additions, simple refactors |
| 20-70 (Moderate) | Sonnet | Bug fixes, test generation, code review |
| 70+ (Critical) | Opus | Architecture, security, complex reasoning |
Routing Features:
- Confidence-based decisions: Routes based on task complexity analysis
- Automatic escalation: Escalates to higher-tier model if confidence is low
- Learning from outcomes: Improves routing based on success/failure patterns
- Token budget optimization: Minimizes cost while maintaining quality
# Check model routing for a task
aqe hooks model-route --task "fix type errors in user-service.ts"
# View routing statistics
aqe hooks model-stats
🔐 Consensus & MinCut Coordination
V3 includes advanced coordination mechanisms for reliable multi-agent decisions:
| Feature | Description |
|---|---|
| Byzantine Consensus | Fault-tolerant voting for critical quality decisions |
| MinCut Topology | Graph-based self-healing agent coordination |
| Multi-Model Voting | Aggregate decisions from multiple model tiers |
| Claim Verification | Cryptographic verification of agent work claims |
# View consensus status
aqe coordination consensus --status
# Check topology health
aqe coordination topology --optimize
🔍 O(log n) Coverage Analysis
Efficient coverage gap detection using Johnson-Lindenstrauss algorithms:
- Sublinear complexity: Analyze large codebases in logarithmic time
- Risk-weighted gaps: Prioritize coverage by business impact
- Intelligent test selection: Minimal tests for maximum coverage
- Trend tracking: Monitor coverage changes over time
claude "Use qe-coverage-specialist to analyze gaps in src/ with risk scoring"
🔗 Claude Flow Integration
V3 deeply integrates with Claude Flow for:
- MCP Server: All V3 tools available via Model Context Protocol
- Swarm Orchestration: Multi-agent coordination with hierarchical topology
- Memory Sharing: Cross-agent state via
aqe/v3/*namespaces - Hooks System: Pre/post task learning and optimization
- Session Management: Persistent state across conversations
# Initialize swarm with Claude Flow
npx @claude-flow/cli@latest swarm init --topology hierarchical-mesh
# Spawn V3 agents
npx @claude-flow/cli@latest agent spawn -t qe-test-architect --name test-gen
📊 50 Specialized QE Agents
| Category | Count | Highlights |
|---|---|---|
| Main QE Agents | 43 | Test generation, coverage, security, performance, accessibility |
| TDD Subagents | 7 | RED/GREEN/REFACTOR with code review |
V2 Backward Compatibility: All V2 agents map to V3 equivalents automatically.
📋 View All Main QE Agents (43)
| Agent | Domain | Purpose |
|---|---|---|
| qe-queen-coordinator | coordination | Hierarchical fleet orchestration |
| qe-test-architect | test-generation | AI-powered test creation |
| qe-tdd-specialist | test-generation | TDD workflow coordination |
| qe-parallel-executor | test-execution | Multi-worker test execution |
| qe-retry-handler | test-execution | Intelligent retry with backoff |
| qe-coverage-specialist | coverage-analysis | O(log n) coverage analysis |
| qe-gap-detector | coverage-analysis | Risk-weighted gap detection |
| qe-quality-gate | quality-assessment | Quality threshold validation |
| qe-risk-assessor | quality-assessment | Multi-factor risk scoring |
| qe-deployment-advisor | quality-assessment | Go/no-go deployment decisions |
| qe-defect-predictor | defect-intelligence | ML-powered defect prediction |
| qe-root-cause-analyzer | defect-intelligence | Systematic root cause analysis |
| qe-flaky-hunter | defect-intelligence | Flaky test detection & fix |
| qe-requirements-validator | requirements-validation | Testability analysis |
| qe-bdd-generator | requirements-validation | Gherkin scenario generation |
| qe-code-intelligence | code-intelligence | Semantic code search |
| qe-kg-builder | code-intelligence | Knowledge graph construction |
| qe-dependency-mapper | code-intelligence | Dependency analysis |
| qe-security-scanner | security-compliance | SAST/DAST scanning |
| qe-security-auditor | security-compliance | Security audit & compliance |
| qe-contract-validator | contract-testing | API contract validation |
| qe-graphql-tester | contract-testing | GraphQL testing |
| qe-visual-tester | visual-accessibility | Visual regression testing |
| qe-accessibility-auditor | visual-accessibility | WCAG compliance testing |
