11 boosters for "academic" — open source, verified from GitHub, ready to install
Provides the Hugging Face Hub CLI (`hf`) tool for downloading, uploading, and managing models, datasets, and Spaces directly from Claude Code. Essential for developers integrating Hugging Face resources into AI workflows.
检测和改写中文 AI 生成文本的完整工具链。可独立运行（统一 CLI 或独立脚本），也可作为 LLM prompt 指南使用。 所有脚本在 目录下，纯 Python，无依赖。 v3.0 所有阈值都基于 HC3-Chinese 300+300 人类/AI 样本的 Cohen's d 校准：
arXiv、Semantic Scholar、PubMed、Papers with Code 等 API 平台无需 Chrome 远程调试即可使用。 学术搜索不同于通用网页浏览——目标是获取准确、结构化的论文元数据，而不是浏览网页内容。 所有结果输出为统一 schema（见 ），不要输出原始 HTML 或非结构化文本。多平台结果用 DOI/arXiv ID 去重合并。
Extracts structured datasets from academic papers by leveraging OpenAlex search and citation graph traversal. Researchers and AI scientists benefit from automating literature review and dataset creation workflows.
Search academic papers via the Semantic Scholar API using a structured 4-phase workflow. Parse the user's intent and choose a search strategy: Write ONE Python script. Example:
当用户对已有导师 Skill 说以下内容时，进入进化模式： 本 Skill 运行在 Claude Code 环境，使用以下工具： 1. 不主动给出学术不端建议：不伪造数据、不抄袭、不代写造假
ADHARA is an LLM system prompt that enables early detection of learning friction by analyzing behavioral metrics like mouse hesitation, attention, and task performance against age-appropriate baselines. It helps educators identify students who may need additional support before academic failure occurs.
An MCP server that enables searching and downloading academic papers from multiple sources including arXiv, PubMed, bioRxiv, medRxiv, and Google Scholar. Ideal for researchers, students, and developers who need programmatic access to academic literature.
"description": "End-to-end skills for academic writing, data analysis, teaching, and research communication", "name": "academic-skills", "description": "Academic manuscript writing suite, topic modeling consolidation, exploratory analysis, and course content development",
"name": "open-academic-paper-machine", "description": "Open Academic Paper Machine — Autonomous academic paper production system with idea evaluation gate and paper-vs-code audit. NEW in v6.4: /audit-paper command and audit-engine skill — static audit of a paper's empirical claims (datasets, models,
Enables researchers and academics to systematically search arXiv papers, analyze research content, build literature reviews, and generate citations through a skill designed for Claude Code integration. Useful for students, researchers, and anyone conducting academic research who need structured access to arXiv resources.
