agentic-qe

Agentic QE Fleet is an open-source AI-powered QA/QE platform designed for use with Coding Agents (works best with Claude Code) featuring specialized agents and skills to support testing activities for a product at any stage of the SDLC. Free to use, fork, build, and contribute. Based on the Agentic QE Framework created by Dragan Spiridonov.

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Install command
npx skhub add --skillset @proffesor-for-testing/agentic-qe

Included Skills

n8n expression syntax validation, context-aware testing, common pitfalls detection, and performance optimization. Use when validating n8n expressions and data transformations.
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Testing in production with feature flags, canary deployments, synthetic monitoring, and chaos engineering. Use when implementing production observability or progressive delivery.
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Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios.
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End-to-end npm release workflow with verification gates and hardcoded-version protection
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Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating testing resources, or making coverage decisions.
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Move testing activities earlier in the development lifecycle to catch defects when they're cheapest to fix. Use when implementing TDD, CI/CD, or early quality practices.
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Testing in production with feature flags, canary deployments, synthetic monitoring, and chaos engineering. Use when implementing production observability or progressive delivery.
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Unify 6+ memory systems into AgentDB with HNSW indexing for 150x-12,500x search improvements. Implements ADR-006 (Unified Memory Service) and ADR-009 (Hybrid Memory Backend).
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Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
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Complete security architecture overhaul for claude-flow v3. Addresses critical CVEs (CVE-1, CVE-2, CVE-3) and implements secure-by-default patterns. Use for security-first v3 implementation.
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15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.
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Runs multi-stage validation gates with per-step scoring, pass/fail verdicts, and aggregate quality reports. Use when validating requirements, code, or artifacts through structured gate enforcement before merge or release.
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Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
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Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.
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WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.
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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.
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Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.
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Comprehensive n8n workflow testing including execution lifecycle, node connection patterns, data flow validation, and error handling strategies. Use when testing n8n workflow automation applications.
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Use when you want to prevent .skip(), .only(), xit(), and xdescribe() from being committed to test files. Activate with /no-skip for session-scoped test skip prevention.
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Observability and monitoring validation patterns for dashboards, alerting, log aggregation, APM traces, and SLA/SLO verification. Use when testing monitoring infrastructure, dashboard accuracy, alert rules, or metric pipelines.
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AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
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Use when validating security findings from SAST/DAST scans, proving exploitability of reported vulnerabilities, eliminating false positives, or running the 4-phase pentest pipeline (recon, analysis, validation, report).
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Profiles application performance under load using k6, Artillery, or JMeter to measure latency, throughput, and error rates. Use when planning load tests, stress tests, soak tests, benchmarking APIs, or identifying performance bottlenecks.
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Use when reviewing a GitHub PR for quality, scope correctness, trust tier compliance, or generating user-friendly review feedback.
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QCSD Verification phase swarm for CI/CD pipeline quality gates using regression analysis, flaky test detection, quality gate enforcement, and deployment readiness assessment. Consumes Development outputs (SHIP/CONDITIONAL/HOLD decisions, quality metrics) and produces signals for Production monitoring.
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QCSD Development phase swarm for in-sprint code quality assurance using TDD adherence, code complexity analysis, coverage gap detection, and defect prediction. Consumes Refinement outputs (BDD scenarios, SFDIPOT priorities) and produces signals for Verification.
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QCSD Ideation phase swarm for Quality Criteria sessions using HTSM v6.3, Risk Storming, and Testability analysis before development begins. Uses 5-tier browser cascade: Vibium → agent-browser → Playwright+Stealth → WebFetch → WebSearch-fallback.
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QCSD Production Telemetry phase swarm for post-release production health assessment using DORA metrics, root cause analysis, defect prediction, and cross-phase feedback loops. Consumes CI/CD outputs (RELEASE/REMEDIATE/BLOCK decisions, release readiness metrics) and produces feedback signals to Ideation and Refinement.
