Batch 11: arXiv Paper Reader + Custom Morning Brief + Event Guest Confirmation + Daily Reddit Digest
Sources: arXiv-Paper-Reader, Custom-Morning-Brief, Event-Guest-Confirmation, Daily-Reddit-Digest Entities: SuperCall, Twilio, reddit-readonly Overview: 4 new domain sections added
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wiki/sources/Custom-Morning-Brief.md
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wiki/sources/Custom-Morning-Brief.md
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---
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title: "Custom Morning Brief"
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type: source
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tags: [agent-use-case, automation, productivity, telegram]
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date: 2026-04-16
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---
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## Source File
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- [[raw/Agent/usecases/Custom-Morning-Brief.md]]
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## Summary
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- 核心主题：OpenClaw 定时主动任务——每日个性化晨报
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- 问题域：早晨 30 分钟用于刷新闻/查日历/看任务，"最生产力时间"浪费在信息获取而非决策
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- 方法/机制：定时任务（Telegram/Discord/iMessage）= 新闻聚合 + 待办推送 + AI 主动推荐任务
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- 结论/价值：利用夜间待机时间完成信息聚合，起床即可做决策
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## Key Claims
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- 晨报核心价值：AI 主动推荐可代劳任务，而非仅推送信息
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- 夜间待机时间利用：用户睡眠期间 AI 完成研究任务，产出可直接使用（完整脚本/商业提案）
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- 自定义接口：用户只需通过短信向 Bot 说明需求，AI 自动调整晨报结构
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- Alex Finn 的视频激发此工作流设计
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## Key Quotes
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> "You're spending your most productive morning hours just getting oriented. Meanwhile, your AI agent sits idle all night. The morning brief turns idle overnight hours into productive prep time — you wake up to work already done."
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> "Full drafts (not just ideas) are the key to saving time. Wake up to scripts, not suggestions."
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## Key Concepts
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- [[定时主动任务]]：Agent 在无用户请求时主动执行并推送结果，而非等待 prompt
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- [[晨报自动化]]：早晨信息聚合+任务推荐一体化工作流
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- [[AI推荐任务]]：Agent 主动识别可代劳事项，是晨报最有价值的部分
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## Key Entities
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- [[Alex Finn]]：YouTube 视频《Life-Changing OpenClaw Use Cases》作者，激发晨报工作流设计
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- [[OpenClaw]]：晨报工作流的执行平台，支持 Telegram/Discord/iMessage 多渠道推送
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## Connections
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- [[Alex Finn]] ← inspired ← [[Custom Morning Brief]]
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- [[Custom Morning Brief]] ← implements ← [[定时主动任务]]
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- [[定时主动任务]] ← uses ← [[OpenClaw]]
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- [[Custom Morning Brief]] ← integrates ← [[Todoist]]（任务获取）
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- [[Custom Morning Brief]] ← integrates ← [[x-research-v2]]（社交热点研究，可选）
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## Contradictions
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wiki/sources/Daily-Reddit-Digest.md
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wiki/sources/Daily-Reddit-Digest.md
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---
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title: "Daily Reddit Digest"
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type: source
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tags: [agent-use-case, reddit, content-curation, automation]
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date: 2026-04-16
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---
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## Source File
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- [[raw/Agent/usecases/Daily-Reddit-Digest.md]]
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## Summary
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- 核心主题：OpenClaw Agent 每日 Reddit 内容聚合工作流
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- 问题域：手动浏览多个 subreddit 费时，热门帖子筛选依赖算法而非人工判断
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- 方法/机制：reddit-readonly skill 读取指定 subreddits（hot/new/top）+ AI 按偏好规则过滤 + 每日定时推送
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- 结论/价值：Read-only 模式只读不互动，建立内容偏好记忆实现个性化digest
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## Key Claims
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- reddit-readonly skill 无需认证，直接读取 Reddit 热门/New/Top 帖子
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- AI 维护内容偏好记忆（memory），随时间优化 digest 质量
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- 每日下午 5 点定时执行，自动推送 Telegram/指定渠道
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- Read-only 约束：无发帖/投票/评论，仅信息消费
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## Key Quotes
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> "Create a separate memory for the reddit processes, about the type of posts I like to see and every day ask me if I liked the list you provided. Save my preference as rules in the memory to use for a better digest curation."
