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
listener-rewarded-vlm-preferencesAligns reasoning traces with final decisions in preference models using an independent frozen VLM as listener. Achieves 67.4% accuracy on ImageReward by enforcing consistency between explanations and choices. Use when training reward models for image generation quality where both reasoning quality and accuracy matter.
Independent GitHub snapshot · Automated classification · Original documentation governs