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QCSD Refinement phase swarm for Sprint Refinement sessions using SFDIPOT product factors, BDD scenario generation, and requirements validation.
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Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
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Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.
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Use when orchestrating QE agents, understanding PACTS principles, configuring the AQE v3 fleet, or leveraging AI agents as force multipliers for quality work.
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Comprehensive API testing patterns including contract testing, REST/GraphQL testing, and integration testing. Use when testing APIs or designing API test strategies.
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Create risk-based quality and test plans for Agentic QE changes. Use when scoping a feature, translating requirements into verification work, selecting QE specialties, assessing testability, or deciding which `.claude/agents/v3/qe-*.md` capabilities should inform a task. Do not use merely to execute an already-defined test command.
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Use when debugging a failing test or runtime error with hypothesis-driven investigation, autonomous command validation, and systematic root cause elimination.
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Use when verifying complete user flows end-to-end with the qe-browser skill (Vibium), recording session evidence, and asserting state at each step. For product verification with real browser automation.
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Use when testing enterprise integrations across SAP, middleware, WMS, or backend systems, validating E2E enterprise flows, testing SAP-specific patterns (RFC, BAPI, IDoc, OData, Fiori), or enforcing cross-system quality gates.
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Advanced exploratory testing techniques with Session-Based Test Management (SBTM), RST heuristics, and test tours. Use when planning exploration sessions, investigating bugs, or discovering unknown quality risks.
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Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus
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Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges
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Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
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Build dependency-aware execution plans for complex Agentic QE, Ruflo, integration, migration, or multi-stream engineering programs. Use when Codex must turn research or requirements into phased work, select a small AQE fleet, map critical paths and parallel streams, define acceptance gates, or sequence risky changes. Use aqe-plan-quality instead when the primary output is only a test or quality plan.
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Conduct evidence-first technical research for Agentic QE, Ruflo, related ruvnet projects, or external tools. Use when Codex must investigate a repository, compare current upstream changes, trace dependencies and history, distinguish verified facts from inference, or synthesize findings into actionable engineering recommendations. Do not use for a simple known-answer lookup or an implementation-only task.
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Review Agentic QE changes and issue an evidence-backed quality verdict. Use for code review, regression-risk assessment, release readiness, quality-gate evaluation, security/performance/testability review, or checking whether a change has sufficient verification. Do not use when the user primarily asks to implement a feature.
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Add optional Ruflo development-time orchestration to an Agentic QE workflow. Use when a task benefits from coordinated swarms, persistent cross-session memory, routing, or Ruflo hooks. Do not use for a one-shot edit, and never add Ruflo to shipped AQE runtime dependencies.
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Design, implement, and run durable tests for Agentic QE code changes. Use when adding tests, reproducing a defect, filling a coverage gap, selecting affected Vitest suites, checking CLI/MCP parity, or verifying a fix in this repository. Do not use for a read-only quality review with no requested edits.
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Web browser automation with AI-optimized snapshots for claude-flow agents
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Use when refactoring production code and you want to ensure test files are not modified. Activate with /freeze-tests to block all edits to test files for safe refactoring.
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Comprehensive GitHub code review with AI-powered swarm coordination
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Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
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Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
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Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
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Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management
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Unvarnished technical criticism combining Linus Torvalds' precision, Gordon Ramsay's standards, and James Bach's BS-detection. Use when code/tests need harsh reality checks, certification schemes smell fishy, or technical decisions lack rigor. No sugar-coating, just surgical truth about what's broken and why.
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Write high-quality bug reports that get fixed quickly. Use when reporting bugs, training teams on bug reporting, or establishing bug report standards.
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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.
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Orchestrate quality engineering across CI/CD pipeline phases. Use when designing test strategies, planning quality gates, or implementing shift-left/shift-right testing.
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Conduct context-driven code reviews focusing on quality, testability, and maintainability. Use when reviewing code, providing feedback, or establishing review practices.
