vijayarjun7

AI Qe Agent — Testing skill for Claude Code

Testing community

AI QE Agent with LLM Evaluation Layer — catches hallucinations, monitors chain consistency, self-heals Playwright selectors.

How to install AI Qe Agent

This entry records only its repository, not the path inside it, so there is no exact command to give. Open vijayarjun7/ai-qe-agent and copy the folder into ~/.claude/skills/, or the file into ~/.claude/agents/.

What AI Qe Agent does

AI QE Agent with LLM Evaluation Layer — catches hallucinations, monitors chain consistency, self-heals Playwright selectors. Claude + TruLens + LangSmith + Pinecone

Alternatives in Testing

  • GAAI Framework — 95+ Drop-in governance layer (.gaai/ folder) -- backlog authorization, cross-session memory, decision tracking 113 ★
  • Relentless.Analyze — Analyze consistency across spec, plan, tasks, and checklist 97 ★
  • Aod.Analyze — Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.m 89 ★

README

AI QE Agent

**End-to-End AI-Driven Quality Engineering Pipeline — Powered by Playwright + Claude AI**

![Claude](https://img.shields.io/badge/Claude-Sonnet--4--6-orange?logo=anthropic) ![TypeScript](https://img.shields.io/badge/TypeScript-E2E%20Tests-blue?logo=typescript) ![Python](https://img.shields.io/badge/Python-MLOps%20Stack-green?logo=python) ![TruLens](https://img.shields.io/badge/TruLens-Monitoring-purple) ![LangSmith](https://img.shields.io/badge/LangSmith-Tracing-red) ![MLflow](https://img.shields.io/badge/MLflow-Experiments-blue) ![Pinecone](https://img.shields.io/badge/Pinecone-Vector%20Search-teal) ![HuggingFace](https://img.shields.io/badge/🤗%20Demo-Live-yellow) ![Stars](https://img.shields.io/github/stars/vijayarjun7/ai-qe-agent?style=social)

AI QE Agent is a TypeScript automation framework that demonstrates a complete AI-driven QE pipeline: **AI writes the app → AI writes & reviews manual tests → AI generates & reviews automation scripts → Self-healing on selector/requirement changes.**


🧪 LLM Evaluation Layer

Built a custom **LLM-as-Judge eval suite** on top of the pipeline — Claude evaluating Claude's own outputs across 4 dimensions.

Eval Results (First Production Run)

Agent Quality Faithfulness Hallucination Chain Compat
ManualTestGenerator 0.87 ✅ 0.0 ⚠️ None 0.0 ⚠️
QAReviewAgent 0.80 ✅ 1.0 ✅ None 0.0 ⚠️
AutomationScriptGenerator 0.94 ✅ 1.0 ✅ Detected 🔴 —
SelfHealingAgent 1.0 ✅ 0.0 ⚠️ None —

**Avg Quality Score: 0.902 | Hallucinations caught: 2 | Pipeline breaks: 2**

Observability Stack

Tool Purpose
TruLens Real-time eval dashboard (4 metrics per agent)
LangSmith Production API tracing (latency, tokens, cost)
MLflow Experiment tracking + run comparison
Pinecone Semantic test deduplication (0.85 threshold)

Run the eval suite

npm run eval                    # TypeScrip