agentic-qe

Agentic Quality Engineering Fleet

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AI-powered quality engineering agents that generate tests, find coverage gaps, detect flaky tests, and learn your codebase patterns — across 11 coding agent platforms.

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What AQE Does For You

• Generates comprehensive tests automatically — unit, integration, property-based, and BDD scenarios for your codebase with framework-specific output (Jest, Vitest, Playwright, Cypress, pytest, JUnit, Go, Rust, Swift, Flutter, and more)
• Finds coverage gaps and prioritizes what to test — risk-weighted analysis identifies the most impactful untested code paths
• Detects and fixes flaky tests — ML-powered detection with root cause analysis and stabilization recommendations
• Learns your codebase patterns over time — remembered patterns are reused across sessions and projects, improving with every interaction
• Coordinates 60 specialized QE agents — from test generation to security scanning to chaos engineering, orchestrated by a central coordinator
• Reduces AI costs with intelligent routing — automatically routes tasks to the right model tier (fast/cheap for simple tasks, powerful for complex ones)
• Works with your existing tools — integrates with 11 coding agent platforms and your existing CI/CD pipeline

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Quick Start

# Install
npm install -g agentic-qe

# Initialize your project (auto-detects tech stack, configures MCP)
cd your-project && aqe init --auto

# That's it — MCP tools are available immediately in Claude Code
# For other clients: aqe-mcp

After init, your coding agent can use AQE tools directly. For example in Claude Code:

"Generate tests for src/services/UserService.ts with 90% coverage target"
"Find coverage gaps in src/ and prioritize by risk"
"Run security scan on the authentication module"
"Analyze why tests in auth/ are flaky and suggest fixes"

Windows install

agentic-qe runs on Windows, but several of its performance-oriented native dependencies (hnswlib-node for HNSW search, @ruvector/gnn for graph neural networks, @ruvector/rvf-node for the RVF pattern store) ship as optional native modules. hnswlib-node in particular has no prebuilt binaries and compiles from source via node-gyp. npm install does not fail when these modules can't build — they're declared optional and AQE falls back to JavaScript paths at runtime.

Important caveat about the fallback. The pure-JavaScript HNSW fallback (ProgressiveHnswBackend) is correct but degrades to O(N) brute-force search when neither hnswlib-node nor @ruvector/gnn is available. That's fine for small projects but unsuitable for large indexes (tens of thousands of vectors and up). If you plan to run AQE against a sizeable codebase on Windows, install the native build toolchain so hnswlib-node compiles:

• Python 3 (added to PATH), and
• Visual Studio 2022 Build Tools with the Desktop development with C++ workload — works with any node-gyp version, or
• Visual Studio 2026 with the same workload plus an upgraded npm (npm install -g npm@latest — VS 2026 detection requires npm ≥ 11.6.3, shipped via node-gyp ≥ 12.1.0). Node 22 LTS still ships npm 10.x by default, which cannot detect VS 2026; either upgrade npm globally or use VS 2022 Build Tools instead.

If the native dep fails to build you'll see a node-gyp warning during install (e.g. gyp ERR! find VS); the install itself completes. To verify which backend is active:

aqe health
# Look for "HNSW backend: native" (hnswlib-node) or "HNSW backend: js"
# (ProgressiveHnswBackend — see caveat above).

Linux and macOS users: no extra setup required. The native binary compiles out of the box.

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Claude Code Plugin (Alternative Install)

If you only need a slim, scoped fleet inside Claude Code — without the full aqe init setup — install the agentic-qe-fleet plugin. It bundles 11 specialized QE agents, 9 slash commands, 9 skills, and auto-registers the MCP server.

Install from a local checkout

git clone https://github.com/proffesor-for-testing/agentic-qe.git
claude --plugin-dir ./agentic-qe/plugins/agentic-qe-fleet

Install from the marketplace

In any Claude Code session:

/plugin marketplace add proffesor-for-testing/agentic-qe
/plugin install agentic-qe-fleet

What you get

Asset	Count	Notes
Agents (Task tool)	11	Model-routed: 6 on Opus (heavy reasoning), 5 on Sonnet (focused execution)
Slash commands	9	/aqe-analyze, /aqe-execute, /aqe-generate, /aqe-optimize, /aqe-chaos, /aqe-fleet-status, /aqe-report, /aqe-benchmark, /aqe-costs
Skills	9	All trust-tier 2 or 3 (validated/verified). Tier-1 untested skills excluded per policy.
MCP server	1	Auto-registers via npx -y agentic-qe@latest mcp — no separate claude mcp add

Bundled agents: qe-test-architect, qe-coverage-specialist, qe-flaky-hunter, qe-chaos-engineer, qe-fleet-commander, qe-quality-gate, qe-security-scanner, qe-performance-tester, qe-regression-analyzer, qe-tdd-specialist, qe-requirements-validator.

Bundled skills: qe-test-generation, qe-coverage-analysis, qe-test-execution, qe-chaos-resilience, qe-quality-assessment, chaos-engineering-resilience, mutation-testing, risk-based-testing, tdd-london-chicago.

