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ZimoLiao

scholaraio

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

AI EngineeringGive agent knowledgeBuild agent workflow (SDK)Python
Open on GitHub
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576
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78
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Created 2026-03-09 · Updated 2026-10-10 · #16709 today
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ZimoLiaoShlok148DevAnterCreeper

ZimoLiao/scholaraio is ranked 16,709 with 576 stars.

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Key parameters and specifications
Key parameters and specifications
ParameterValue
LanguagePython
CategoryAI Engineering
SubcategoryGive agent knowledge, Build agent workflow (SDK)
KeywordsAgent-ready APIs, Document understanding, Knowledge base, Retrieval
Stars576
Forks78
Contributors7
Created date2026-03-09
Updated date2026-10-10
Stars in 1 day0
Stars in 7 days-1
Rank16,709
Previous rank16,497
Rank change-212
7-day stars rank17,929
Previous 7-day stars rank15,685
7-day stars rank change-2,244
Total stars rank17,326
Previous total stars rank17,296
Total stars rank change-30
README summary

ScholarAIO adds the academic harness around it, so the same agent can carry evidence, project state, repeatable workflows, and reviewable outputs across the whole research process. Your paper library becomes a reusable knowledge base for the same agent. Skills and CLI contracts give the agent stable ways to search, read, organize, cite, write, and verify. Optional tools are integrated selectively when they strengthen that workflow and degrade cleanly when unavailable. Here, **All-in-One means one coherent academic workflow**, not

every scientific package in one distribution. The active agent supplies reasoning and orchestration; ScholarAIO supplies the durable academic context and operational contracts around it. It gives an AI coding agent a stable academic substrate for evidence, project memory, tool use, research outputs, and verification without trying to replace the agent itself. 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. 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, the repository knowledge map in , and the complete codebase context are all available directly. For Claude Code plugins, Codex/OpenClaw skill registration, and other setup paths, see . 0 is a product-boundary and compatibility release; it does not change the current data layout for 1. Upgrade the package, run , and rebuild indexes when appropriate. 3 or

earlier must still complete the explicit runtime migration. See for removed surfaces, migration guidance, and the 2. The current writing stack is organized around: : route by deliverable and writing stage : bridge to the upstream 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 : long-form review and survey writing : guided deep reading of a single paper from fuzzy search

to full-text analysis : manuscript sections and paper-focused drafting : rebuttal and response-letter workflows : gap analysis and open-question reports : technical briefings and topic reports : poster-oriented content packaging : final DOCX / PPTX packaging See 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. io standard, and and are symlinks

to so different agents can discover and reuse the same skills. Qwen-specific project context lives in . For reuse from another project, run to preview shell, skill-discovery, and project-wrapper changes; add to perform the automatic steps. Wrappers created with include local machine paths; review the managed block before committing those files to a shared repository. ** 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, can also pull DOI or landing-page PDFs into the normal ingest flow or refresh

Frequently asked questions

How many stars and forks are recorded?

ZimoLiao/scholaraio has 576 stars and 78 forks.

What is the repository rank?

ZimoLiao/scholaraio is ranked 16,709.

What language and category are recorded?

ZimoLiao/scholaraio has 576 stars, uses Python and belongs to AI Engineering.

Which repository is closest in rank?

ZimoLiao/scholaraio is compared with astrio-labs/forall-mcp, ranked 16,710 with 576 stars.

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