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Cross-browser, cross-platform, and cross-device compatibility testing ensuring consistent experience across environments. Use when validating browser support, testing responsive design, or ensuring platform compatibility.
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Regulatory compliance testing for GDPR, CCPA, HIPAA, SOC2, PCI-DSS and industry-specific regulations. Use when ensuring legal compliance, preparing for audits, or handling sensitive data.
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Apply effective software quality consultancy practices. Use when consulting, advising clients, or establishing consultancy workflows.
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Apply context-driven testing principles where practices are chosen based on project context, not universal 'best practices'. Use when making testing decisions, questioning dogma, or adapting approaches to specific project needs.
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Consumer-driven contract testing for microservices using Pact, schema validation, API versioning, and backward compatibility testing. Use when testing API contracts or coordinating distributed teams.
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Use when test coverage has dropped and you need to find which changes caused it and what tests to add. Traces coverage regressions to specific commits and files.
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Use when you want to prevent coverage regressions during development. Activate with /coverage-guard to warn when coverage drops below threshold after code changes.
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Database schema validation, data integrity testing, migration testing, transaction isolation, and query performance. Use when testing data persistence, ensuring referential integrity, or validating database migrations.
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Apply the Holistic Testing Model evolved with PACTS (Proactive, Autonomous, Collaborative, Targeted, Structured) principles. Use when designing comprehensive test strategies for Classical, AI-assisted, Agent based, or Agentic Systems building quality into the team, or implementing whole-team quality practices.
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Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.
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Runs continuous AI iteration loops that repeat build-test-fix cycles until success criteria are met. Use when building features requiring test-driven refinement, implementing tasks with clear pass/fail criteria, or automating iterative improvement workflows.
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Internationalization (i18n) and localization (l10n) testing for global products including translations, locale formats, RTL languages, and cultural appropriateness. Use when launching in new markets or building multi-language products.
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Enterprise middleware testing patterns for message routing, transformation, DLQ, protocol mediation, ESB error handling, and EIP patterns. Use when testing middleware layers, message brokers, ESBs, or integration buses.
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Comprehensive mobile testing for iOS and Android platforms including gestures, sensors, permissions, device fragmentation, and performance. Use when testing native apps, hybrid apps, or mobile web, ensuring quality across 1000+ device variants.
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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.
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n8n expression syntax validation, context-aware testing, common pitfalls detection, and performance optimization. Use when validating n8n expressions and data transformations.
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API contract testing, authentication flows, rate limit handling, and error scenario coverage for n8n integrations with external services. Use when testing n8n node integrations.
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Credential exposure detection, OAuth flow validation, API key management testing, and data sanitization verification for n8n workflows. Use when validating n8n workflow security.
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Webhook testing, schedule validation, event-driven triggers, and polling mechanism testing for n8n workflows. Use when testing how workflows are triggered.
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Comprehensive WCAG accessibility auditing with multi-tool testing (axe-core + pa11y + Lighthouse), TRUE PARALLEL execution with Promise.allSettled, graceful degradation, retry with backoff, context-aware remediation, learning integration, and video accessibility. Uses 3-tier browser cascade: Vibium → agent-browser → Playwright+Stealth.
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WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
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Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
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AI agents as force multipliers for quality work. Core skill for all 19 QE agents using PACTS principles.
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Comprehensive API testing patterns including contract testing, REST/GraphQL testing, and integration testing. Use when testing APIs or designing API test strategies.
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Migrate Agentic QE projects from v2 to v3 with zero data loss
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Browser automation for QE agents using Vibium (WebDriver BiDi) with assertions, batch execution, visual diff, prompt-injection scanning, and semantic intents. Use when any QE skill needs to drive a real browser — visual testing, accessibility audits, E2E flow verification, pentest validation, or exploratory testing.
