auto-review-loop-minimax

# Auto Review Loop (MiniMax Version): Autonomous Research Improvement Autonomously iterate: review → implement fixes → re-review, until the external reviewer gives a positive assessment or MAX_ROUNDS is reached. ## Context: $ARGUMENTS ## Constants - MAX_ROUNDS = 4 - POSITIVE_THRESHOLD: score >= 6/10, or verdict contains "accept", "sufficient", "ready for submission" - REVIEW_DOC: `AUTO_REVIEW.md` in project root (cumulative log) - REVIEWER_MODEL = `MiniMax-M2.7` — Model used via MiniMax API ## API Configuration This skill uses MiniMax API for external review. Two methods are supported: ### Method 1: MCP Tool (Primary) If `mcp__minimax-chat__minimax_chat` is available, use it: ``` mcp__minimax-chat__minimax_chat: message: | [Review prompt content] model: "MiniMax-M2.7" system: "You are a senior machine learning researcher..." ``` ### Method 2: curl (Fallback) If MCP is not available, use curl directly: ```bash curl -s "https://api.minimax.io/v1/chat/completions" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer $MINIMAX_API_KEY" \ -d '{ "model": "MiniMax-M2.7", "messages": [ {"role": "system", "content": "You are a senior ML researcher..."}, {"role": "user", "content": "[Review prompt]"} ], "max_tokens": 4096 }' ``` **API Key**: Read from `~/.codex/settings.json` under `env.MINIMAX_API_KEY`, or from environment variable. **Why MiniMax instead of a secondary Codex agent?** Codex CLI uses OpenAI's Respon...