ruflo-cost-tracker
claudeToken usage tracking, model cost attribution per agent, budget alerts, and optimization recommendations
24 skills · 1 command · 1 agent · hooks
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
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.
chaos-engineering-resilienceChaos 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-testingTest 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-resilienceInjects 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-analysisAnalyzes 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-assessmentEvaluates 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-executionOrchestrates 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-generationGenerates 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-testingFocus 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-chicagoApply London (mock-based) and Chicago (state-based) TDD schools. Use when practicing test-driven development or choosing testing style for your context.
/agentic-qe-fleet:aqe-analyzeAnalyze test coverage, identify gaps, and optimize coverage strategy using sublinear algorithms
/agentic-qe-fleet:aqe-benchmarkRun performance benchmarks and compare against baselines
/agentic-qe-fleet:aqe-chaosRun chaos testing scenarios to validate system resilience and fault tolerance
/agentic-qe-fleet:aqe-costsDisplay inference cost analysis and savings from local vs cloud providers
/agentic-qe-fleet:aqe-executeExecute test suites with parallel orchestration, retry logic, and real-time reporting
/agentic-qe-fleet:aqe-fleet-statusDisplay comprehensive fleet health, agent status, and coordination metrics
/agentic-qe-fleet:aqe-generateGenerate comprehensive test suites using AI-powered analysis and sublinear optimization
/agentic-qe-fleet:aqe-optimizeOptimize test suites using sublinear algorithms to maximize coverage while minimizing test count and execution time
/agentic-qe-fleet:aqe-reportGenerate comprehensive quality engineering reports with metrics, trends, and actionable insights
qe-chaos-engineerChaos engineering specialist for controlled fault injection, resilience testing, and system weakness discovery
qe-coverage-specialistO(log n) sublinear coverage analysis with risk-weighted gap detection and HNSW vector indexing
qe-flaky-hunterFlaky test detection and remediation with pattern recognition and auto-stabilization
qe-fleet-commanderFleet management with agent lifecycle, workload distribution, and cross-domain coordination at scale
qe-performance-testerPerformance testing with load, stress, endurance testing and regression detection
qe-quality-gateQuality gate enforcement with configurable thresholds, policy validation, and AI-powered deployment decisions
qe-regression-analyzerRegression risk analysis with intelligent test selection, historical analysis, and change impact scoring
qe-requirements-validatorRequirements validation with testability analysis, BDD scenario generation, and acceptance criteria validation
qe-security-scannerComprehensive security scanning with SAST, DAST, dependency scanning, and secrets detection
qe-tdd-specialistTDD Red-Green-Refactor specialist for test-driven development with London and Chicago school support
qe-test-architectAI-powered test generation with sublinear optimization, multi-framework support, and self-learning capabilities
agentic-qeruns: npx -y [email protected] mcp
Token usage tracking, model cost attribution per agent, budget alerts, and optimization recommendations
24 skills · 1 command · 1 agent · hooks
Tenant-isolated AI teams that plan work, coordinate tasks, recall approved context, and return evidence-backed results
6 skills · 6 commands · 4 agents · 1 MCP server
Agent runtimes — local WASM-sandboxed agents (rvagent) + Anthropic Claude Managed Agents (cloud); one interface, local-vs-cloud backends
5 skills · 2 commands · 9 agents
MetaHarness integration — surfaces score/genome/mint/mcp-scan/threat-model via skills; pairs with @metaharness/router (ADR-148/149) for cost-optimal model routing; honors ADR-150 optional-augmentation constraint
13 skills · 1 command · 1 agent · hooks
Visual workflow automation with templates, orchestration, and lifecycle management
5 skills · 8 commands · 3 agents
Neural trading strategies — self-learning LSTM/Transformer/N-BEATS models with Rust/NAPI backtesting
9 skills · 1 command · 4 agents
Matt Pocock's agent skills for real engineering (grilling, spec/ticket flows, TDD, code review, domain modelling and more).
39 skills
Core skills library for Claude Code: TDD, debugging, collaboration patterns, and proven techniques
15 skills · hooks
Harness-native ECC operator layer - 71 agents, 314 skills, 98 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
200 skills · 98 commands · 71 agents · 1 MCP server · hooks
Collection of example skills demonstrating various capabilities including skill creation, MCP building, visual design, algorithmic art, internal communications, web testing, artifact building, Slack GIFs, and theme styling
19 skills
Comprehensive PR review agents specializing in comments, tests, error handling, type design, code quality, and code simplification
1 command · 6 agents
Production-grade engineering skills covering every phase of software development: spec, plan, build, verify, review, and ship.
25 skills · 4 agents
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