Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
proffesor-for-testing avatar

Qe Learning Optimization

proffesor-for-testing/agentic-qe

  • 32 installs
  • 433 repo stars
  • Updated August 4, 2026
  • proffesor-for-testing/agentic-qe

qe learning optimization is a Claude Code skill for ai & agent building.

About

qe learning optimization is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • qe learning optimization
  • AI & Agent Building
  • AI-coding skill

Qe Learning Optimization by the numbers

  • 32 all-time installs (skills.sh)
  • Ranked #9,069 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill qe-learning-optimization

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs32
repo stars★ 433
Last updatedAugust 4, 2026
Repositoryproffesor-for-testing/agentic-qe ↗

How do I helps with ai & agent building tasks.?

Helps with ai & agent building tasks.

Who is it for?

Best when you're working on ai & agent building and need structured help with qe learning optimization.

Skip if: Teams with no ai & agent building needs, or anyone wanting a generic chat assistant without this specific workflow.

When should I use this skill?

When you need to helps with ai & agent building tasks., or when qe learning optimization is a claude code skill for ai & agent building.

What you get

Structured output aligned to qe learning optimization: qe learning optimization, AI & Agent Building.

Files

SKILL.mdMarkdownGitHub ↗

QE Learning Optimization

Purpose

Guide the use of v3's learning optimization capabilities including transfer learning between agents, hyperparameter tuning, A/B testing, and continuous performance improvement.

Activation

  • When optimizing agent performance
  • When transferring knowledge between agents
  • When tuning learning parameters
  • When running A/B tests
  • When analyzing learning metrics

Quick Start

# Transfer knowledge between agents
aqe learn transfer --from jest-generator --to vitest-generator

# Tune hyperparameters
aqe learn tune --agent defect-predictor --metric accuracy

# Run A/B test
aqe learn ab-test --hypothesis "new-algorithm" --duration 7d

# View learning metrics
aqe learn metrics --agent test-generator --period 30d

Agent Workflow

// Transfer learning
Task("Transfer test patterns", `
  Transfer learned patterns from Jest test generator to Vitest:
  - Map framework-specific syntax
  - Adapt assertion styles
  - Preserve test structure patterns
  - Validate transfer accuracy
`, "qe-transfer-specialist")

// Metrics optimization
Task("Optimize prediction accuracy", `
  Tune defect-predictor agent:
  - Analyze current performance metrics
  - Run Bayesian hyperparameter search
  - Validate improvements on holdout set
  - Deploy if accuracy improves >5%
`, "qe-metrics-optimizer")

Learning Operations

1. Transfer Learning

await transferSpecialist.transfer({
  source: {
    agent: 'qe-jest-generator',
    knowledge: ['patterns', 'heuristics', 'optimizations']
  },
  target: {
    agent: 'qe-vitest-generator',
    adaptations: ['framework-syntax', 'api-differences']
  },
  strategy: 'fine-tuning',
  validation: {
    testSet: 'validation-samples',
    minAccuracy: 0.9
  }
});

2. Hyperparameter Tuning

await metricsOptimizer.tune({
  agent: 'defect-predictor',
  parameters: {
    learningRate: { min: 0.001, max: 0.1, type: 'log' },
    batchSize: { values: [16, 32, 64, 128] },
    patternThreshold: { min: 0.5, max: 0.95 }
  },
  optimization: {
    method: 'bayesian',
    objective: 'accuracy',
    trials: 50,
    parallelism: 4
  }
});

3. A/B Testing

await metricsOptimizer.abTest({
  hypothesis: 'ML pattern matching improves test quality',
  variants: {
    control: { algorithm: 'rule-based' },
    treatment: { algorithm: 'ml-enhanced' }
  },
  metrics: ['test-quality-score', 'generation-time'],
  traffic: {
    split: 50,
    minSampleSize: 1000
  },
  duration: '7d',
  significance: 0.05
});

4. Feedback Loop

await metricsOptimizer.feedbackLoop({
  agent: 'test-generator',
  feedback: {
    sources: ['user-corrections', 'test-results', 'code-reviews'],
    aggregation: 'weighted',
    frequency: 'real-time'
  },
  learning: {
    strategy: 'incremental',
    validationSplit: 0.2,
    earlyStoppingPatience: 5
  }
});

