auto-review-loop-minimax

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".

by wanshuiyin 15k GitHub stars MIT Updated Aug 18, 2026
auto-review-loop-minimax skill by wanshuiyin
auto-review-loop-minimax — Data skill by wanshuiyin

Overview

auto-review-loop-minimax is an open-source data skill for Codex, published by wanshuiyin. Its author describes it as: “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".”. The project has 15k stars on GitHub and is available under the MIT license. Add it to your setup with `git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep ~/.claude/skills/auto-review-loop-minimax`.

What auto-review-loop-minimax does

> 🔒 **Do not wrap this skill in `/loop`, `/schedule`, or `CronCreate`.** Like > `/auto-review-loop`, it already loops internally (review → fix → re-review), > feeding each round's prior-round summary into the next review prompt (the > backend is a stateless per-round API call, not a shared thread). An external > timer re-enters from the top each tick, dropping that accumulated context and > firing the verdict on wall-clock time instead of on artifact change — zero > new signal, full token cost. Schedule the *external wait that precedes it*, > not the verdict. See > `shared-references/external…

What’s inside

The SKILL.md for auto-review-loop-minimax is organised into these sections:

  • Context: $ARGUMENTS
  • Constants
  • API Configuration
  • Method 1: MCP Tool (Primary)
  • Method 2: curl (Fallback)
  • State Persistence (Compact Recovery)
  • Workflow
  • Initialization
  • Loop (repeat up to MAXROUNDS)
  • Termination
  • Key Rules
  • Prompt Template for Round 2+

Installation

Add auto-review-loop-minimax to your agent with:

git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep ~/.claude/skills/auto-review-loop-minimax

Review a skill’s source before installing it — skills can instruct your agent to run commands. This command comes from the skill’s public repository, which is the source of truth for setup steps. New to skills? Read how to install Claude Code skills.

Supported agents

  • Claude Code — declared in the repository topics
  • Codex — named in the skill.md

License

auto-review-loop-minimax is published under the MIT license.

Strengths

  • Clear MIT license — safe to read and adapt within its terms
  • Ships in wanshuiyin/Auto-claude-code-research-in-sleep, an established project with 14,858 GitHub stars
  • Works with Claude Code, Codex
  • Actively maintained — repository updated in the last 90 days

Author

wanshuiyin 41 skills in the catalog · GitHub profile ↗
View skills

Topics

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Frequently asked questions

What does auto-review-loop-minimax do?
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".
How do I install auto-review-loop-minimax?
Run git clone https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep ~/.claude/skills/auto-review-loop-minimax in your agent, then reload your skills. Review the source at https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep before installing.
Is auto-review-loop-minimax free to use?
Yes. auto-review-loop-minimax is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
Which agents does auto-review-loop-minimax work with?
auto-review-loop-minimax lists Claude Code and Codex — named in its SKILL.md, its plugin marketplace or its repository topics. Skills use the portable SKILL.md format, so other agents that read that format may load it too.
Where does auto-review-loop-minimax come from?
auto-review-loop-minimax ships inside wanshuiyin/Auto-claude-code-research-in-sleep, a repository that contains 41 catalogued skills in total. The repository's 14,858 GitHub stars apply to that whole collection, not to this skill on its own.

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