PaperOrchestra

# PaperOrchestra

A pluggable skill pack that lets **any coding agent** in Claude Code, Cursor,
Antigravity, Cline, Aider, OpenCode, etc. which can run the
[**PaperOrchestra**](https://arxiv.org/pdf/2604.05018) multi-agent pipeline for
turning unstructured research materials into a submission-ready LaTeX paper.

> Song, Y., Song, Y., Pfister, T., Yoon, J.
> *PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing.*
> arXiv:2604.05018, 2026. <https://arxiv.org/pdf/2604.05018>

<p align="center">
  <a href="https://arxiv.org/pdf/2604.05018">
    <img src="docs/assets/paper-preview.png" alt="PaperOrchestra paper — first page preview" width="420"/>
  </a>
  <br/>
  <em>Click to read the paper on arXiv</em>
</p>

## Why this exists

The paper defines a five-agent pipeline 
- Outline
- Plotting
- Literature Review
- Section Writing
- Content Refinement
  
that substantially outperforms single-agent and tree-search baselines on the `PaperWritingBench` benchmark (50–68% absolute win margin on literature review quality; 14–38% on overall quality). The paper ships the exact prompts for every agent in Appendix F.

This repo turns those prompts, schemas, halt rules, and verification pipelines into a set of **host-agent-executable skills**. There are **no API keys**, no SDK dependencies, no embedded LLM calls. The skills are instruction documents plus deterministic helpers; your coding agent does all LLM reasoning and web search using its own tools.

<img width="640" height="413" alt="image" src="https://github.com/user-attachments/assets/073630c8-9790-4b38-b8c4-184cec6eee06" />

## How skills work here

Each skill is:

- `SKILL.md` — a dense instruction document the host agent reads and follows.
- `references/` — reference material: verbatim paper prompts (Appendix F), JSON
  schemas, rubrics, halt rules, example outputs.
- `scripts/` — **purely deterministic** local helpers: JSON schema validation,
  Levenshtein fuzzy matching, BibTeX formatting, dedup,