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emergence-paper-orchestra出现纸乐团

Agent Skill

emergence-paper-orchestra 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,189

周安装

129

GitHub Stars

公开资料未说明

下载量

1,001
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:emergence-paper-orchestra(出现纸乐团)
来源仓库:https://github.com/symbolscience/emergence-paper-orchestra
安装命令:
openclaw skills install emergence-paper-orchestra
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install emergence-paper-orchestra

简介

基于 PaperOrchestra 方法的高严谨学术写作框架。

  • 支持多主体协作与严格论证流程管理。
  • 适用于科研论文撰写或系统性分析报告生成。
  • 建议查阅原始文档以了解协作规则与接口规范。
  • emergence-paper-orchestra 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
emergence-paper-orchestra
title
Emergence PaperOrchestra
description
High-rigor, multi-agent scholarly writing framework based on the PaperOrchestra methodology.
version
1.0.0

Emergence PaperOrchestra Skill

This skill transforms raw ideas and unstructured data into high-rigor, submission-ready manuscripts. It functions as a Research Partner that proactively clarifies, critiques, and anchors content in verifiable evidence.

1. Core Workflow (Modular)

The process is designed for Human-in-the-Loop collaboration over potentially "narrow" IM channels (linear chat).

Phase 0: The Interactive Interview (Scaffolding)

The agent initiates an Interview Mode to capture tacit knowledge. Every user response is used to auto-update idea.md.

  • The Critic Persona: The agent acts as a Research Partner, identifying logical leaps or missing data points in the initial input.

Phase 1: Institutional Planning (Outline Agent)

Synthesize all inputs into a JSON Master Plan (stored in metadata.json).

Phase 2: Literature Strategy (Search Agent)

  • Macro Search: Foundational context.
  • Micro Search: Competitor benchmarking and citation verification via IDs (DOI/arXiv).

Phase 3: Modular Drafting (Writing Agent)

Draft strictly section-by-section into the sections/ directory to prevent context drift.

Phase 4: Peer Refinement (Refinement Agent)

Critical evaluation pass focusing on "Numerical Literalism" and "Zero Hallucination" compliance.


2. Agent Roles

RolePersona GoalRecommended System Prompt Hook
OrchestratorGlobal Consistency"Maintain the Master Plan. Ensure Section 4 answers the hypothesis in Section 1."
Search AgentVerification & Discovery"Find narrow queries documenting exact limitations of prior work."
Section WriterHigh-Density Composition"Adopt a dense, objective, and technical tone. No flourishes."
ReviewerCritical Evaluation"Act as a harsh conference reviewer. Identify every unsupported claim."
PartnerCritique & Refine"Challenge the user's premises. If an idea is vague, ask for data-backed specifics."

3. Best Practices

  • The "Interview-to-Persist" Loop: Use natural conversation to build the idea.md ground truth.
  • Scaffold Folders: Use the provided scaffold.sh to initialize the environment:

- idea.md: Methodology and user-provided context. - metadata.json: Master Plan & verified Citation bank. - content.md: The assembled final output.

  • Verification Loop: Always verify candidate papers via IDs (Semantic Scholar/DOI) before adding to the BibTeX bank.

4. Attribution & Citation

If you use this framework for scientific publications, please cite the original PaperOrchestra team:

@misc{song2026paperorchestramultiagentframeworkautomated,
      title={PaperOrchestra: A Multi-Agent Framework for Automated AI Research Paper Writing}, 
      author={Yiwen Song and Yale Song and Tomas Pfister and Jinsung Yoon},
      year={2026},
      eprint={2604.05018},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2604.05018}, 
}

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能力概览

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

87.01%
按下载量换算871

安全审计

VirusTotal

通过

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通过

Static analysis

通过

权限和风险

需要联网

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安装前确认

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