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Unvarnished technical criticism combining Linus Torvalds' precision, Gordon Ramsay's standards, and James Bach's BS-detection. Use when code/tests need harsh reality checks, certification schemes smell fishy, or technical decisions lack rigor. No sugar-coating, just surgical truth about what's broken and why.
00
Write high-quality bug reports that get fixed quickly. Use when reporting bugs, training teams on bug reporting, or establishing bug report standards.
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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.
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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.
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Orchestrate quality engineering across CI/CD pipeline phases. Use when designing test strategies, planning quality gates, or implementing shift-left/shift-right testing.
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Knowledge graph-based code understanding with semantic search and 80% token reduction through intelligent context retrieval.
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Conduct context-driven code reviews focusing on quality, testability, and maintainability. Use when reviewing code, providing feedback, or establishing review practices.
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Cross-browser, cross-platform, and cross-device compatibility testing ensuring consistent experience across environments. Use when validating browser support, testing responsive design, or ensuring platform compatibility.
00
Regulatory compliance testing for GDPR, CCPA, HIPAA, SOC2, PCI-DSS and industry-specific regulations. Use when ensuring legal compliance, preparing for audits, or handling sensitive data.
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Apply effective software quality consultancy practices. Use when consulting, advising clients, or establishing consultancy workflows.
00
Apply context-driven testing principles where practices are chosen based on project context, not universal 'best practices'. Use when making testing decisions, questioning dogma, or adapting approaches to specific project needs.
00
Consumer-driven contract testing for APIs including REST, GraphQL, and event-driven systems with schema validation.
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Adversarial review court — a delivery (diff, PR, test suite, or artifact) is prosecuted by independent AI reviewers from different vendors, each with its own probe set, then a SHIP verdict must SURVIVE escalating deeper reviewers before it stands. Use when you want more than one reviewer's opinion on whether something is safe to ship: pre-merge gating, release go/no-go, catching a too-easy PASS, or any 'is this actually done?' decision where a shallow approval is a risk. Produces a signed court record with a three-valued verdict (SHIP / REMAND / BLOCK) and a human as final judge. Learns over time: reproduced charges and overturned SHIPs feed the QE flywheel.
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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.
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Database schema validation, data integrity testing, migration testing, transaction isolation, and query performance. Use when testing data persistence, ensuring referential integrity, or validating database migrations.
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Hypothesis-driven autonomous debugging with real command validation
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AI-powered defect prediction, pattern learning, and root cause analysis for proactive quality management.
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Orchestration skill for enterprise integration testing across SAP, middleware, WMS, and backend systems. Covers E2E enterprise flows, SAP-specific patterns (RFC, BAPI, IDoc, OData, Fiori), cross-system data validation, and enterprise quality gates.
00
Advanced exploratory testing techniques with Session-Based Test Management (SBTM), RST heuristics, and test tours. Use when planning exploration sessions, investigating bugs, or discovering unknown quality risks.
00
Comprehensive GitHub code review with AI-powered swarm coordination
00
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
00
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
00
Apply the Holistic Testing Model evolved with PACTS (Proactive, Autonomous, Collaborative, Targeted, Structured) principles. Use when designing comprehensive test strategies for Classical, AI-assisted, Agent based, or Agentic Systems building quality into the team, or implementing whole-team quality practices.
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Quality Engineering iteration loops for autonomous test improvement, coverage achievement, and quality gate compliance. Use when tests need to pass, coverage targets must be met, quality gates require compliance, or flaky tests need stabilization. Integrates with AQE v3 fleet agents for coordinated quality iteration.
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Transfer learning, metrics optimization, and continuous improvement for AI-powered QE agents.
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Internationalization (i18n) and localization (l10n) testing for global products including translations, locale formats, RTL languages, and cultural appropriateness. Use when launching in new markets or building multi-language products.
00
Enterprise middleware testing patterns for message routing, transformation, DLQ, protocol mediation, ESB error handling, and EIP patterns. Use when testing middleware layers, message brokers, ESBs, or integration buses.
