AgentBeats
Agent-based evaluation framework where AI judges assess other agents through standardized protocols
About
AgentBeats is an open research framework that uses AI agents as judges to evaluate other AI agents. Unlike traditional static benchmarks, it provides a dynamic, agent-agnostic assessment interface where judge agents evaluate performance through standardized protocols. Designed for reproducible benchmarking across different agent architectures, enabling researchers to compare autonomous systems objectively. Published as academic research with full methodology transparency.
Details
| Type | |
| Integrations | |
| Language |
Tags
Quick Info
- Organization
- Research
- Pricing
- open-source
- Free Tier
- Yes
- Updated
- Jun 14, 2026
Also in Dev Tools
Crawl4AI
Open-source web crawler optimized for LLMs and AI agents — 62K+ stars
Firecrawl
Web scraping API built for LLMs — turn any website into LLM-ready data — 89K+ stars
Headroom Context Optimization
Reduce LLM API costs by 50-90% through advanced context compression