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## Key Concepts
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- [[Reddit内容聚合]]：多 subreddit 热门/New/Top 帖子批量获取与筛选
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- [[内容偏好记忆]]：AI 维护用户内容偏好规则，实现 digest 个性化
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- [[定时内容推送]]：每日固定时间自动执行并推送 digest
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- [[Read-only API]]：仅消费数据不产生互动，降低账号风险
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## Key Entities
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- [[reddit-readonly]]：ClawHub 插件，无需认证的 Reddit 只读 skill
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- [[Reddit]]：美国最大社区内容平台，AMAs/hot/new/top 多维度排序
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## Connections
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- [[Daily Reddit Digest]] ← uses ← [[reddit-readonly]]
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- [[Daily Reddit Digest]] ← stores ← [[内容偏好记忆]]
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- [[reddit-readonly]] ← reads ← [[Reddit]]
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- [[Daily Reddit Digest]] ← triggers ← [[定时内容推送]]
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## Contradictions
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wiki/sources/Event-Guest-Confirmation.md
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---
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title: "Event Guest Confirmation"
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type: source
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tags: [agent-use-case, voice-ai, supercall, twilio]
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date: 2026-04-16
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---
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## Source File
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- [[raw/Agent/usecases/Event-Guest-Confirmation.md]]
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## Summary
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- 核心主题：SuperCall 批量外呼确认活动出席
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- 问题域：20+ 人活动手动电话确认费时费力——电话tag、遗忘记录、饮食限制/Plus-one 收集困难
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- 方法/机制：SuperCall AI 语音 Agent 逐一呼叫宾客人列，收集出席意向和备注，编译汇总报告
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- 结论/价值：批量外呼+结构化汇总，单次电话费用（Twilio分钟计费）
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## Key Claims
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- SuperCall 是完全独立的语音 Agent，呼叫过程不访问 OpenClaw Gateway，无数据泄露风险
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- AI Persona 沙箱化：每通电话独立上下文，不跨对话记忆，防止对话操纵
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- 调用链路：SuperCall → OpenAI GPT-4o Realtime API → Twilio 拨号
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- 完整工作流：准备宾客人列 → 单个外呼 → 记录结果 → 全量汇总
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## Key Quotes
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> "SuperCall is a fully standalone voice agent. The AI persona on the call only has access to the context you provide (the persona name, the goal, and the opening line). It cannot access your gateway agent, your files, your other tools, or anything else."
