AI Research Writing Skill provides a comprehensive suite of over 30 AI prompt templates designed to assist researchers throughout the entire academic writing process. Targeting graduate students, educators, and researchers, this tool aims to significantly enhance writing efficiency and output quality by leveraging large language models for tasks ranging from literature review to grant applications.

How It Works

This project offers a collection of meticulously crafted prompts that guide AI models (such as ChatGPT, Claude, or GPT-4) through various stages of research writing. The core approach involves providing users with pre-defined templates for specific tasks, including literature summarization, outline generation, chapter expansion, translation, polishing, figure/table descriptions, reviewer simulation, and rebuttal drafting. This structured prompting methodology aims to elicit more accurate, relevant, and high-quality outputs from AI assistants compared to generic queries.

Quick Start & Requirements

Users can integrate these prompts via three methods:

1. OpenClaw: Clone the repository, copy the research-writing skill folder into the OpenClaw workspace (~/.openclaw/workspace/skills/), and restart OpenClaw.
2. Manual Prompting: Browse the SKILL.md file in the repository, copy desired prompt templates, and paste them into any AI tool that supports Markdown (e.g., Claude, ChatGPT, Cursor, Cherry Studio), replacing placeholder variables.
3. Direct AI Tool Integration: The prompts are designed for compatibility with major AI platforms like Claude, ChatGPT, and Cursor.

No specific hardware, software, or dataset prerequisites are mentioned beyond the need for an external AI model service.

Highlighted Details

• Comprehensive Workflow Coverage: 30+ templates span literature research, drafting, revision, figure/table creation, submission replies, and grant applications.
• Versatile Prompting: Includes prompts for translation (Chinese-English), academic polishing to top-tier journal standards, AI-generated text removal, logic checking, and simulating reviewer feedback.
• Cross-Platform Compatibility: Works with popular AI tools including Claude, ChatGPT, and Cursor.
• Structured Output Examples: Demonstrates how prompts can generate structured summaries, translations, and reviewer critiques.

Maintenance & Community

The project is inspired by awesome-ai-research-writing and welcomes contributions via GitHub Issues and Pull Requests for prompt improvements, new templates, or case studies. Specific community channels (like Discord/Slack) or a public roadmap are not detailed in the README.

Licensing & Compatibility

The project is released under the MIT License, permitting free use, modification, distribution, and commercial application, provided original attribution and license notices are retained.

Limitations & Caveats

This tool functions as a set of templates and relies entirely on the capabilities of external AI models. The quality of the output is dependent on the chosen AI service and the user's input. Users are cautioned that all experimental data must be based on real research, as the AI is intended only to assist with expression, not data generation.