00
Comprehensive mobile testing for iOS and Android platforms including gestures, sensors, permissions, device fragmentation, and performance. Use when testing native apps, hybrid apps, or mobile web, ensuring quality across 1000+ device variants.
00
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.
00
API contract testing, authentication flows, rate limit handling, and error scenario coverage for n8n integrations with external services. Use when testing n8n node integrations.
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Credential exposure detection, OAuth flow validation, API key management testing, and data sanitization verification for n8n workflows. Use when validating n8n workflow security.
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Webhook testing, schedule validation, event-driven triggers, and polling mechanism testing for n8n workflows. Use when testing how workflows are triggered.
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Comprehensive n8n workflow testing including execution lifecycle, node connection patterns, data flow validation, and error handling strategies. Use when testing n8n workflow automation applications.
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Observability and monitoring validation patterns for dashboards, alerting, log aggregation, APM traces, and SLA/SLO verification. Use when testing monitoring infrastructure, dashboard accuracy, alert rules, or metric pipelines.
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AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.
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Orchestrate security finding validation through graduated exploitation. 4-phase pipeline: recon (SAST/DAST), analysis (code review), validation (exploit proof), report (No Exploit, No Report gate). Eliminates false positives by proving exploitability.
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Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms
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Test application performance, scalability, and resilience. Use when planning load testing, stress testing, or optimizing system performance.
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Scope-aware GitHub PR review with user-friendly tone and trust tier validation
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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.
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Measure quality effectively with actionable metrics. Use when establishing quality dashboards, defining KPIs, or evaluating test effectiveness.
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Apply safe refactoring patterns to improve code structure without changing behavior. Use when cleaning up code, reducing technical debt, or improving maintainability.
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Strategic regression testing with test selection, impact analysis, and continuous regression management. Use when verifying fixes don't break existing functionality, planning regression suites, or optimizing test execution for faster feedback.
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End-to-end npm release workflow with verification gates and hardcoded-version protection
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Requirements traceability, acceptance criteria validation, and BDD scenario management for complete requirements coverage.
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Focus testing effort on highest-risk areas using risk assessment and prioritization. Use when planning test strategy, allocating testing resources, or making coverage decisions.
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Security auditing, vulnerability scanning, and compliance validation for OWASP, SOC2, GDPR, and other standards.
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Test for security vulnerabilities using OWASP principles. Use when conducting security audits, testing auth, or implementing security practices.
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Security-first visual testing combining URL validation, PII detection, and visual regression with parallel viewport support. Use when testing web applications that handle sensitive data, need visual regression coverage, or require WCAG accessibility compliance.
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James Bach's HTSM Product Factors (SFDIPOT) analysis for comprehensive test strategy generation. Use when analyzing requirements, epics, or user stories to generate prioritized test ideas across Structure, Function, Data, Interfaces, Platform, Operations, and Time dimensions.
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Evidence-based investigative code review using deductive reasoning to determine what actually happened versus what was claimed. Use when verifying implementation claims, investigating bugs, validating fixes, or conducting root cause analysis. Elementary approach to finding truth through systematic observation.
00
Move testing activities earlier in the development lifecycle to catch defects when they're cheapest to fix. Use when implementing TDD, CI/CD, or early quality practices.
00
Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis. Use when designing test strategies, conducting test retrospectives, analyzing test failures, evaluating testing approaches, or facilitating testing discussions. Each hat provides a distinct testing perspective: facts (White), risks (Black), benefits (Yellow), creativity (Green), emotions (Red), and process (Blue).
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Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.
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SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
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Apply London (mock-based) and Chicago (state-based) TDD schools. Use when practicing test-driven development or choosing testing style for your context.
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Write clear, engaging technical content from real experience. Use when writing blog posts, documentation, tutorials, or technical articles.
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Design and implement effective test automation with proper pyramid, patterns, and CI/CD integration. Use when building automation frameworks or improving test efficiency.