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## Key Concepts
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- [[AI外呼确认]]：AI 语音 Agent 批量执行活动出席确认
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- [[沙箱化 Persona]]：独立上下文重置，隔离每通电话防止数据泄露
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- [[AI Persona]]：AI 外呼中扮演特定角色的对话 Agent
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## Key Entities
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- [[SuperCall]]：OpenClaw 语音外呼插件，@xonder/supercall，GPT-4o Realtime 语音驱动
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- [[Twilio]]：电话拨号基础设施，按分钟计费
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- [[OpenAI Realtime API]]：GPT-4o Realtime 语音模型，支撑 SuperCall 对话能力
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## Connections
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- [[Event Guest Confirmation]] ← uses ← [[SuperCall]]
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- [[SuperCall]] ← calls ← [[OpenAI Realtime API]]
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- [[SuperCall]] ← dials via ← [[Twilio]]
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- [[Event Guest Confirmation]] ← applies ← [[沙箱化 Persona]]
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## Contradictions
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---
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title: "arXiv Paper Reader"
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type: source
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tags: [research, arxiv, openclaw-skill]
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tags: [agent-use-case, research, arxiv, llm]
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date: 2026-04-16
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---
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## Source File
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- [[raw/Agent/usecases/arxiv-paper-reader.md]]
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- [[raw/Agent/usecases/arXiv-Paper-Reader.md]]
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## Summary
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- 核心主题：基于 OpenClaw Agent 的 arXiv 论文阅读助手工作流
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- 问题域：PDF 下载后切换论文丢失上下文、LaTeX 公式难以解析
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- 方法/机制：Prismer AI 的 arxiv-reader skill（3 个工具：arxiv_fetch/arxiv_sections/arxiv_abstract）；Node.js 原生实现无需 Docker；直接从 arXiv 下载并自动扁平化 LaTeX 源码
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- 结论/价值：对话式论文阅读，支持摘要浏览、多篇对比、章节定位、结果缓存
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- 核心主题：OpenClaw Agent 论文阅读助手工作流
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- 问题域：arXiv PDF 阅读痛点——下载 PDF、切换丢失上下文、LaTeX 符号难解析
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- 方法/机制：Prismer arxiv-reader skill（3 工具）+ LaTeX 源码自动展平 + 多篇对比表格 + 本地缓存
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- 结论/价值：对话式论文阅读，无需离开工作区，支持按 ID 获取、结构扫描、摘要批量 triage、深度问答
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## Key Claims
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- arxiv-reader skill 无需 Docker 或 Python，通过 Node.js 内置模块独立运行
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- LaTeX 源码自动展平（flatten includes），消除公式解析障碍
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- 多篇论文可并行获取摘要并生成对比表格，按相关性排序
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- 结果本地缓存，回访论文秒级加载
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- arxiv-reader skill 运行于 OpenClaw，无 Docker/Python 依赖，直接通过 Node.js 内置模块实现
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- LaTeX 源码自动解压并展平，消除 PDF 阅读器的上下文跳跃问题
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- 多篇论文可批量获取摘要并生成对比表格，辅助 reading list 优先级排序
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- 结果本地缓存，二次访问即时返回
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## Key Quotes
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> "Reading arXiv papers means downloading PDFs, losing context when switching between papers, and struggling to parse dense LaTeX notation."
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> "Reading arXiv papers means downloading PDFs, losing context when switching between papers, and struggling to parse dense LaTeX notation. You want to read, analyze, and compare papers conversationally without leaving your workspace."
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## Key Concepts
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- [[arXiv-API]]：论文元数据和 PDF 源码获取接口，支持 ID 检索
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- [[LaTeX-Flattening]]：自动解析并合并 LaTeX 源码中的 \include 语句，生成可读文本
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- [[arxiv-reader-skill]]：Prismer 项目开源 skill，包含 fetch/sections/abstract 三个工具
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- [[LaTeX Flattening]]：自动合并 LaTeX \include 子文件生成可读连续文档
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- [[arxiv-reader skill]]：Prismer AI 开发的 OpenClaw skill，3 工具接口（arxiv_fetch/arxiv_sections/arxiv_abstract）
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## Key Entities
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- [[Prismer-AI]]：arxiv-reader skill 的开发方，GitHub 仓库为 Prismer-AI/Prismer
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- [[Prismer AI]]：arxiv-reader skill 开发方，GitHub 仓库 Prismer-AI/Prismer
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- [[arXiv]]：康奈尔大学运营的开放获取论文预印本平台
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## Connections
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- [[OpenClaw]] ← 平台 ← [[arXiv-Paper-Reader]]
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- [[Personal-Knowledge-Base-RAG]] ← 类似工作流 ← [[arXiv-Paper-Reader]]
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- [[Prismer AI]] ← provides ← [[arxiv-reader skill]]
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- [[arxiv-reader skill]] ← enables ← [[LaTeX Flattening]]
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- [[arXiv Paper Reader]] ← extends ← [[arxiv-reader skill]]
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## Contradictions
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