copilot-goal-skill vs. superpowers-optimized

Goal-driven task orchestration with independent verification. Interviews the user to define a clear goal, then loops between a Builder subagent (does the work) and an Inspector subagent (judges the result with fresh context). The Inspector never trusts the Builder. Output is auditable in git commits from each subagent actions. Use when the user says "achieve this goal", "make this work", "implement until done", or wants verified autonomous task completion with independent quality review.

Built on the trusted obra/superpowers workflow and refined through research into LLM agent behavior, it adds automatic 3-tier workflow routing, proactive safety hooks, self-consistency verification at critical decision points, cross-session memory, and adversarial red-teaming — everything the original does, plus the discipline layer it was missing. Cross-session memory changes the experience fundamentally. Without it, every session starts blind: the AI re-explores structure it already mapped, re-proposes approaches that were already rejected, re-debugs errors that were already solved. With the four-file memory stack, it arrives knowing what was tried, what was decided, and why — and builds forward instead of sideways. Five research-backed principles run throughout: *less is more* (minimal always-on instructions), *fresh context beats accumulated context* (subagents get clean scoped prompts, not polluted history), *compliance ≠ competence* (instructions must be carefully engineered, not just comprehensive), *v