| qe-responsive-tester | visual-accessibility | Cross-viewport testing |
| qe-chaos-engineer | chaos-resilience | Controlled fault injection |
| qe-load-tester | chaos-resilience | Load & performance testing |
| qe-performance-tester | chaos-resilience | Performance validation |
| qe-learning-coordinator | learning-optimization | Fleet-wide learning |
| qe-pattern-learner | learning-optimization | Pattern discovery |
| qe-transfer-specialist | learning-optimization | Cross-project transfer |
| qe-metrics-optimizer | learning-optimization | Hyperparameter tuning |
| qe-integration-tester | test-execution | Component integration |
| qe-mutation-tester | test-generation | Test effectiveness validation |
| qe-property-tester | test-generation | Property-based testing |
| qe-regression-analyzer | defect-intelligence | Regression risk analysis |
| qe-impact-analyzer | code-intelligence | Change impact assessment |
| qe-code-complexity | code-intelligence | Complexity metrics |
| qe-qx-partner | quality-assessment | QA + UX collaboration |
| qe-fleet-commander | coordination | Large-scale orchestration |
| qe-integration-architect | code-intelligence | V3 integration design |
| qe-product-factors-assessor | quality-assessment | SFDIPOT product factors analysis |
| qe-test-idea-rewriter | test-generation | Transform passive tests to active actions |
🔧 TDD Subagents (7)
| Subagent | Phase | Purpose |
|---|---|---|
| qe-tdd-red | RED | Write failing tests |
| qe-tdd-green | GREEN | Implement minimal code |
| qe-tdd-refactor | REFACTOR | Improve code quality |
| qe-code-reviewer | REVIEW | Code quality validation |
| qe-integration-reviewer | REVIEW | Integration review |
| qe-performance-reviewer | REVIEW | Performance review |
| qe-security-reviewer | REVIEW | Security review |
💻 V3 Usage Examples
Example 1: Queen-Coordinated Quality Pipeline
claude "Use qe-queen-coordinator to run full quality assessment:
1. Generate tests for src/services/*.ts
2. Execute tests with parallel workers
3. Analyze coverage gaps with risk scoring
4. Run security scan
5. Validate quality gate at 90% threshold
6. Provide deployment recommendation"
What happens:
- Queen spawns domain coordinators for each task
- Agents execute in parallel across 5 domains
- Results aggregate through memory coordination
- Queen synthesizes final recommendation
Example 2: Learning-Enhanced Test Generation
claude "Use qe-test-architect to create tests for PaymentService with:
- Property-based testing for validation
- 95% coverage target
- Apply learned patterns from similar services"
Output includes:
Generated 48 tests across 4 files
- unit/PaymentService.test.ts (32 unit tests)
- property/PaymentValidation.property.test.ts (8 property tests)
- integration/PaymentFlow.integration.test.ts (8 integration tests)
Coverage: 96.2%
Pattern reuse: 78% from learned patterns
Learning stored: "payment-validation-patterns" (confidence: 0.94)
Example 3: TDD Workflow with Subagents
claude "Use qe-tdd-specialist to implement UserAuthentication with full RED-GREEN-REFACTOR cycle"
Workflow:
- qe-tdd-red: Writes failing tests defining behavior
- qe-tdd-green: Implements minimal code to pass
- qe-tdd-refactor: Improves code quality
- qe-code-reviewer: Validates standards
- qe-security-reviewer: Checks security concerns
Example 4: Cross-Domain Coordination
claude "Coordinate security audit across the monorepo:
- qe-security-scanner for SAST/DAST
- qe-dependency-mapper for vulnerability scanning
- qe-contract-validator for API security
- qe-chaos-engineer for resilience testing"
🎓 61 QE Skills
V3 agents automatically apply relevant skills from the comprehensive skill library:
View All 61 QE Skills
Core Testing & Methodologies (12)
- agentic-quality-engineering - Core PACT principles for AI-powered QE
- holistic-testing-pact - Evolved testing model with PACT integration
- context-driven-testing - Practices chosen based on project context
- tdd-london-chicago - Test-driven development with both school approaches
- xp-practices - Extreme programming practices for quality
- risk-based-testing - Focus testing effort on highest-risk areas
- test-automation-strategy - Strategic approach to automation
- refactoring-patterns - Safe code improvement patterns
