How fast evolvent-ai/RSIGym is gaining stars, and where it lands on Trendshift and GitHub Trending
Activity and trending
Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending
Oct 7 – Oct 22, 2026
Stars +117in 16 days
01020
20
Forks +4in 16 days
01
1
Merged PRs 0in 16 days
01
Trendshift Trendingwhere the repository ranked each day it made the top 25
Not in the Trendshift top 25 in this period
Oct 7Oct 9Oct 11Oct 13Oct 15Oct 17Oct 19Oct 21
The left and right arrow keys step from day to day; Home and End go to the first and the last
Stars, forks, merged pull requests and Trendshift Trending rank, by day
Day
Stars gained
Forks gained
Merged PRs
Wed, Oct 7, 2026
+0
+0
0
Thu, Oct 8, 2026
+13
+1
0
Fri, Oct 9, 2026
+17
+0
0
Sat, Oct 10, 2026
+14
+0
0
Sun, Oct 11, 2026
+8
+0
0
Mon, Oct 12, 2026
+20
+1
0
Tue, Oct 13, 2026
+6
+0
0
Wed, Oct 14, 2026
+5
+1
0
Thu, Oct 15, 2026
+6
+0
0
Fri, Oct 16, 2026
+12
+1
0
Sat, Oct 17, 2026
+0
+0
0
Sun, Oct 18, 2026
+5
+0
0
Mon, Oct 19, 2026
+3
+0
0
Tue, Oct 20, 2026
+4
+0
0
Wed, Oct 21, 2026
+4
+0
0
Thu, Oct 22, 2026
+0
+0
0
Total
+117
+4
0
1#1 on the list
7Rank that day
Not trending
Social mentions
Recent discussions about this repository across the web
2 posts
LESS PLUMBING, MORE EXPERIMENTS That’s what caught my eye about RSIGym. Research agents work in lightweight CPU-only containers, calling services for training, inference, rollouts and evaluation. The…
Claude Opus 5 nearly tripled a Qwen model's SWE-bench Verified score while working as an automated AI researcher. @Evolvent_AI 's newly released open-source RSIGym made that measurement possible by…
🐕 Beagle is designed to be the unified platform for the broader Recursive Self-Improvement (RSI) ecosystem. Think of it as Hugging Face Trainer for agent evolution. Its efficient rollout engine enables evaluation and evolution at scale across different agents, datasets, benchmarks, and evolution methods.
A research framework for principled agent self-improvement under frozen evaluators and declared mutation boundaries, recording verifiable lineage to make it reproducible and auditable.
A training-free multi-agent framework for recursive self-improvement in new environments through broad-then-deep autonomous exploration and reusable memory.
