v0.1.0 — Initial public release
A host-agent-pluggable skill pack implementing PaperOrchestra (Song et al., 2026, arXiv:2604.05018) for any coding agent.
Song, Y., Song, Y., Pfister, T., Yoon, J. PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing. arXiv:2604.05018, 2026.
What it is
Seven composable skills + a benchmark harness + four autoraters that turn Claude Code, Cursor, Antigravity, Cline, Aider, OpenCode (or any coding agent) into the PaperOrchestra five-agent paper-writing pipeline.
No API keys. No embedded LLM clients. No SDK dependencies. Skills are markdown instruction documents the host agent reads and executes using its own native tools. Deterministic Python helpers do only mechanical work (JSON schema validation, Levenshtein fuzzy citation matching, BibTeX formatting, citation gates, LaTeX sanity, refinement halt logic).
The seven skills
| Skill | Paper step | LLM calls | Role |
|---|---|---|---|
paper-orchestra |
orchestrator | — | Top-level driver |
outline-agent |
Step 1 | 1 | Idea + log + template + guidelines → outline JSON |
plotting-agent |
Step 2 | ~20–30 | Render plots & diagrams + optional VLM critique loop |
literature-review-agent |
Step 3 | ~20–30 | Web-search + S2 verify (Levenshtein > 70) + ≥90% citation integration |
section-writing-agent |
Step 4 | 1 | One single multimodal call drafting all remaining sections |
content-refinement-agent |
Step 5 | ~5–7 | Simulated peer review + strict accept/revert halt rules |
paper-writing-bench |
§3 | — | Reverse-engineer raw materials from existing papers |
paper-autoraters |
App. F.3 | — | Citation F1, LitReview Quality, SxS Paper, SxS LitReview |
Fidelity to the paper
All 13 prompts from Appendices D.4, F.1, F.2, F.3 are reproduced verbatim with per-page citations to the paper. See docs/paper-fidelity.md for the full design-decision → paper-page map.
What's included
- 76 files, ~6.8K lines
- 8
SKILL.mdinstruction documents - 35 reference documents (verbatim prompts, JSON schemas, rubrics, halt rules, integration guides)
- 19 deterministic Python helper scripts (with argparse CLIs)
- Realistic end-to-end example (
examples/minimal/— a fabricated but coherent Adaptive Top-K Attention paper case) - Architecture, paper-fidelity, and per-host integration docs
Quickstart
`bash
git clone https://github.com/Ar9av/paper-orchestra ~/paper-orchestra
cd ~/paper-orchestra
pip install -r requirements.txt
symlink into your host's skill directory (Claude Code shown)
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
`
Then ask your coding agent: "Run the paper-orchestra pipeline on ./workspace".
See docs/coding-agent-integration.md for Cursor, Antigravity, Cline, Aider, OpenCode setup.
Smoke-tested
All 10 deterministic helpers pass on real inputs:
validate_inputs.py✓validate_outline.py✓extract_metrics.py✓ (4 tables extracted from the example log)levenshtein_match.py✓ (incl. substring-bypass)check_cutoff.py✓ (PASS / FAIL paths)dedupe_by_id.py+bibtex_format.py✓ (real BibTeX entries with deterministic keys)orphan_cite_gate.py✓latex_sanity.py✓citation_coverage.py✓anti_leakage_check.py✓score_delta.py✓render_matplotlib.py✓ (real PNG at requested aspect ratio)render_diagram.py✓
Citation
If you use this skill pack, please cite the paper:
bibtex @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} }
License
MIT — see LICENSE.