- shift-left-testing - Early testing in development lifecycle
- shift-right-testing - Production testing and observability
- regression-testing - Strategic regression management
- verification-quality - Quality verification practices
Specialized Testing (13)
- accessibility-testing - WCAG 2.2 compliance and inclusive design
- mobile-testing - iOS and Android platform testing
- database-testing - Schema validation and data integrity
- contract-testing - Consumer-driven contract testing
- chaos-engineering-resilience - Fault injection and resilience testing
- visual-testing-advanced - Visual regression and UI testing
- security-visual-testing - Security-first visual testing with PII detection
- compliance-testing - Regulatory compliance (GDPR, HIPAA, SOC2)
- compatibility-testing - Cross-browser and platform testing
- localization-testing - i18n and l10n testing
- mutation-testing - Test suite effectiveness evaluation
- performance-testing - Load, stress, and scalability testing
- security-testing - OWASP and security vulnerability testing
V3 Domain Skills (14)
- qe-test-generation - AI-powered test synthesis
- qe-test-execution - Parallel execution and retry logic
- qe-coverage-analysis - O(log n) sublinear coverage
- qe-quality-assessment - Quality gates and deployment readiness
- qe-defect-intelligence - ML defect prediction and root cause
- qe-requirements-validation - BDD scenarios and acceptance criteria
- qe-code-intelligence - Knowledge graphs and token reduction
- qe-security-compliance - OWASP and CVE detection
- qe-contract-testing - Pact and schema validation
- qe-visual-accessibility - Visual regression and WCAG
- qe-chaos-resilience - Fault injection and resilience
- qe-learning-optimization - Transfer learning and self-improvement
- qe-iterative-loop - QE iteration patterns
- aqe-v2-v3-migration - Migration guide from v2 to v3
Strategic & Communication (8)
- six-thinking-hats - Edward de Bono's methodology for QE
- brutal-honesty-review - Unvarnished technical criticism
- sherlock-review - Evidence-based investigative code review
- cicd-pipeline-qe-orchestrator - CI/CD quality orchestration
- bug-reporting-excellence - High-quality bug reports
- consultancy-practices - QE consultancy workflows
- quality-metrics - Effective quality measurement
- pair-programming - AI-assisted pair programming
Testing Techniques & Management (9)
- exploratory-testing-advanced - SBTM and RST heuristics
- test-design-techniques - Test design methodologies
- test-data-management - Test data strategies
- test-environment-management - Environment configuration
- test-reporting-analytics - Quality dashboards and KPIs
- testability-scoring - Score code testability
- technical-writing - Documentation practices
- code-review-quality - Context-driven code reviews
- api-testing-patterns - REST and GraphQL testing
n8n Workflow Testing (5) (contributed by @fndlalit)
- n8n-workflow-testing-fundamentals - Execution lifecycle and data flow
- n8n-expression-testing - Expression validation and testing
- n8n-security-testing - Workflow security scanning
- n8n-trigger-testing-strategies - Webhook and event testing
- n8n-integration-testing-patterns - API contract testing for n8n
🔄 V2 to V3 Migration
V3 provides automatic backward compatibility with V2:
# Check migration status
aqe migrate status
# Run migration with backup
aqe migrate run --backup
# Validate migration
aqe migrate validate
What gets migrated:
- ✅ Memory data (SQLite → AgentDB with HNSW indexing)
- ✅ Configuration files
- ✅ Learned patterns (→ ReasoningBank)
- ✅ Agent mappings (V2 names → V3 equivalents)
| V2 Agent | V3 Agent |
|---|---|
| qe-test-generator | qe-test-architect |
| qe-coverage-analyzer | qe-coverage-specialist |
| qe-quality-gate | qe-quality-gate |
| qe-security-scanner | qe-security-scanner |
| qe-coordinator | qe-queen-coordinator |
🤖 LLM Provider Configuration
AQE V3 supports multiple LLM providers for maximum flexibility:
| Provider | Type | Cost | Best For |
|---|---|---|---|
| Ollama | Local | FREE | Privacy, offline |
| OpenRouter | Cloud | Varies | 300+ models |
| Groq | Cloud | FREE | High-speed |
| Claude API | Cloud | Paid | Highest quality |
| Google AI | Cloud | FREE | Gemini models |
# Configure provider
export GROQ_API_KEY="gsk_..."
