research-review

Review research papers and experimental results through iterative dialogue.

100|24|Updated Mar 31, 2026

Search Tags:#critical analysis #Codex MCP #research quality #research review #iterative dialogue

Ready to run

npx skills add https://github.com/GRIND-Lab-Core/night_owl_research_agent --skill research-review-grind-lab-core

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: research-review
Source: https://github.com/GRIND-Lab-Core/night_owl_research_agent/tree/main/skills/idea-review
Command: npx skills add https://github.com/GRIND-Lab-Core/night_owl_research_agent --skill research-review-grind-lab-core

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires mcp__codex__codex, mcp__codex__codex-reply, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides in-depth critical review of research ideas, papers, or experimental results, offering expert-level feedback and analysis.

Core Features & Use Cases

Critical Review: Gain comprehensive feedback from a senior ML reviewer on research projects.
Multi-Round Dialogue: Engage in iterative dialogue to address criticisms and refine the research.
Documentation: Document the entire review process and conclusions in a structured report.

Quick Start

Run the /research-review command with your research topic to get a critical review.

Frequently Asked Questions about research-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I get expert critical analysis on my research paper before submission?▼

You can obtain expert critical analysis on your research paper by engaging in multi-round iterative dialogue that simulates a senior reviewer. This process provides comprehensive critical review and addresses specific concerns to refine your research quality.

Do I need to configure the Codex MCP server for research review?▼

You must configure the Codex MCP server to perform research review. The Skill requires specific Codex MCP tools for deep reasoning to provide expert-level critical feedback and iterative dialogue on your research.

Can I use multi-round dialogue to address criticisms and refine experimental results?▼

Yes, you can use multi-round dialogue to address criticisms and refine experimental results. The iterative dialogue allows you to resolve specific concerns raised during the critical review and systematically improve your research quality.

What is the best way to document the critical review process for my research?▼

The best way to document the critical review process is to generate a structured report that captures the iterative dialogue and final conclusions. This documentation provides a comprehensive record of expert feedback and analysis applied to your research.

Does this critical review tool work for machine learning research topics specifically?▼

This critical review tool works for machine learning research topics by providing feedback from a senior ML reviewer perspective. It analyzes your research ideas, papers, or experimental results to deliver domain-specific expert-level analysis.