Miles is an enterprise-facing reinforcement learning framework for LLM and VLM post-training, forked from and co-evol...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Still active enough to matter. Good candidate for a fast stack test instead of a long evaluation loop.
Copy the install, test the workflow, then decide if it earns a permanent slot.
Reasonable to try, but it will take more than a quick skim to get real signal.
GitHub health 50/100. no security policy. 954 open issues make this testable, but not something to trust blind.
AI Agent
Universal
Model
Multiple
Fastest way to find out if miles belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
git clone https://github.com/radixark/miles ~/.claude/agents/milesRun this first. You will know quickly if the workflow earns a permanent slot.
rm -rf ~/.claude/agents/milesNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ skills/ ├─ agents/ │ └─ miles/ ← installs here └─ settings.json
Miles is an enterprise-facing reinforcement learning framework for LLM and VLM post-training, forked from and co-evolving with slime.
Source: GitHub repository
Source check: September 4, 2026
Upstream commit: September 4, 2026
Repository state: Not marked archived
Honeystax upvotes are community interest signals, not star ratings. GitHub stars and repository health are source measurements; editorial risk and trial-cost notes are Honeystax analysis.