Regression testing for AI agents. Snapshot behavior, diff tool calls, catch regressions in CI. Works with LangGraph, CrewAI, OpenAI, Anthropic.

Mathematical benchmark exposing the massive performance gap between real agents and LLM wrappers. Rigorous multi-dimensional evaluation with statistical validation (95% CI, Cohen's h) and reproducible methodology. Separates architectural theater from real systems through stress testing, network resilience, and failure analysis.

TraitBasis applied to TauBench

Deterministic runtime for agent evaluation

A curated collection of the world’s most advanced benchmark datasets for evaluating Large Language Model (LLM) Agents.

University for AI agents. 92 courses, 4400+ scenarios, any model via OpenRouter. Auto-training loops generate per-model SKILL.md documents. Works with Claude Code, OpenClaw, Cursor, Windsurf. No fine-tuning required.

🧠 Discover and evaluate advanced benchmark datasets for Large Language Model agents to enhance performance assessment in real-world tasks.

AI Arena is a competitive evaluation framework where multiple AI agents answer the same set of questions under identical conditions. Their performance is scored, ranked, and tracked over time using two complementary metrics AIQ and ELO

A community catalog of autonomous agents and bundles certified by passing TraceCore deterministic episode runs in public CI

🤖 Benchmark AI agent capabilities, bridging the gap between hype and reality with clear metrics and insights for informed development decisions.