by ZimoLiao
Scholar All-In-One: A research infrastructure for AI agents
# Add to your Claude Code skills
git clone https://github.com/ZimoLiao/scholaraioScholar All-In-One — A research infrastructure for AI agents.
Your coding agent already reads code, writes code, and runs experiments. ScholarAIO adds a structured research workspace on top, so the same agent can search literature, cross-check results against papers, use scientific software more accurately, and carry the whole research workflow from one terminal.
ScholarAIO offers more than search. It gives an AI coding agent a research workspace that supports natural-language interaction, papers and notes, more reliable use of scientific software, writing and running code, checking results against the literature, and structured academic writing.
The default and recommended way to use ScholarAIO is simple: install it, configure it once, and open this repository directly with your coding agent.
git clone https://github.com/ZimoLiao/scholaraio.git
cd scholaraio
pip install -e ".[full]"
scholaraio setup
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Then open the repository in Codex, Claude Code, or another supported agent. In this setup, the agent gets the fullest experience: bundled instructions, local skills, the CLI, and the complete codebase context are all available directly. For Claude Code plugins, Codex/OpenClaw skill registration, and other setup paths, see docs/getting-started/agent-setup.md.
| | Feature | Details | |--|---------|---------| | PDF Parsing | Deep structure extraction | Convert PDFs into structured Markdown while preserving formulas, figures, and layout as much as possible | | Not Just Papers | More than papers | Journal articles, theses, patents, technical reports, standards, and lecture notes — four inbox categories with tailored metadata handling | | Hybrid Search | Keyword + semantic fusion | Combine full-text and vector retrieval for stronger search results | | Topic Discovery | See what your library is about | Automatically group papers into research themes and use interactive views to grasp the overall structure quickly | | Literature Exploration | Multi-dimensional discovery | Explore a research direction through journal, topic, author, institution, keyword, year, citation impact, and more | | Citation Graph | References & impact | Forward citations, backward citations, and shared-reference analysis | | Layered Reading | Read on demand | Start with metadata or the abstract, then move into conclusions or full text only when you need to | | Multi-Source Import | Connect your existing library | Import directly from reference managers, PDFs, and Markdown without rebuilding your library from scratch | | Workspaces | Organize by project | Manage paper subsets with scoped search and BibTeX export | | Multi-Format Export | BibTeX, RIS, Markdown, DOCX | Export your full library or a workspace for Zotero, Endnote, submission, or sharing | | Persistent Notes | Cross-session memory | Keep analysis notes for each paper so future sessions can reuse them instead of starting over | | Research Insights | Reading behavior analytics | Search hot keywords, most-read papers, reading trends, and semantic neighbor recommendations for papers you haven't read yet | | Federated Discovery | Cross-library search | Search your main library, exploration libraries, and arXiv from one entry point instead of hopping across tools | | AI-for-Science Runtime | Use scientific software more accurately | Use scientific software against official documentation at runtime instead of guessing commands and parameters | | Extensible Tool Onboarding | Keep adding the tools that matter | As new scientific tools and workflows become important, the system can keep expanding | | Academic Writing | AI-assisted writing | Literature review, paper sections, citation check, rebuttal, and gap analysis — with every citation traceable to your own library |
ScholarAIO is designed to be agent-agnostic, but different agents expose different integration paths. Some work best when you open this repository directly; others are easier to use through plugins.
| Agent / IDE | Open this repo directly | Reuse from another project |
|-------------|-------------------------|-----------------------------|
| Claude Code | CLAUDE.md + .claude/skills/ | Claude plugin marketplace |
| Codex / OpenClaw | AGENTS.md + .agents/skills/ | Symlink skills into ~/.agents/skills/ |
| Cline | .clinerules + .claude/skills/ | CLI + skills |
| Cursor | .cursorrules | CLI + skills |
| Windsurf | .windsurfrules | CLI + skills |
| GitHub Copilot | .github/copilot-instructions.md | CLI + skills |
Skills follow the open AgentSkills.io standard, and .agents/skills/ is a symlink to .claude/skills/ so different agents can discover and reuse the same skills.
Migrating from existing tools? Import directly from Endnote (XML/RIS) and Zotero (Web API or local SQLite), with PDFs, metadata, and references brought over together. More import sources are on the roadmap.
Start by opening
scholaraiowith your agent and let it walk you through the setup. The notes below are only a basic overview.
ScholarAIO works with a minimal setup and can be expanded as needed.
scholaraio setup walks you through the basics.scholaraio setup check shows what is installed, what is optional, and what is missing.Full setup and configuration details → docs/getting-started/agent-setup.md, config.yaml
ScholarAIO works best through an AI coding agent, but it also provides a CLI for scripting, debugging, and quick queries. For a current command reference aligned with the code, see docs/guide/cli-reference.md.
scholaraio/ # Python package — CLI and all core modules
ingest/ # PDF parsing + metadata extraction pipeline
sources/ # External source adapters (arXiv / Endnote / Zotero)
.claude/skills/ # Agent skills (AgentSkills.io format)
.agents/skills/ # ↑ symlink for cross-agent discovery
data/papers/ # Your paper library (gitignored)
data/proceedings/ # Proceedings library (gitignored)
data/inbox/ # Drop PDFs here for ingestion
data/inbox-proceedings/ # Drop proceedings volumes here for dedicated ingest
If you use ScholarAIO in your research, please cite:
@software{scholaraio,
author = {Liao, Zi-Mo},
title = {ScholarAIO: AI-Native Research Terminal},
year = {2026},
url = {https://github.com/ZimoLiao/scholaraio},
license = {MIT}
}
MIT © 2026 Zi-Mo Liao