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@qualixar

qualixar

Qualixar

Advancing Agent Development Through Research


10 research projects. 4 peer-reviewed publications. One mission.

Website ORCID


The Problem

2.4 million AI agents deployed in production. Zero standard methodology for verifying they work correctly. Agents leak data, exceed budgets, drift from intended behavior, and fail in ways no one predicted.

Every framework helps you build agents. We're working on making them reliable.

What We're Building

An open-source research initiative spanning the complete agent development lifecycle:

  • Behavioral specification & verification
  • Security validation & supply chain analysis
  • Token-efficient statistical testing
  • Privacy-preserving memory architectures
  • Communication fidelity benchmarks
  • Chaos engineering & resilience testing

10 projects. Each backed by formal methods, mathematical proofs, and peer-reviewed research.

Publications

Paper Venue Year
Agent Behavioral Contracts: Formal Specification and Runtime Enforcement arXiv:2602.22302 2026
SkillFortify: Formal Verification for AI Agent Skill Security arXiv:2603.00195 2026
Token-Efficient Regression Testing for Non-Deterministic AI Agent Workflows arXiv:2603.02601 2026
Privacy-Preserving Multi-Agent Memory with Bayesian Trust Defense arXiv:2603.02240 2026

More papers in preparation. Conference targets: ASE 2026, NeurIPS 2026, AAMAS 2027, ICSE 2027.

Philosophy

  • Every project is backed by published research — not blog posts.
  • Every tool is open-source and framework-agnostic.
  • We solve problems with math and proofs — not marketing.

An independent research initiative by Varun Pratap Bhardwaj

We don't just identify problems in agent development. We solve them.

Popular repositories Loading

  1. skillfortify skillfortify Public

    First formal security scanner for AI agent skills & plugins. Static analysis, supply chain verification, SBOM generation. 22 frameworks supported including MCP, LangChain, CrewAI.

    Python 6

  2. agentassay agentassay Public

    Token-efficient stochastic testing for AI agents. 5-20x cost reduction. 10 framework adapters. Paper: arXiv:2603.02601

    Python 1

  3. .github .github Public

    Qualixar organization profile

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