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paper-digest论文文摘

Agent Skill

paper-digest 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

20,975

周安装

901

GitHub Stars

2

下载量

7,352
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:paper-digest(论文文摘)
来源仓库:https://github.com/damoonsh/paper-digest
安装命令:
openclaw skills install paper-digest
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 paper-digest

简介

给定 arXiv ID 或 URL,获取论文,生成子代理来读取其关键引文,并在下面编写执行摘要。

SKILL.md

name
paper-digest
description
Given an arXiv ID or URL, fetch the paper, spawn sub-agents to read its key citations, and write an executive summary under.
user-invocable
true
author
Damoon
version
0.0.1

Paper Digest

Input

  • arxiv_id: bare ID like 2305.11206 or full https://arxiv.org/abs/2305.11206 (Normalise: strip the URL prefix, extract bare ID.)

Step 1 — Fetch the main paper

Try HTML first: web.fetch https://arxiv.org/html/<arxiv_id>

  • If HTTP 200 → use this as paper_text.
  • If Falis: add v1 at the end, and try again: web.fetch https://arxiv.org/html/<arxiv_id>v1
  • else if all fails skip and ABORT!

If the paper_text is retrieved then write the summary to ~/.openclaw/workspace/papers/<arxiv-id>.md.

Step 2 — Extract citations

Note: DO NOT DO THIS STEP INSIDE sub-agents

Within the main agent and from paper_text, identify at most 5 citations the paper most directly builds on. Prioritize:

  • Papers that are explicitly extended or improved upon
  • Papers used as the primary baseline for comparison
  • Papers that provide the core architecture this work adopts
  • Papers referred to repeatedly (not just mentioned once) or that provide essential context

For each citation, extract either the arXiv ID or the title. Then resolve to an arXiv URL:

  • If an arXiv ID is in the reference → https://arxiv.org/html/<id>
  • Otherwise search https://arxiv.org/search/?query=<title>&searchtype=all and take the first match.

Step 3 — Spawn sub-agents for citations

*Note*: Ensure that the sub-agent related task is precise and concise so the sub-agent does not have to re-read the previously read SKILLs and files.

For each resolved citation:

  • Check if the file for citation exists: ~/.openclaw/workspace/papers/<arxiv-id>.md, if it does then skip and consider the sub-agent concluded.
  • If the previous step fails then spawn a sub-agent with this EXACT instruction in VERBATIM:

- Fetch https://arxiv.org/html/<citation_id> (or add v1 at the end, and try again: web.fetch https://arxiv.org/html/<arxiv_id>v1). If unavailable, SKIP. If retrieved then Write the summary to ~/.openclaw/workspace/papers/<arxiv-id>.md.

Step 4 — Write the executive summary

Check the citation summaries within ~/.openclaw/workspace/papers/ then utilize the main paper we are summarising with citation summaries and write a single markdown document in flowing prose (no bullet lists) to ~/.openclaw/workspace/digest/report_<arxiv-id>. Use this structure:

# <Title>

<What problem this solves and why it matters. Context and related references summary>

<What prior work missed and how this paper addresses that gap. Cite inline as [Author et al., YEAR](<arxiv_link>).

<Core method in plain terms>

<Headline result. How it differs from previous work.

<One limitation and one future direction>

<Detailed Ablations, benchmarks if present in this paper or cited references>

Rules

  • Every citation must be a markdown link: [Author et al., YEAR](<arxiv_or_url>)
  • No bullet lists in the output — prose only.
  • If a section is absent from the paper (e.g., no ablations), skip it silently.
  • Do not fabricate results, metrics, or author claims.
  • Citation resolution retry: If a citation URL cannot be resolved after one retry, write the citation as plain text without a link: [Author et al., YEAR].

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

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

83.79%
按下载量换算6,160

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install paper-digest 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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