scholaraio 1.5.0

Scholar All-In-One — A research infrastructure for AI agents

ScholarAIO

Scholar All-In-One — A research infrastructure for AI agents.

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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.

• Your paper library becomes a reusable knowledge base for the same agent.
• When scientific software questions come up, the agent can consult official documentation at runtime instead of guessing from prompts.
• The system is built to keep expanding as new tools and workflows become worth supporting.

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.

Quick Start

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

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.

Upgrading To 1.4

ScholarAIO 1.4 is a runtime-layout upgrade. It does not migrate user data automatically during git pull, pip install -U, or normal CLI startup. That is intentional: data movement is an explicit offline operation with a migration journal and verification.

Recommended path:

# 1. Update the code/package
git pull
pip install -e ".[full]"

# 2. From the ScholarAIO runtime root, inspect and migrate explicitly
scholaraio migrate status
scholaraio migrate upgrade --migration-id upgrade-1.4.0 --confirm
scholaraio migrate verify --migration-id upgrade-1.4.0

# 3. Rebuild indexes after migrated data lands in the fresh layout
scholaraio index --rebuild

For the lowest-risk upgrade, keep or copy your old ScholarAIO folder first, then run the migration in the upgraded checkout that contains your data/, workspace/, and config*.yaml. See docs/getting-started/upgrading-to-1.4.md.

What It Does

	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, with optional line-addressable evidence chunk search for precise source snippets
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
Local Library WebUI	Browse and inspect	Open a read-only local UI for records, audit status, Markdown abstracts/conclusions, proceedings children, and PDFs without exposing library data to remote scripts
Publisher PDF Fetch	Use your current access	Fetch DOI or publisher-page PDFs through the user's legal network context, with direct campus-network mode and selected/all-library PDF refetch
Multi-Source Import	Connect your existing library	Import directly from reference managers, fetched PDFs, local 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
Metadata Scrub	Incremental cleanup after enrich	Review and repair low-quality titles, authors, and years for non-standard documents, then mark reviewed records to skip future passes
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
Remote Backup	Rsync-based sync	Back up the ScholarAIO data/ workspace to configured remote targets through named rsync plans
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	Router-first workflows for literature review, guided single-paper reading, paper sections, citation check, rebuttal, gap analysis, poster packages, and technical reports — with every citation traceable to your own library

For writing tasks, start with the router-style writing entry when the deliverable is clear but the workflow is not. The current writing stack is organized around:

• academic-writing: route by deliverable and writing stage
• literature-review: long-form review and survey writing
• paper-guided-reading: guided deep reading of a single paper from fuzzy search to full-text analysis
• paper-writing: manuscript sections and paper-focused drafting
• review-response: rebuttal and response-letter workflows
• research-gap: gap analysis and open-question reports
• technical-report: technical briefings and topic reports
• poster: poster-oriented content packaging
• document: final DOCX / PPTX packaging

See docs/guide/writing.md for the full writing map.

Works With Your Agent

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
Qwen	.qwen/QWEN.md + .qwen/skills/	CLI + skills
Cursor	.cursor/rules/scholaraio.mdc + AGENTS.md (.cursorrules legacy fallback)	CLI + skills
Windsurf	.windsurfrules	CLI + skills
GitHub Copilot	.github/copilot-instructions.md	CLI + skills

Skills follow the open AgentSkills.io standard, and .agents/skills/ and .qwen/skills/ are symlinks to .claude/skills/ so different agents can discover and reuse the same skills. Qwen-specific project context lives in .qwen/QWEN.md.

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. If your current network has publisher access, scholaraio fetch-pdf can also pull DOI or landing-page PDFs into the normal ingest flow or refresh canonical PDFs for existing library records.

Configuration

Start by opening scholaraio with 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.
• An LLM API key is optional but recommended for more robust metadata extraction and content completion.
• A MinerU token is optional but recommended, and free. You can also deploy MinerU or Docling locally for PDF parsing.
• 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

Agent First, CLI Available

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.

Project Structure

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 (canonical source)
.agents/skills/         # ↑ symlink for cross-agent discovery
.qwen/QWEN.md           # ↑ project context for Qwen Code
.qwen/skills/           # ↑ symlink for Qwen agent skill discovery
data/libraries/papers/  # Paper library (fresh default)
data/libraries/proceedings/ # Proceedings library (fresh default)
data/spool/inbox/       # Drop PDFs here for ingestion
data/spool/inbox-proceedings/ # Dedicated proceedings ingest inbox

Upgrading an older runtime layout? See Upgrading To 1.4.

Agent entry docs → CLAUDE.md or AGENTS.md Deep agent reference → docs/guide/agent-reference.md

Citation

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}
}

License

MIT © 2026 Zi-Mo Liao