auto-review-loop-minimax

The MiniMax API integration provides external reviewer feedback for your research automation loop. It acts as a senior ML reviewer, assessing your work and suggesting improvements while internal scripts automatically implement the recommended fixes within the iterative cycle.

An iterative research review loop is an automated cycle that repeatedly reviews research, implements script-based changes, and reassesses the output. It continues until a positive review is received or the maximum iteration rounds are reached.

Start the automated review loop by triggering the auto review loop minimax command. This initiates the MiniMax API assessment cycle, which coordinates external feedback with internal script execution to iteratively implement fixes and reassess your research.

Yes, the MiniMax API is required because it supplies the external reviewer feedback needed to evaluate your ML research. The automated loop depends on this API to assess work and suggest improvements before internal scripts implement the fixes.

The automated review loop stops iterating when the external MiniMax API reviewer returns a positive review or when the process reaches the maximum number of rounds. This prevents infinite cycles and ensures research quality improvements are bounded.