executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
rl-anything-dynamicEnable simultaneous optimization of environment difficulty, policy, and reward model. System uses reward model evaluations to guide environment adaptation, creating positive feedback loop for scalable agent improvement.
Independent GitHub snapshot · Automated classification · Original documentation governs