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Imbad0202/academic-research-skills

A comprehensive Claude Code skill suite designed to augment human researchers throughout the academic research, writing, and peer-review process, focusing on quality and integrity.

Core Features

Deep Research with Socratic guided mode and Semantic Scholar API verification

Academic Paper Writing with Style Calibration and Writing Quality Check

Multi-perspective Peer Review with quality rubrics and integrity gates

Orchestrated Academic Pipeline with adaptive checkpoints and claim verification

Data Access Level Metadata for enforced data handling

Detailed Introduction

This project provides a sophisticated set of Claude Code skills to assist academic researchers across the entire publication lifecycle, from initial research to final review. It emphasizes a "human-in-the-loop" approach, leveraging AI as a copilot to handle tedious tasks like reference hunting, citation formatting, and data verification, while ensuring academic integrity and quality. Unlike fully autonomous AI systems, it incorporates integrity gates and calibration modes to mitigate common AI failure modes, allowing researchers to focus on critical thinking and interpretation.