paper-orchestra

A pluggable skill pack that lets any coding agent — Claude Code, Cursor,
Antigravity, Cline, Aider, OpenCode, etc. — run the
PaperOrchestra 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

Click to read the paper on arXiv

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.

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, LaTeX sanity checks,
  coverage gates. No network, no LLM, no API keys.

Everything else (LLM reasoning, web search, Semantic Scholar lookups, LaTeX
compilation) is delegated to the host agent by instruction. See
skills/paper-orchestra/references/host-integration.md
for per-host invocation (Claude Code, Cursor, Antigravity, Cline, Aider).

The seven skills

Steps 2 and 3 run in parallel (see skills/paper-orchestra/references/pipeline.md).

Install

git clone <this repo> ~/paper-orchestra
cd ~/paper-orchestra
pip install -r requirements.txt   # deterministic helpers only

Then symlink the skills you want into your host's skill directory:

# Claude Code
mkdir -p ~/.claude/skills
for s in paper-orchestra outline-agent plotting-agent literature-review-agent \
         section-writing-agent content-refinement-agent paper-writing-bench \
         paper-autoraters; do
  ln -sf ~/paper-orchestra/skills/$s ~/.claude/skills/$s
done

# Or for ~/.all-skills/
mkdir -p ~/.all-skills
for s in paper-orchestra outline-agent plotting-agent literature-review-agent \
         section-writing-agent content-refinement-agent paper-writing-bench \
         paper-autoraters; do
  ln -sf ~/paper-orchestra/skills/$s ~/.all-skills/$s
done

For Cursor / Antigravity / Cline / Aider, see skills/paper-orchestra/references/host-integration.md.

Optional integrations

The pipeline still requires zero API keys to run under any host with a
native web search tool. The only optional integration is for hosts that
lack one:

• Exa — research-paper-focused search engine. The
  literature-review-agent can use it as a Phase 1 candidate-discovery
  backend via skills/literature-review-agent/scripts/exa_search.py. Set
  EXA_API_KEY in your environment (the repo never commits a key) and the
  helper queries Exa with category: "research paper", returning 10–20
  candidates per query in the format the rest of the pipeline expects. See
  skills/literature-review-agent/references/exa-search-cookbook.md for
  the full recipe, query patterns, cost (~$0.007/query), and security
  notes.

  export EXA_API_KEY="your-key-here"   # https://dashboard.exa.ai/
  python skills/literature-review-agent/scripts/exa_search.py \
      --query "Sparse attention long context" --num-results 15
  

  Skip Exa entirely if your host (Claude Code, Cursor, Antigravity) already
  has a native web search tool — the agent will use that instead.

Quickstart

# 1. scaffold a workspace next to your raw materials
python skills/paper-orchestra/scripts/init_workspace.py --out workspace/

# 2. drop your inputs into workspace/inputs/
#    (idea.md, experimental_log.md, template.tex, conference_guidelines.md;
#     optional pre-existing figures go in workspace/inputs/figures/)

# 3. ask your coding agent:
#    "Run the paper-orchestra pipeline on ./workspace"

A ready-to-run toy case lives at examples/minimal/.

Repo layout

paper-orchestra/
├── README.md, LICENSE, CITATION.cff, requirements.txt
├── skills/                  # 7 skills + orchestrator
├── examples/minimal/        # toy end-to-end example
└── docs/
    ├── architecture.md      # deep-dive on the pipeline
    ├── paper-fidelity.md    # design-decision → paper page map
    └── coding-agent-integration.md  # per-host setup

Fidelity to the paper

Every agent prompt in skills/*/references/prompt.md is reproduced verbatim
from Appendix F of arXiv:2604.05018, with a header pointing to the page number.
See docs/paper-fidelity.md for a design-decision → paper-page map.

On top of the paper, this repo adds a few deterministic hardening scripts
(orphan-citation gate, anti-leakage grep, worklog-based rollback, provenance
snapshots). These are clearly marked as out-of-paper improvements in
docs/paper-fidelity.md.

Citation

If you use this skill pack, please cite the paper:

@article{song2026paperorchestra,
  title={{PaperOrchestra}: A Multi-Agent Framework for Automated {AI} Research Paper Writing},
  author={Song, Yiwen and Song, Yale and Pfister, Tomas and Yoon, Jinsung},
  journal={arXiv preprint arXiv:2604.05018},
  year={2026},
  url={https://arxiv.org/pdf/2604.05018}
}

It would have been fun if the repo wrote the paper.

License

MIT — see LICENSE.