aqe init --auto
📖 Documentation
V3 Guides
- V3 Migration Guide - Complete migration instructions
- V3 CLI Reference - All V3 commands
- DDD Architecture - Domain-driven design overview
V2 Documentation (Legacy)
- V2 README - Complete V2 documentation
- Quick Start Guide - V2 quick start
- User Guide - V2 workflows and examples
Feature Guides
- Learning System Guide - ReasoningBank learning
- Pattern Management Guide - Cross-project patterns
- MCP Integration - Claude Code integration
Testing Guides
- Test Generation - AI-powered test creation
- Coverage Analysis - O(log n) gap detection
- Quality Gates - Intelligent validation
📊 Project Architecture
agentic-qe/
├── v3/ # V3 DDD Implementation (Main Version)
│ ├── src/
│ │ ├── kernel/ # Shared kernel
│ │ ├── domains/ # 12 bounded contexts
│ │ │ ├── test-generation/
│ │ │ ├── coverage-analysis/
│ │ │ ├── quality-assessment/
│ │ │ └── ...
│ │ ├── routing/ # Agent routing & registry
│ │ ├── mcp/ # MCP server
│ │ └── cli/ # V3 CLI
│ ├── tests/ # 5,600+ tests
│ └── assets/agents/ # 51 QE agent definitions (44 main + 7 subagents)
├── v2/ # V2 Implementation (Legacy)
│ ├── src/ # V2 source code
│ ├── tests/ # V2 tests
│ └── docs/ # V2 documentation
├── .claude/
│ ├── agents/v3/ # V3 agent definitions (source)
│ └── skills/ # 15 QE-specific skills
├── docs/ # Shared documentation
│ ├── plans/ # Migration plans
│ ├── policies/ # Project policies
│ └── v3/ # V3 specific docs
├── package.json # Points to v3 (main version)
└── README.md # This file
🚀 Development
Setup
# Clone repository
git clone https://github.com/proffesor-for-testing/agentic-qe.git
cd agentic-qe
# Install V3 dependencies
cd v3
npm install
# Build
npm run build
# Run tests
npm test -- --run
V3 Scripts
| Script | Description |
|---|---|
npm run build |
Compile TypeScript |
npm test -- --run |
Run all tests |
npm run cli |
Run CLI in dev mode |
npm run mcp |
Start MCP server |
🤝 Contributing
We welcome contributions! Please see CONTRIBUTING.md for details.
📞 Support
- Documentation: docs/
- Issues: GitHub Issues
- Discussions: GitHub Discussions
- Email: support@agentic-qe.com
📝 License
This project is licensed under the MIT License - see the LICENSE file for details.
👥 Contributors
Thanks to all the amazing people who have contributed to Agentic QE Fleet!
![]() @proffesor-for-testing Project Lead |
![]() @fndlalit QX Partner, Testability |
![]() @shaal Core Development |
![]() @mondweep Architecture |
|---|
View all contributors | Become a contributor
💖 Support the Project
If you find Agentic QE Fleet valuable, consider supporting its development:
| Monthly | Annual (Save $10) | |
|---|---|---|
| Price | $5/month | $50/year |
| Benefits | Sponsor recognition, Priority support | All monthly + Featured in README, Roadmap input |
| Subscribe | Monthly | Annual |
🙏 Acknowledgments
V3 is built on the shoulders of giants:
- Claude Flow by @ruvnet - Multi-agent orchestration, MCP integration, swarm coordination
- Agentic Flow by @ruvnet - Agent patterns, learning systems, neural coordination
- Built with TypeScript, Node.js, and better-sqlite3
- HNSW indexing via hnswlib-node
- Inspired by Domain-Driven Design and swarm intelligence
- Integrates with Jest, Cypress, Playwright, k6, SonarQube, and more
- Compatible with Claude Code via Model Context Protocol (MCP)
Made with ❤️ by the Agentic QE Team