Learning Metrics Dashboard

interface LearningDashboard {
  agent: string;
  period: DateRange;
  performance: {
    current: MetricValues;
    trend: 'improving' | 'stable' | 'declining';
    percentile: number;
  };
  learning: {
    samplesProcessed: number;
    patternsLearned: number;
    improvementRate: number;
  };
  experiments: {
    active: Experiment[];
    completed: ExperimentResult[];
  };
  recommendations: {
    action: string;
    expectedImpact: number;
    confidence: number;
  }[];
}

Cross-Framework Transfer

transfer_mappings:
  jest_to_vitest:
    syntax:
      "describe": "describe"
      "it": "it"
      "expect": "expect"
      "jest.mock": "vi.mock"
      "jest.fn": "vi.fn"
    patterns:
      - mock-module
      - async-testing
      - snapshot-testing

  mocha_to_jest:
    syntax:
      "describe": "describe"
      "it": "it"
      "chai.expect": "expect"
      "sinon.stub": "jest.fn"
    adaptations:
      - assertion-style
      - hook-naming

Continuous Improvement

await learningOptimizer.continuousImprovement({
  agents: ['test-generator', 'coverage-analyzer', 'defect-predictor'],
  schedule: {
    metricCollection: 'hourly',
    tuning: 'weekly',
    majorUpdates: 'monthly'
  },
  thresholds: {
    degradationAlert: 5,  // percent
    improvementTarget: 2,  // percent per week
  },
  automation: {
    autoTune: true,
    autoRollback: true,
    requireApproval: ['major-changes']
  }
});

Pattern Learning

await patternLearner.learn({
  sources: {
    codeExamples: 'examples/**/*.ts',
    testExamples: 'tests/**/*.test.ts',
    userFeedback: 'feedback/*.json'
  },
  extraction: {
    syntacticPatterns: true,
    semanticPatterns: true,
    contextualPatterns: true
  },
  storage: {
    vectorDB: 'agentdb',
    versioning: true
  }
});

Coordination

Primary Agents: qe-transfer-specialist, qe-metrics-optimizer, qe-pattern-learner Coordinator: qe-learning-coordinator Related Skills: qe-test-generation, qe-defect-intelligence

Related skills

mattpocockSetup Matt Pocock SkillsScaffold the per-repo configuration that Matt Pocock’s engineering agent skills rely on so they understand the issue tracker, triage labels, and domain documentation la495k196kopen.feishu.cnLark AppsConnect Claude, Cursor or custom agents directly to Lark (Feishu) for messaging, document automation, approval workflows and enterprise data access.402kjuliusbrusseeCavemanSlash token usage by roughly 75% while keeping every technical detail intact when working with Claude Code, Cursor or similar agents.391k94.7klarksuiteLark Skill MakerQuickly turn any Lark/Feishu OpenAPI call or multi-step workflow into a reusable agent skill with its own SKILL.md.386k16kxixu-meRunning Claude Code Via Litellm CopilotRun Claude Code at a fraction of the cost by routing requests through LiteLLM to the GitHub Copilot Chat API.270k72runcomfy-comCodex PetGenerate a complete Codex Pet spritesheet and metadata from one reference image without needing an OpenAI key or Codex Pro.246k10

FAQ

What does qe learning optimization do?

qe learning optimization is a Claude Code skill for ai & agent building.

When should I use qe learning optimization?

When you need to helps with ai & agent building tasks., or when qe learning optimization is a claude code skill for ai & agent building.

What are the main capabilities?

qe learning optimization; AI & Agent Building; AI-coding skill.

AI & Agent Buildingagents
Browse by category
AI & AgentsFrontend & DesignBackend & DataDev ToolsAutomationTesting & ReviewSecurityMonitoring & CloudDocs & Planning
Design & frontend
Design systemsAnimation & motionAccessibility (a11y)CSS & TailwindUI designUXDesign to codeshadcn/uiLanding pagesBest design skills
Most searched skills
find-skillscavemanfrontend-designbrainstormingsystematic-debuggingstop-slopemil-design-engui-ux-pro-maxkarpathy-guidelinesweb-design-guidelinesreact-best-practicesgrill-meimprovemicrosoft-foundryagent-browser
Browse all listings
All agent skillsAll MCP serversAll marketplacesAll plugins

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.