Automate ML research loops with ARIS skills git:20260710.2925510B

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---
title: "Automate ML research loops with ARIS skills"
description: "Use ARIS to run Markdown-based agent skills for literature review, idea discovery, cross-model critique, experiment planning, and paper-writing support."
verification: "security_reviewed"
source: "https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep"
author: "wanshuiyin"
publisher_type: "individual"
category:
  - "Templates & Workflows"
framework:
  - "Multi-Framework"
tool_ecosystem:
  github_repo: "wanshuiyin/Auto-claude-code-research-in-sleep"
  github_stars: 9609
---

# Automate ML research loops with ARIS skills

Use ARIS to run Markdown-based agent skills for literature review, idea discovery, cross-model critique, experiment planning, and paper-writing support.

## Prerequisites

ARIS skills or ARIS-Code CLI, Claude Code/Codex/OpenClaw-compatible agent, configured model providers

## Installation

Choose whichever fits your setup:

1. Copy this skill folder into your local skills directory.
2. Clone the repo and symlink or copy the skill into your agent workspace.
3. Add the repo as a git submodule if you manage shared skills centrally.
4. Install it through your internal provisioning or packaging workflow.
5. Download the folder directly from GitHub and place it in your skills collection.

Install command or upstream instructions:

```
Install the ARIS skill pack or download the latest ARIS-Code release, configure model providers, then invoke the relevant research skill from the supported agent runtime or CLI.
```

## Documentation

- https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep

## Source

- [Agent Skill Exchange](https://agentskillexchange.com/skills/automate-ml-research-loops-with-aris-skills/)