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Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage.
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Test environment provisioning, infrastructure as code for testing, Docker/Kubernetes for test environments, service virtualization, and cost optimization. Use when managing test infrastructure, ensuring environment parity, or optimizing testing costs.
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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.
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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 Playwright.
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Transform passive 'Verify X' test descriptions into active, observable test actions. Use when test ideas lack specificity, use vague language, or fail quality validation. Converts to action-verb format for clearer, more testable descriptions.
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Advanced test reporting, quality dashboards, predictive analytics, trend analysis, and executive reporting for QE metrics. Use when communicating quality status, tracking trends, or making data-driven decisions.
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AI-powered testability assessment using 10 principles of intrinsic testability with Playwright and optional Vibium integration. Evaluates web applications against Observability, Controllability, Algorithmic Simplicity, Transparency, Stability, Explainability, Unbugginess, Smallness, Decomposability, and Similarity. Use when assessing software testability, evaluating test readiness, identifying testability improvements, or generating testability reports.
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Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
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Visual regression testing, responsive design validation, and WCAG accessibility compliance testing.
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Advanced visual regression testing with pixel-perfect comparison, AI-powered diff analysis, responsive design validation, and cross-browser visual consistency. Use when detecting UI regressions, validating designs, or ensuring visual consistency.
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Warehouse Management System testing patterns for inventory operations, pick/pack/ship workflows, wave management, EDI X12/EDIFACT compliance, RF/barcode scanning, and WMS-ERP integration. Use when testing WMS platforms (Blue Yonder, Manhattan, SAP EWM).
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Apply XP practices including pair programming, ensemble programming, continuous integration, and sustainable pace. Use when implementing agile development practices, improving team collaboration, or adopting technical excellence practices.
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Tracks quality metrics including defect density, test effectiveness ratio, DORA metrics, and mean time to detection. Use when establishing quality dashboards, defining KPIs, evaluating test suite effectiveness, or reporting quality trends to stakeholders.
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Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
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Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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Apply safe refactoring patterns to improve code structure without changing behavior. Use when cleaning up code, reducing technical debt, or improving maintainability.
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Strategic regression testing with test selection, impact analysis, and continuous regression management. Use when verifying fixes don't break existing functionality, planning regression suites, or optimizing test execution for faster feedback.
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Ruflo is a multi-agent orchestration platform for AI coding agents (Claude Code, Cursor, Codex, Copilot, Gemini, Amp, +12 more). Use this skill when the user wants to (1) install/init ruflo in a project, (2) run multi-agent swarms with hierarchical coordination, (3) use ruflo's 314+ MCP tools for memory, routing, hooks, sub-agents, or workflows, (4) check ruflo status/version/doctor health, or (5) discover which of ruflo's 30+ plugins fits their task.
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Scans for security vulnerabilities including XSS, SQL injection, CSRF, and auth flaws using OWASP Top 10 methodology. Use when conducting SAST/DAST scans, auditing authentication flows, testing authorization rules, or implementing security test automation.
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Security-first visual testing combining URL validation, PII detection, and visual regression with parallel viewport support. Use when testing web applications that handle sensitive data, need visual regression coverage, or require WCAG accessibility compliance.
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Use when working on security-sensitive code to catch secrets, eval(), innerHTML, and other dangerous patterns before they're written. Activate with /security-watch for real-time security scanning.
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James Bach's HTSM Product Factors (SFDIPOT) analysis for comprehensive test strategy generation. Use when analyzing requirements, epics, or user stories to generate prioritized test ideas across Structure, Function, Data, Interfaces, Platform, Operations, and Time dimensions.
00
Evidence-based investigative code review using deductive reasoning to determine what actually happened versus what was claimed. Use when verifying implementation claims, investigating bugs, validating fixes, or conducting root cause analysis. Elementary approach to finding truth through systematic observation.
