scholaraio

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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.

<div align="center"> <img src="docs/assets/scholaraio.gif" width="900" alt="ScholarAIO natural-language research workflow"> </div>

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.

<div align="center"> <img src="docs/assets/scholaraio-architecture-v1.3.0.png" width="900" alt="ScholarAIO architecture: human, agent, scientific context, tool layer, and compute/outputs"> </div>

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

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
• •nature-workflow: bridge to the upstream nature-skills bundle for Nature/high-impact figures, polishing, writing, reviewer critique, citation, Data Availability, paper reading, reviewer response, paper-to-PPT, and academic search; direct upstream skills are preferred when available
• •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.

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.

For reuse from another project, run scholaraio setup agent to preview shell, skill-discovery, and project-wrapper changes; add --apply to perform the automatic steps.

Wrappers created with --target-project include local machine paths; review the managed block before committing those files to a shared repository.

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.
• •scholaraio setup agent configures cross-project agent discovery and CLI runtime wiring.
• •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