Use it

After loading the plugin, the slash commands and agents are available immediately:

/aqe-fleet-status                 # health and metrics
/aqe-generate src/services/Auth.ts
/aqe-analyze src/                 # coverage gap analysis

Or invoke an agent through the Task tool:

"Use qe-test-architect to generate tests for src/services/PaymentService.ts"
"Use qe-flaky-hunter to find and stabilize flaky tests in tests/integration/"
"Use qe-chaos-engineer to inject network partitions into the order workflow"

Plugin vs aqe init — which to use?

	Plugin	aqe init
Setup	One slash command	Full project setup
Scope	11 agents, 9 skills	60 agents, 86 skills
Persistent learning DB	No (uses MCP server's)	Yes (.agentic-qe/memory.db)
Cross-platform support	Claude Code only	11 platforms (Cursor, Copilot, Cline, etc.)
Use when	Quick start, single Claude Code project	Production team setup, multi-platform, full fleet

You can run both — the plugin's MCP server uses the same agentic-qe package, so installing both gives you the full fleet via aqe init and the slash-command shortcuts via the plugin.

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Platform Support

AQE works with 11 coding agent platforms through a single MCP server:

Platform	Setup
Claude Code	aqe init --auto (built-in)
GitHub Copilot	aqe init --auto --with-copilot
Cursor	aqe init --auto --with-cursor
Cline	aqe init --auto --with-cline
OpenCode	aqe init --auto --with-opencode
AWS Kiro	aqe init --auto --with-kiro
Kilo Code	aqe init --auto --with-kilocode
Roo Code	aqe init --auto --with-roocode
OpenAI Codex CLI	aqe init --auto --with-codex
Windsurf	aqe init --auto --with-windsurf
Continue.dev	aqe init --auto --with-continuedev

# Set up all platforms at once
aqe init --auto --with-all-platforms

# Or add a platform later
aqe platform setup cursor
aqe platform list       # show install status
aqe platform verify cursor  # validate config

For detailed per-platform instructions, see Platform Setup Guide.

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Usage Examples

Generate Tests

claude "Use qe-test-architect to create tests for PaymentService with 95% coverage target"

Output:

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

Full Quality Pipeline

claude "Use qe-queen-coordinator to run full quality assessment:
1. Generate tests for src/services/*.ts
2. Analyze coverage gaps with risk scoring
3. Run security scan
4. Validate quality gate at 90% threshold
5. Provide deployment recommendation"

The Queen Coordinator spawns domain-specific agents, runs them in parallel, and synthesizes a final recommendation.

TDD Workflow

claude "Use qe-tdd-specialist to implement UserAuthentication with full RED-GREEN-REFACTOR cycle"

Coordinates 5 subagents: write failing tests → implement minimal code → refactor → code review → security review.

Security Audit

claude "Coordinate security audit:
- SAST/DAST scanning with qe-security-scanner
- Dependency vulnerability scanning with qe-dependency-mapper
- API security with qe-contract-validator
- Chaos resilience testing with qe-chaos-engineer"

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60 QE Agents

The fleet is organized into 13 domains, coordinated by the qe-queen-coordinator:

Domain	Agents	What They Do
Test Generation	test-architect, tdd-specialist, mutation-tester, property-tester	Generate tests, TDD workflows, validate test effectiveness
Test Execution	parallel-executor, retry-handler, integration-tester	Run tests in parallel, handle retries, integration testing
Coverage Analysis	coverage-specialist, gap-detector	Find untested code, prioritize by risk
Quality Assessment	quality-gate, risk-assessor, deployment-advisor, devils-advocate	Go/no-go decisions, risk scoring, adversarial review
Defect Intelligence	defect-predictor, root-cause-analyzer, flaky-hunter, regression-analyzer	Predict bugs, find root causes, fix flaky tests
Requirements	requirements-validator, bdd-generator	Validate testability, generate BDD scenarios
Code Intelligence	code-intelligence, kg-builder, dependency-mapper, impact-analyzer	Knowledge graphs, semantic search, change impact
Security	security-scanner, security-auditor, pentest-validator	SAST/DAST, compliance audits, exploit validation
Contracts	contract-validator, graphql-tester	API contracts, GraphQL schema testing
Visual & A11y	visual-tester, accessibility-auditor, responsive-tester	Visual regression, WCAG compliance, viewport testing
Chaos & Performance	chaos-engineer, load-tester, performance-tester	Fault injection, load testing, performance validation
Learning	learning-coordinator, pattern-learner, transfer-specialist, metrics-optimizer	Cross-project learning, pattern discovery
Enterprise	soap-tester, sap-rfc-tester, sap-idoc-tester, sod-analyzer, odata-contract-tester, middleware-validator, message-broker-tester	SAP, SOAP, ESB, OData, JMS/AMQP/Kafka

Plus 7 TDD subagents (red, green, refactor, code/integration/performance/security reviewers) and the fleet-commander for large-scale orchestration.

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75 QE Skills