Meta Agents Research Environments
Meta Agents Research Environments is a comprehensive platform designed to evaluate AI agents in dynamic, realistic scenarios. Unlike static benchmarks, this platform introduces evolving environments where agents must adapt their strategies as new information becomes available, mirroring real-world challenges.
Meta Agents Research Environments scores 4.5/10 (Emerging) in Benchmarks & Resources.
Kind Toolkit Language Python License MIT Stars 523★ Repo facebookresearch/meta-agents-research-environments
Quality
Emerging 4.5
Adoption 18
Activity 42
Maturity 78
Community 22
Capability 50
Show the math
Overall 4.5/10
value = 4.5/10
score = value
Adoption 2.6/10
value = 18/100
score = 1 + 9 * value / 100
Activity 4.7/10
value = 41.5/100
score = 1 + 9 * value / 100
Maturity 8/10
value = 78.1/100
score = 1 + 9 * value / 100
Community 3/10
value = 22/100
score = 1 + 9 * value / 100
Capability 5.5/10
value = 50/100
score = 1 + 9 * value / 100
Key metrics
523★ GitHub stars
9/90d Recent commits
2 devs/90d Recent contributors
10mo Project age
active Last commit
Gotchas
No gotchas documented yet. Contribute one if you know a constraint we missed.
Labels
- New project
New (10mo)
Created within the last year — promising but less battle-tested.
benchmark agents environment evaluation