00
Apply Edward de Bono's Six Thinking Hats methodology to software testing for comprehensive quality analysis. Use when designing test strategies, conducting test retrospectives, analyzing test failures, evaluating testing approaches, or facilitating testing discussions. Each hat provides a distinct testing perspective: facts (White), risks (Black), benefits (Yellow), creativity (Green), emotions (Red), and process (Blue).
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Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.
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Use when reviewing which QE skills are being used, finding undertriggering skills, or analyzing skill effectiveness. Shows usage patterns and recommendations.
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SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration
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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
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Use when enforcing TDD discipline — blocks writing production code unless a failing test exists first. Activate with /strict-tdd to enable session-scoped Red-Green-Refactor guardrail.
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Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows
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Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.
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Apply London (mock-based) and Chicago (state-based) TDD schools. Use when practicing test-driven development or choosing testing style for your context.
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Write clear, engaging technical content from real experience. Use when writing blog posts, documentation, tutorials, or technical articles.
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Design and implement effective test automation with proper pyramid, patterns, and CI/CD integration. Use when building automation frameworks or improving test efficiency.
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Strategic test data generation, management, and privacy compliance. Use when creating test data, handling PII, ensuring GDPR/CCPA compliance, or scaling data generation for realistic testing scenarios.
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Systematic test design with boundary value analysis, equivalence partitioning, decision tables, state transition testing, and combinatorial testing. Use when designing comprehensive test cases, reducing redundant tests, or ensuring systematic coverage.
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Test environment provisioning, infrastructure as code for testing, Docker/Kubernetes for test environments, service virtualization, and cost optimization. Use when managing test infrastructure, ensuring environment parity, or optimizing testing costs.
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Use when a test is failing and you need to determine root cause: is it flaky, an environment issue, or a real regression? Traces failure from symptom to fix.
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Transform passive 'Verify X' test descriptions into active, observable test actions. Use when test ideas lack specificity, use vague language, or fail quality validation. Converts to action-verb format for clearer, more testable descriptions.
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Use when querying test history, analyzing flakiness rates, tracking MTTR, or building quality trend dashboards from test execution data.
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Advanced test reporting, quality dashboards, predictive analytics, trend analysis, and executive reporting for QE metrics. Use when communicating quality status, tracking trends, or making data-driven decisions.
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AI-powered testability assessment using 10 principles of intrinsic testability with Playwright and optional Vibium integration. Evaluates web applications against Observability, Controllability, Algorithmic Simplicity, Transparency, Stability, Explainability, Unbugginess, Smallness, Decomposability, and Similarity. Use when assessing software testability, evaluating test readiness, identifying testability improvements, or generating testability reports.
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CLI modernization and hooks system enhancement for claude-flow v3. Implements interactive prompts, command decomposition, enhanced hooks integration, and intelligent workflow automation.
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Core module implementation for claude-flow v3. Implements DDD domains, clean architecture patterns, dependency injection, and modular TypeScript codebase with comprehensive testing.
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Domain-Driven Design architecture for claude-flow v3. Implements modular, bounded context architecture with clean separation of concerns and microkernel pattern.
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Deep agentic-flow@alpha integration implementing ADR-001. Eliminates 10,000+ duplicate lines by building claude-flow as specialized extension rather than parallel implementation.
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MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.
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Advanced visual regression testing with pixel-perfect comparison, AI-powered diff analysis, responsive design validation, and cross-browser visual consistency. Use when detecting UI regressions, validating designs, or ensuring visual consistency.
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Warehouse Management System testing patterns for inventory operations, pick/pack/ship workflows, wave management, EDI X12/EDIFACT compliance, RF/barcode scanning, and WMS-ERP integration. Use when testing WMS platforms (Blue Yonder, Manhattan, SAP EWM).
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Apply XP practices including pair programming, ensemble programming, continuous integration, and sustainable pace. Use when implementing agile development practices, improving team collaboration, or adopting technical excellence practices.
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