A Claude Code plugin suite that supports academic research work end to end—from planning and literature review to writing, review, revision, and finalization—while keeping a human researcher in control.
Imbad0202/academic-research-skills is a Python-based Claude Code skill collection for academic research and writing. The README presents it as a full pipeline for moving from research to publication, with commands such as /ars-plan for Socratic paper planning and /ars-lit-review for literature review support. It is designed for Claude Code users in the CLI, VS Code, and JetBrains workflows.
The repository addresses the repetitive, error-prone parts of academic research writing: gathering references, formatting citations, checking data consistency, reviewing logic, and revising prose. The README argues that AI should assist with these chores rather than replace the researcher, because the human still needs to define the question, choose the method, interpret results, and make the core argument.
Conceptually, the system organizes research work into stages and skills that cover the pipeline from planning through final review. The README points to architecture and setup docs for the stage-by-stage flow, quality gates, and skill dependencies, and it highlights features such as Socratic planning, style calibration from past work, writing-quality checks, citation provenance tracking, and optional claim-level audits that compare claims against cited sources. The overall model is human-in-the-loop: AI handles support tasks, while blocking checks and review steps are meant to prevent unsupported claims, citation problems, and other integrity issues.
It is gaining attention because it sits at the intersection of AI-assisted writing, academic workflows, and Claude Code's plugin ecosystem, and the README presents it as easy to install with a short command sequence. The project also aligns with current concerns about citation integrity and AI-generated research quality, which the README explicitly connects to recent literature on hallucinated citations and autonomous research failures. Its rapid star growth suggests strong interest from users looking for practical, research-specific Claude Code tooling.
The README itself points to a few adjacent approaches rather than direct competitors: a fully autonomous research system such as The AI Scientist, the PaperOrchestra-style verification and anti-leakage ideas, and a Codex-native sibling distribution for users of Codex CLI. More broadly, the closest alternative is the manual academic workflow without these skills, or other general-purpose AI writing assistants that do not focus specifically on research-stage checks, citation provenance, and human-in-the-loop academic review.
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