By WenyuChiou
Orchestrate a full academic literature review workflow: discover papers, ingest into Zotero/Obsidian/NotebookLM, compress context, verify briefs, build paper memory, and produce go/no-go decision dossiers for thesis or proposal topics.
Turn a research area into a go/no-go decision dossier for ONE candidate thesis/proposal topic — a 3-gate verdict (is the gap open? is it a contribution? is it feasible?) with the evidence laid out so the researcher can verify it. Use when the user asks "is this gap worth pursuing", "help me pick a thesis topic", "is this idea already taken", "find me a defensible research gap", "vet this research idea before I commit", or "should I do this". NOT a literature review (use `literature-triage-matrix` for a comparison matrix) and NOT a study design (use `research-design-helper` once a topic is chosen). Produces a `.research/topic_dossier.md`, a `.research/topic_dossier.docx` (Word, colour-coded), a `.bib`, and a `.gaps.yml`.
Turn a list of papers (Zotero collection, Obsidian cluster, manual list) into a compact comparison matrix written to .research/literature_matrix.md, instead of generic per-paper summaries. Use when the user asks to "make a literature matrix", "compare these papers by method/data/limitations", or "decide which papers are central to my review". If the user says "extract the claims from these papers": cross-paper comparison matrix → this skill; claims from their own manuscript draft → `paper-memory-builder`; per-cited-paper Key Findings → `paper-summarize`. This skill compares a KNOWN paper set; to turn a research area into a go/no-go decision on a candidate thesis/proposal topic, use `gap-to-topic`.
Compare a downloaded NotebookLM brief against the source bundle research-hub uploaded, and report missed sources, unsupported claims, contradictions, and recommended follow-up prompts. Use when the user asks to "verify this NotebookLM brief", "check if the brief missed anything", or "compare downloaded notes to the cluster papers".
Convert a paper draft + figures + Zotero metadata into reusable .paper/claims.yml and .paper/figures.yml files so the academic-writing-skills skill can do writing, revision, and audit passes without re-reading the manuscript every time. Use when the user asks to "build paper memory", "extract claims from this manuscript", "extract claims, supporting evidence, and figure key numbers", or "prepare this paper for AI-assisted writing". NOT for summarizing cited papers in a literature cluster — that's `paper-summarize`. This skill is for the user's own manuscript draft only.
After research-hub ingests a cluster of cited papers, fill the per-paper Key Findings + Methodology + Relevance sections in BOTH Obsidian markdown and the Zotero child note. Use when the user says "fill the TODO Key Findings/Methodology blocks left by research-hub auto", "I just ran auto and don't know what these papers are about", or "summarize the papers in cluster X". Invokes a supported LLM CLI on each paper's abstract. NOT for summarizing the user's own manuscript draft — that's `paper-memory-builder`. NOT for cluster-level briefs — that's `research-hub notebooklm generate`. This skill is per-cited-paper only. If the user says "extract claims from these papers", disambiguate before acting: their own manuscript draft → `paper-memory-builder`; a cross-paper comparison matrix → `literature-triage-matrix`; per-cited-paper Key Findings → this skill.
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Turn your research stack into an AI-operable workspace. Use Zotero, Obsidian, and NotebookLM together, or start with any two. research-hub gives your AI assistant a real CLI, MCP server, REST API, and dashboard for repeatable literature workflows.

Traditional Chinese: README.zh-TW.md | Watch the full-res mp4
📚 Part of the agentic AI learning roadmap — a 7-stage curated path for building agentic AI, multilingual (zh-TW · zh-Hans · English). This workspace is referenced in §13 (research workflow skills).
🧪 Real-use signal: in daily use by 1 PhD researcher (Lehigh CEE) tracking 7+ research clusters across Zotero + Obsidian + NotebookLM. Shipping since Apr 2026, docs updated for v0.95.0.
pip install research-hub-pipeline
research-hub dashboard --sample # preview with sample data, no accounts needed
For a real research-hub vault with Zotero / Obsidian / NotebookLM integration, pick the install path matching your stack in § Start Here.
These are generated by a real research-hub vault, not mockups.
Obsidian paper note: Markdown note with title, authors, DOI, Zotero key, tags, cluster, status, and verification metadata.
Obsidian Bases dashboard: generated .base file with sortable paper
metadata and reading status.
Obsidian graph view: managed topic folders and labels can be colored with
research-hub vault graph-colors --refresh.
Generated crystals are also plain Markdown notes under
hub/<cluster>/crystals/*.md, so they can be linked, searched, and read
by MCP tools at low token cost.
research-hub does not replace Zotero, Obsidian, or NotebookLM. It connects them so an AI agent can operate the workflow.
| What you can do | Zotero alone | NotebookLM alone | Generic RAG | Obsidian-Zotero plugin | research-hub |
|---|---|---|---|---|---|
| Search arXiv + Semantic Scholar in one command | No | No | DIY | No | Yes |
| Ingest into Zotero and Obsidian and NotebookLM | No | No | DIY | Partial | Yes |
| AI brief from your collection | No | Manual | DIY | No | Yes |
| Cached canonical answers | No | No | Re-fetches | No | Yes |
| Structured memory layer | No | No | Usually chunks | No | Yes |
| Direct AI-agent control via MCP | No | No | DIY | No | Yes |
| Live dashboard with action buttons | No | No | No | No | Yes |
| Per-cluster Obsidian Bases dashboard | No | No | No | No | Yes |
| No OpenAI/Anthropic API key required | n/a | Yes | Usually no | n/a | Yes |
| Local-first vault you own | Partial | No | Depends | Yes | Yes |
The practical fit: research-hub is most useful if you already use at least two of Zotero, Obsidian, and NotebookLM and want your AI assistant to run the repetitive steps.
Hand token-heavy mechanical work (batch edits, scaffolding, refactors, test generation, plotting scripts) from Claude to Codex CLI.
Hand long-context reading, bilingual rewrites, second-opinion review, and Traditional Chinese / CJK output from Claude to Gemini CLI.
Full Zotero CRUD: search, add, update, delete items with notes, tags, collections, and PDF attachments. Dual local/Web API routing.
Manuscript revision, claim-evidence audit, banned-word / humanize pass, figure-text consistency, journal-format check, reviewer response.
6 skills for context-safe multi-agent collaboration: task-splitter, context-budget, output-reconciler, debate, shared-memory, and acceptance-gate. Composes with codex-delegate + gemini-delegate via bounded .ai task packets, .coord context policy, and result.json contracts.
npx claudepluginhub wenyuchiou/ai-research-skills --plugin research-workspaceSemi-automated research assistant for academic research and software development, with skills for literature review, experiments, analysis, writing, and project knowledge management
Karpathy-style LLM wiki for research papers. Ingest a URL / arXiv ID / DOI / PDF, write a structured summary into a local Obsidian vault, and maintain a finding-level knowledge graph via wikilinks + Dataview.
A research infrastructure for AI agents. Search, read, and analyze papers from your local knowledge base while coding. Includes arXiv discovery, layered reading, ingestion, topic modeling, citation graphs, insights analytics, Office document inspection, scientific tool docs, and academic writing workflows. Requires Python 3.10+ and pip install.
Academic research agents — hypothesis generation, experiment design, paper drafting, peer review simulation, and more.
完整学术流水线 — 从 idea 到论文的全流程编排:状态机追踪、完整性验证、claim 校验
Collection of academic skills based on effortlessacademic.com note taking ideas like atomic sentences.