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Found 11 Skills
Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
Autonomous multi-round research review loop. Repeatedly reviews via Codex MCP, implements fixes, and re-reviews until positive assessment or max rounds reached. Use when user says "auto review loop", "review until it passes", or wants autonomous iterative improvement.
Autonomous multi-round research review loop using MiniMax API. Use when you want to use MiniMax instead of Codex MCP for external review. Trigger with "auto review loop minimax" or "minimax review".
Self-improving review loop for Ralph Wiggum skills. Reviews skills against best practices, implements improvements, and continues until two consecutive clean reviews. Use when validating or improving the ralph-prompt-* skill suite.
Use when iterative review-fix cycles are needed on a plan or implementation — bounded loop with severity gating, automatic fixes, and finding disposition.
Iterative worker-reviewer cycle that spawns a critic subagent to score work 1-10 and provide actionable feedback, then revises until a quality gate is met. Use when implementing features, writing specs, reviewing existing code, or completing any task where quality matters more than speed. Trigger phrases: "use review-loop", "polish this", "iterate on this", "/review-loop", "review with feedback loop".
Use when addressing open PR review comments from any reviewer (human or bot) within the current agent session. For a fresh-context-per-comment approach, use ralph-wiggum-loop instead.
Use when one agent is implementing code and another agent must review the resulting changes, compare the summary against the actual files, decide whether to fix now or move on, and write the next tightly scoped prompt with context handoff guidance.
Use when another skill or agent needs a review panel assembled, retained, or converged — invoked by /review-loop, /plan-review, and code-reviewer, not directly by users.
Full research pipeline: Workflow 1 (idea discovery) → implementation → Workflow 2 (auto review loop). Goes from a broad research direction all the way to a submission-ready paper. Use when user says "全流程", "full pipeline", "从找idea到投稿", "end-to-end research", or wants the complete autonomous research lifecycle.
Use when automating an iterative GitHub Copilot review loop on a PR — triggers Copilot review, addresses its feedback one comment at a time, and re-triggers up to 2 cycles until all critical issues are resolved.