claude

agentic-qe-fleet

Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data

81,589 on GitHubby Agentic QEv3.15.17MITupdated today
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Plugin agentic-qe-fleet from marketplace ruflo in ruvnet/ruflo. Commands read from the repo's manifest — today.

This plugin runs code on your machine — it starts local MCP servers. The exact commands are listed below; read them before installing.

What it installs

Skills (9)

  • chaos-engineering-resilience

    Chaos engineering principles, controlled failure injection, resilience testing, and system recovery validation. Use when testing distributed systems, building confidence in fault tolerance, or validating disaster recovery.

  • mutation-testing

    Test quality validation through mutation testing, assessing test suite effectiveness by introducing code mutations and measuring kill rate. Use when evaluating test quality, identifying weak tests, or proving tests actually catch bugs.

  • qe-chaos-resilience

    Injects controlled faults (network partition, latency, process kill, disk pressure) into distributed systems and validates recovery behavior. Use when testing circuit breakers, failover paths, retry logic, or building confidence in system resilience through chaos engineering.

  • qe-coverage-analysis

    Analyzes test coverage data (Istanbul, c8, lcov) to identify uncovered lines, branches, and functions with risk-weighted gap detection. Use when analyzing coverage reports, identifying coverage gaps, comparing coverage between branches, or prioritizing which untested code to cover first.

  • qe-quality-assessment

    Evaluates code quality through complexity analysis, lint results, code smell detection, and test health metrics. Use when assessing deployment readiness, configuring quality gates, scoring a codebase for release, or generating quality reports with pass/fail verdicts.

  • qe-test-execution

    Orchestrates test suite execution with parallel sharding, intelligent retry, and real-time reporting across Jest, Vitest, and Playwright. Use when running test suites, optimizing execution time, handling flaky tests, configuring CI test pipelines, or analyzing test run results.

  • qe-test-generation

    Generates durable-first tests — invariants, contracts, and property-based tests at boundaries that survive a reimplementation — plus unit, integration, and e2e coverage. Use when creating tests for new or changed code, filling coverage gaps, or migrating test suites between Jest, Vitest, and Playwri

  • risk-based-testing

    Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating testing resources, or making coverage decisions.

  • tdd-london-chicago

    Apply London (mock-based) and Chicago (state-based) TDD schools. Use when practicing test-driven development or choosing testing style for your context.

Slash commands (9)

  • /agentic-qe-fleet:aqe-analyze

    Analyze test coverage, identify gaps, and optimize coverage strategy using sublinear algorithms

  • /agentic-qe-fleet:aqe-benchmark

    Run performance benchmarks and compare against baselines

  • /agentic-qe-fleet:aqe-chaos

    Run chaos testing scenarios to validate system resilience and fault tolerance

  • /agentic-qe-fleet:aqe-costs

    Display inference cost analysis and savings from local vs cloud providers

  • /agentic-qe-fleet:aqe-execute

    Execute test suites with parallel orchestration, retry logic, and real-time reporting

  • /agentic-qe-fleet:aqe-fleet-status

    Display comprehensive fleet health, agent status, and coordination metrics

  • /agentic-qe-fleet:aqe-generate

    Generate comprehensive test suites using AI-powered analysis and sublinear optimization

  • /agentic-qe-fleet:aqe-optimize

    Optimize test suites using sublinear algorithms to maximize coverage while minimizing test count and execution time

  • /agentic-qe-fleet:aqe-report

    Generate comprehensive quality engineering reports with metrics, trends, and actionable insights

Subagents (11)

  • qe-chaos-engineer

    Chaos engineering specialist for controlled fault injection, resilience testing, and system weakness discovery

  • qe-coverage-specialist

    O(log n) sublinear coverage analysis with risk-weighted gap detection and HNSW vector indexing

  • qe-flaky-hunter

    Flaky test detection and remediation with pattern recognition and auto-stabilization

  • qe-fleet-commander

    Fleet management with agent lifecycle, workload distribution, and cross-domain coordination at scale

  • qe-performance-tester

    Performance testing with load, stress, endurance testing and regression detection

  • qe-quality-gate

    Quality gate enforcement with configurable thresholds, policy validation, and AI-powered deployment decisions

  • qe-regression-analyzer

    Regression risk analysis with intelligent test selection, historical analysis, and change impact scoring

  • qe-requirements-validator

    Requirements validation with testability analysis, BDD scenario generation, and acceptance criteria validation

  • qe-security-scanner

    Comprehensive security scanning with SAST, DAST, dependency scanning, and secrets detection

  • qe-tdd-specialist

    TDD Red-Green-Refactor specialist for test-driven development with London and Chicago school support

  • qe-test-architect

    AI-powered test generation with sublinear optimization, multi-framework support, and self-learning capabilities

MCP servers (1)

View source on GitHub cognitum.one

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