Self-evolving runtime infrastructure for Physical AI and embodied agents. Ground AI agents into robot bodies with e-U...
Copy the install, test the workflow, then decide if it earns a permanent slot.
Fresh repo activity plus visible builder pull. This is the kind of tool people test before it turns obvious.
Copy the install, test the workflow, then decide if it earns a permanent slot.
Not hard to test, not trivial to unwind. Worth trying if it closes a sharp gap.
GitHub health 62/100. no security policy. Fresh enough repo health and manageable issue load keep the risk controlled.
AI Agent
OpenClaw
Model
Multiple
Fastest way to find out if rosclaw belongs in your setup.
Copy the install command, run a real test, and back it out cleanly if it slows you down.
# Visit: https://github.com/ros-claw/rosclawRun this first. You will know quickly if the workflow earns a permanent slot.
# No automated removal — visit https://github.com/ros-claw/rosclawNo messy cleanup loop. If it misses, remove it and keep moving.
Install Location
~/ └─ .claude/ ├─ commands/ ├─ agents/ │ └─ rosclaw/ ← installs here └─ settings.json
Self-evolving runtime infrastructure for Physical AI and embodied agents. Ground AI agents into robot bodies with e-URDF, sandbox safety, capability routing, praxis capture, physical memory, runtime intervention, and skill evolution.
Source: GitHub repository
Source check: July 18, 2026
Upstream commit: July 18, 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.