René's URL Explorer Experiment


Title: AgentContract-Bench v2 — 293 Benchmark Scenarios

Open Graph Title: AgentContract-Bench v2 — 293 Benchmark Scenarios

X Title: AgentContract-Bench v2 — 293 Benchmark Scenarios

Description: AgentContract-Bench v2: 293 scenarios across 12 domains with 100% pass rate. Live LLM results from GPT-5.3, Claude Sonnet 4.6, and Mistral-Large-3.

Open Graph Description: AgentContract-Bench v2: 293 scenarios across 12 domains with 100% pass rate. Live LLM results from GPT-5.3, Claude Sonnet 4.6, and Mistral-Large-3.

X Description: AgentContract-Bench v2: 293 scenarios across 12 domains with 100% pass rate. Live LLM results from GPT-5.3, Claude Sonnet 4.6, and Mistral-Large-3.

Keywords:

Mail addresses
varun.pratap.bhardwaj@gmail.com

Opengraph URL: https://agentassert.com/benchmarks/

X: @varunPbhardwaj

direct link

Domain: agentassert.com


Hey, it has json ld scripts:
{"@context":"https://schema.org","@type":"WebPage","name":"AgentContract-Bench v2 — 293 Benchmark Scenarios","description":"AgentContract-Bench v2: 293 scenarios across 12 domains with 100% pass rate. Live LLM results from GPT-5.3, Claude Sonnet 4.6, and Mistral-Large-3.","url":"https://agentassert.com/benchmarks/","inLanguage":"en","isPartOf":{"@type":"WebSite","name":"agentAssert","url":"https://agentassert.com/"},"author":{"@type":"Person","name":"Varun Pratap Bhardwaj"}}
{"@context":"https://schema.org","@type":"Organization","name":"Qualixar","url":"https://qualixar.com","logo":"https://agentassert.com/brand/logo-mark.svg","sameAs":["https://www.linkedin.com/in/varun-pratap-bhardwaj-7ab63742/","https://x.com/varunPbhardwaj"],"founder":{"@type":"Person","name":"Varun Pratap Bhardwaj"}}
{"@context":"https://schema.org","@type":"SoftwareApplication","name":"agentAssert","applicationCategory":"DeveloperApplication","operatingSystem":"Any","description":"Agent Behavioral Contracts: Formal Specification and Runtime Enforcement for Autonomous AI Agents","author":{"@type":"Person","name":"Varun Pratap Bhardwaj"},"offers":{"@type":"Offer","price":"0","priceCurrency":"USD","description":"Patent Pending — Request Access"}}
{"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://agentassert.com/"},{"@type":"ListItem","position":2,"name":"Benchmarks","item":"https://agentassert.com/benchmarks"}]}
{"@context":"https://schema.org","@type":"FAQPage","mainEntity":[{"@type":"Question","name":"What is AgentContract-Bench v2?","acceptedAnswer":{"@type":"Answer","text":"AgentContract-Bench v2 is a comprehensive benchmark suite with 293 scenarios across 12 domains for evaluating AI agent behavioral contract compliance. It achieves 100% pass rate with the agentAssert framework."}},{"@type":"Question","name":"Which LLMs have been tested?","acceptedAnswer":{"@type":"Answer","text":"Live results are available for GPT-5.3 (Theta=0.688), Claude Sonnet 4.6 (Theta=0.823), and Mistral-Large-3 (Theta=0.813). All models were evaluated across the full 293-scenario suite."}},{"@type":"Question","name":"How are benchmark scores calculated?","acceptedAnswer":{"@type":"Answer","text":"The aggregate compliance score Theta is computed across all contract constraints (preconditions, invariants, guarantees, and recovery) weighted by domain-specific importance. A higher Theta indicates better behavioral contract adherence."}}]}

authorVarun Pratap Bhardwaj
theme-color#050508
revised2026-04-08
date2026-02-27
og:imagehttps://agentassert.com/og-image.png
og:image:width1200
og:image:height630
og:typewebsite
og:localeen_US
og:site_nameagentAssert
twitter:cardsummary_large_image
twitter:imagehttps://agentassert.com/og-image.png
twitter:urlhttps://agentassert.com/benchmarks/
astro-view-transitions-enabledtrue
astro-view-transitions-fallbackanimate

Links:

agentAssert https://agentassert.com/
Homehttps://agentassert.com/
Getting Startedhttps://agentassert.com/getting-started
Benchmarkshttps://agentassert.com/benchmarks
Contractshttps://agentassert.com/contracts
Researchhttps://agentassert.com/research
Abouthttps://agentassert.com/about
Bloghttps://qualixar.com/research/blog
Contacthttps://www.varunpratap.com/contact
Read the Paper https://arxiv.org/abs/2602.22302
Homehttps://agentassert.com/
Getting Startedhttps://agentassert.com/getting-started
Benchmarkshttps://agentassert.com/benchmarks
Contractshttps://agentassert.com/contracts
Researchhttps://agentassert.com/research
Abouthttps://agentassert.com/about
Bloghttps://qualixar.com/research/blog
Contacthttps://www.varunpratap.com/contact
Read the Paper https://arxiv.org/abs/2602.22302
View Benchmarks on GitHubhttps://github.com/qualixar/agentassert-abc/tree/main/benchmarks
Read the Paperhttps://agentassert.com/research
Overview https://agentassert.com/
Full Paper ↗ https://arxiv.org/abs/2602.22302
Research Details https://agentassert.com/research
About the Author https://agentassert.com/about
Qualixar Platform ↗ https://qualixar.com
SuperLocalMemory ↗ https://superlocalmemory.com
SkillFortify ↗ https://superlocalmemory.com/skillfortify
AgentAssay ↗ https://github.com/qualixar/agentassay
SLM Mesh ↗ https://github.com/qualixar/slm-mesh
Research & Courses ↗ https://qualixar.com/learn
All Papers ↗ https://qualixar.com/research/papers
arXiv:2602.22302 ↗ https://arxiv.org/abs/2602.22302
Zenodo Archive ↗ https://doi.org/10.5281/zenodo.18775393
ORCID ↗ https://orcid.org/0009-0002-8726-4289
Research Inquiry https://agentassert.com/contact
LinkedIn ↗ https://www.linkedin.com/in/varun-pratap-bhardwaj-7ab63742/
Qualixarhttps://qualixar.com

Viewport: width=device-width, initial-scale=1.0

Robots: index, follow, max-video-preview:-1, max-image-preview:large, max-snippet:-1


URLs of crawlers that visited me.