{"slug":"superpowers-optimized","title":"superpowers-optimized","description":"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.\n\nCross-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.\n\nFive 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), *verify your own reasoning* (multi-path self-consistency catches confident-but-wrong failures before they become expensive), and *accountability drives accuracy* (agents that know their output has real downstream consequences perform better).","developer":null,"category":null,"reported_installs":null,"active":true,"first_seen_at":"2026-10-03T22:13:33.942Z","last_seen_at":"2026-10-14T00:00:01.915Z","last_changed_at":"2026-10-03T22:13:33.942Z","platform":"claude","sources":["Community"],"works_with":["Claude Code"],"marketplace_url":null,"repository_url":"https://github.com/REPOZY/superpowers-optimized.git","web_data":{},"github_data":{},"catalog_sources":{"community":[{"name":"superpowers-optimized","source":{"sha":"ae16bf3728512c110513092c01d56069694efda3","url":"https://github.com/REPOZY/superpowers-optimized.git","source":"url"},"homepage":"https://github.com/REPOZY/superpowers-optimized","description":"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.\n\nCross-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.\n\nFive 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), *verify your own reasoning* (multi-path self-consistency catches confident-but-wrong failures before they become expensive), and *accountability drives accuracy* (agents that know their output has real downstream consequences perform better)."}]}}