auto-review-loop-minimax

Automate multi-round external review by running an autonomous loop using MiniMax for iterative feedback, which initiates review rounds, parses feedback, and tracks progress via persistent state files until reaching a positive assessment or maximum rounds.

The autonomous review loop handles workflow orchestration through phase orchestration and state persistence, saving progress to REVIEW_STATE.json and AUTO_REVIEW.md files to track iterative feedback and improvement cycles consistently.

Yes, you can fetch external reviewer insights using configurable API-backed review methods, supporting both MiniMax MCP integration and a curl fallback mechanism to ensure the review loop retrieves feedback reliably.

Structure iterative feedback through a standardized scoring loop that automates multi-round external reviews, enabling a research team to receive structured critique and reach a submission-ready manuscript within a fixed number of bounded rounds.

Yes, the automated review workflow supports a bounded number of improvement cycles, executing repeatable iteration rounds that parse reviewer scoring and structured feedback until the research project achieves a positive assessment or hits the maximum rounds limit.