Research plugin for thesis work on cortical columns and algorithmic representations. Discovers, analyzes, and organizes academic papers from arXiv and Semantic Scholar into an Obsidian vault.
Perform deep methodology analysis of a specific paper with thesis connections, creating a detailed Obsidian note
Search arXiv for papers relevant to cortical column research, quick-scan for relevance, and push findings to Obsidian vault
Analyze existing Obsidian research vault, identify gaps in cortical column literature, and suggest papers to fill them
Scan for new papers in relevant arXiv categories since last check, quick-scan for relevance, and push findings to Obsidian
This folder is a research workspace for theoretical AI.
It is where we keep notes, experiments, plugin prototypes, and supporting material related to formal reasoning, algorithmic structure, mathematical analysis, and other theory-focused AI work.
plugins/algo-math-structurer: a Claude Cowork plugin for turning Python algorithms into formal mathematical documents with proofs and LaTeX outputplugins/cortical-columns: a Claude Cowork plugin for thesis research on cortical columns and algorithmic representationsplugins/algo-math-structurer/ for the algorithm formalization pluginplugins/cortical-columns/ for cortical columns research.sisyphus/ for planning, evidence, and internal notes.claude-plugin/ for marketplace configurationOwn this plugin?
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npx claudepluginhub baptistecaille/research-plugin --plugin cortical-columnsTransform Python algorithm code into formal mathematical documents with proofs, exported as compilable LaTeX and compiled to PDF.
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.
11 research-hub skills: literature triage matrix, context compression, project orientation, design dialog, multi-AI routing, NotebookLM brief verification, paper-memory builder, paper summarizer, Zotero curator, the gap-to-topic decision dossier, and the research-hub orchestrator. Auto-discovered from skills/<name>/SKILL.md.
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.
Semi-automated research assistant for academic research and software development, with skills for literature review, experiments, analysis, writing, and project knowledge management
Academic research agents — hypothesis generation, experiment design, paper drafting, peer review simulation, and more.
Scientific research brainstorming partner: survey the literature, find good problems, and shape concrete research ideas together