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PaperOrchestra

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An automated AI research-paper writer based off Google's PaperOrchestra paper's implementation through a skills - benchmark + autoraters using any coding agent (Claude Code, Cursor, Antigravity, Cline, Aider). No API keys, no LLM SDKs.

Skills575 estrellas80 forksPythonNOASSERTIONActualizado 10d ago
ClaudeWave Trust Score
87/100
Trusted
Passed
  • License: NOASSERTION
  • Actively maintained (<30d)
  • Healthy fork ratio
  • Clear description
  • Topics declared
Last scanned: 6/11/2026
Install as a Claude Code skill
Method: Clone
Terminal
git clone https://github.com/Ar9av/PaperOrchestra ~/.claude/skills/paperorchestra
1. Clone the repository into your ~/.claude/skills directory (or copy the skill folder containing SKILL.md).
2. Start a new Claude Code session so the skill registry reloads.
3. Invoke it by name, or let Claude trigger it automatically when the task matches.
💡 If the repo bundles several skills, copy only the folders you need.

9 items en este repositorio

Pre-pipeline aggregator that scans AI agent cache directories (.claude, .cursor, .antigravity, .openclaw) or any user-specified directory for experimentation logs, extracts insights and numeric results, and formats them as PaperOrchestra-ready inputs (idea.md + experimental_log.md). TRIGGER when the user says "aggregate my agent logs for paper writing", "extract experiments from my coding agent history", "prepare PaperOrchestra inputs from my cache", "turn my agent logs into a paper", mentions a folder or directory they want to use as the basis for a paper, or wants to run PaperOrchestra but only has scattered agent experiment histories rather than structured inputs. Run this BEFORE paper-orchestra. Also called automatically by paper-orchestra when workspace/inputs/idea.md or workspace/inputs/experimental_log.md are missing.

Instalar

Step 5 of the PaperOrchestra pipeline (arXiv:2604.05018). Iteratively refine drafts/paper.tex by simulating peer review and applying targeted revisions, with strict accept/revert halt rules. Maintains a worklog and snapshots each iteration so revert is real, not symbolic. TRIGGER when the orchestrator delegates Step 5 or when the user asks to "refine the draft", "iterate on the paper", or "run peer review on this paper".

Instalar

Step 3 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the literature search strategy from outline.json — discover candidate papers via web search, verify them through Semantic Scholar (Levenshtein > 70 fuzzy title match, temporal cutoff, dedup by paperId), cross-corroborate against Crossref + OpenAlex to flag hallucinated citations, build a BibTeX file, and draft Introduction + Related Work using ≥90% of the verified pool. Runs in parallel with the plotting-agent. TRIGGER when the orchestrator delegates Step 3 or when the user asks to "find citations for my paper", "draft the related work", or "build the bibliography".

Instalar

Step 1 of the PaperOrchestra pipeline (arXiv:2604.05018). Convert (idea.md, experimental_log.md, template.tex, conference_guidelines.md) into a strict JSON outline containing a plotting plan, literature search plan (Intro + Related Work), and section-level writing plan with citation hints. TRIGGER when the orchestrator delegates Step 1 or when the user asks to "outline a paper from raw materials" or "generate the paper structure".

Instalar

Run the four paper-quality autoraters from PaperOrchestra (arXiv:2604.05018, App. F.3) — Citation F1 (P0/P1 partition + Precision/Recall/F1), Literature Review Quality (6-axis 0-100 with anti-inflation rules), SxS Overall Paper Quality (side-by-side), and SxS Literature Review Quality (side-by-side). TRIGGER when the user asks to "score this paper draft", "evaluate against the benchmark", "compare two papers", or "run the autoraters".

Instalar

Orchestrate the full PaperOrchestra (Song et al., 2026, arXiv:2604.05018) five-agent pipeline to turn unstructured research materials (idea, experimental log, LaTeX template, conference guidelines, optional figures) into a submission-ready LaTeX manuscript and compiled PDF. TRIGGER when the user asks to "write a paper from my experiments", "turn this idea and these results into a paper", "generate a conference submission", "run paper-orchestra on X", or otherwise wants the end-to-end paper-writing pipeline. Coordinates the outline-agent, plotting-agent, literature-review-agent, section-writing-agent, and content-refinement-agent skills.

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Reverse-engineer raw materials (Sparse idea, Dense idea, experimental log) from an existing AI research paper to build a benchmark case for evaluating paper-writing pipelines. Replicates the PaperWritingBench dataset construction procedure from arXiv:2604.05018 §3 / App. C. TRIGGER when the user asks to "build a benchmark case from this paper", "reverse-engineer raw materials", or "evaluate my pipeline against PaperWritingBench".

Instalar

Step 2 of the PaperOrchestra pipeline (arXiv:2604.05018). Execute the visualization plan from outline.json — render plots and conceptual diagrams from experimental_log.md and idea.md, optionally refine via VLM critique loop, and produce context-aware captions. Runs in parallel with the literature-review-agent. TRIGGER when the orchestrator delegates Step 2 or when the user asks to "generate the figures for my paper" or "render the plots from this experiment log".

Instalar

Step 4 of the PaperOrchestra pipeline (arXiv:2604.05018). ONE single multimodal LLM call that drafts the remaining paper sections (Abstract, Methodology, Experiments, Conclusion), extracts numeric values from experimental_log.md into LaTeX booktabs tables, splices the generated figures from Step 2, and merges everything into the template that already contains Intro + Related Work from Step 3. TRIGGER when the orchestrator delegates Step 4 or when the user asks to "write the methodology and experiments sections" or "fill in the rest of the paper".

Instalar
Casos de uso

Resumen de Skills

README no disponible. Visita el repo en GitHub para la documentación completa.
agentic-aiai-researchanthropicantigravityarxivautomated-paper-writingclaude-codeclaude-skillscoding-agentscursorlatexliterature-reviewllm-agentsmulti-agentpaper-orchestrapaperorchestraresearch-papersemantic-scholarskill-pack

Lo que la gente pregunta sobre PaperOrchestra

¿Qué es Ar9av/PaperOrchestra?

+

Ar9av/PaperOrchestra es skills para el ecosistema de Claude AI. An automated AI research-paper writer based off Google's PaperOrchestra paper's implementation through a skills - benchmark + autoraters using any coding agent (Claude Code, Cursor, Antigravity, Cline, Aider). No API keys, no LLM SDKs. Tiene 575 estrellas en GitHub y se actualizó por última vez 10d ago.

¿Cómo se instala PaperOrchestra?

+

Puedes instalar PaperOrchestra clonando el repositorio (https://github.com/Ar9av/PaperOrchestra) o siguiendo las instrucciones del README en GitHub. ClaudeWave también te ofrece bloques de instalación rápida en esta misma página.

¿Es seguro usar Ar9av/PaperOrchestra?

+

Nuestro agente de seguridad ha analizado Ar9av/PaperOrchestra y le ha asignado un Trust Score de 87/100 (tier: Trusted). Revisa el desglose completo de comprobaciones superadas y flags en esta página.

¿Quién mantiene Ar9av/PaperOrchestra?

+

Ar9av/PaperOrchestra es mantenido por Ar9av. La última actividad registrada en GitHub es de 10d ago, con 1 issues abiertos.

¿Hay alternativas a PaperOrchestra?

+

Sí. En ClaudeWave puedes explorar skills similares en /categories/skills, ordenados por popularidad o actividad reciente.

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