
An autonomous LLM research agent that executes the full academic paper pipeline — from literature search to compiled PDF
概览
A Claude Code plugin that autonomously writes academic papers — from literature search to production-ready LaTeX/PDF. New /audit-paper command and audit-engine skill: static audit of a paper's empirical claims (datasets, models, hyperparameters, metrics) against the linked code repository. Classifies each claim as CONFIRMED / PARTIAL / MISSING / MISMATCH / NOT_AUDITABLE with file:line evidence. Complements /verify-citations (external sources) by checking own-work claims against own code. Inspired by Feynman's /audit. This project is a technical contribution: it explores what is possible with current LLM technology for academic paper production, not what is desirable or ethically permissible. The ethical, epistemological, and policy questions raised by AI-generated academic writing — authorship attribution, academic integrity, epistemic status, potential misuse — are important but outside the scope of this tool. They are addressed in the companion position paper (Blask & Funk, 2026).
README
以下为原文 README 节选,完整内容请查看原文。
Open Academic Paper Machine
A Claude Code plugin that autonomously writes academic papers — from literature search to production-ready LaTeX/PDF.
v6.4.0 — Paper-vs-Code Audit. New
/audit-papercommand andaudit-engineskill: static audit of a paper’s empirical claims (datasets, models, hyperparameters, metrics) against the linked code repository. Classifies each claim as CONFIRMED / PARTIAL / MISSING / MISMATCH / NOT_AUDITABLE with file:line evidence. Complements/verify-citations(external sources) by checking own-work claims against own code. Inspired by Feynman’s/audit.
Scope note. This project is a technical contribution: it explores what is possible with current LLM technology for academic paper production, not what is desirable or ethically permissible. The ethical, epistemological, and policy questions raised by AI-generated academic writing — authorship attribution, academic integrity, epistemic status, potential misuse — are important but outside the scope of this tool. They are addressed in the companion position paper (Blask & Funk, 2026).
Quick Start
# 1. Install the plugin
/plugin marketplace add TobiasBlask/open-paper-machine
/plugin install open-academic-paper-machine@open-paper-machine
# 2. Install dependencies
pip install paperbanana[google] academic-search-mcp
# 3. Set up your API key (free — https://aistudio.google.com/apikey)
echo 'GOOGLE_API_KEY="your-key"' > ~/.paperbanana.env
# Or per-project: echo 'GOOGLE_API_KEY="your-key"' > .env
# 4. Go
/write-paper The impact of generative AI on organizational decision-making
That’s it. The plugin ships the academic-search MCP server, the PaperBanana direct Python API for figure generation, all 16 skill engines, 4 agents, 24 curated scientific skills, 20 slash commands, and the autonomous pipeline agent. Everything starts automatically.
Technical paper: The Open Academic Paper Machine: An Autonomous LLM Plugin for End-to-End Academic Paper Production (Blask, 2026) — describes the system architecture, design principles, and evaluation. LaTeX source in paper/.
Position paper: From Creator to Orchestrator? How an LLM Agent Wrote This Paper and What That Means for Science (Blask & Funk, 2026) — a position paper on AI-augmented knowledge production, orchestrated through human-AI interaction using this system. GitHub repo.
How It Works
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安装
npx skillfish add tobiasblask/open-paper-machine