academic-research-skills

This Skill suite addresses efficiency bottlenecks across the entire academic research workflow, from literature review and data validation to paper writing and journal submission. In practice, researchers often need to repeatedly verify references, format citations, and check logical consistency. While AI-assisted tools typically handle only isolated tasks, this suite connects eight key stages into a complete research pipeline.

Usage is straightforward: simply run the installation command in Claude Code, then invoke the corresponding skill using natural language instructions. For example, entering /ars-plan initiates a Socratic dialogue to progressively outline your paper's structure; /ars-style-calibrate learns your writing style from past papers; /ars-quality-check detects AI-generated artifacts and optimizes writing quality. Each skill supports a human-AI collaborative loop, with integrity checkpoints at critical stages.

It is ideal for researchers, graduate students, and university faculty who conduct systematic academic work—particularly those already using Claude Code but seeking to upgrade AI from a "Q&A tool" to a "research collaborator," as well as academic teams handling tedious tasks like managing extensive citations, formatting standards, and data verification.

We recommend adopting this suite at the start of a new paper or project to embed AI collaboration from the planning phase. Note that it does not write the paper for you—it focuses on handling the "grunt work" like reference processing, format validation, and logical consistency checks, while leaving core tasks like problem definition, methodology selection, and results interpretation to you. It requires Claude Code v3.7.0+ and an internet connection for installation and updates.