Automates the collection and formatting of ML/AI research papers and news for a daily digest feed.

Install

mkdir -p .claude/skills/daily-digest && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/13211" && unzip -o skill.zip -d .claude/skills/daily-digest && rm skill.zip

Installs to .claude/skills/daily-digest

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Add today's ML/AI paper and news picks to the PaperTrace daily feed. Use when the user wants to update the daily page with new content.
135 chars✓ has a “when” trigger
Intermediate

Key capabilities

  • Generate daily digest content for PaperTrace
  • Update daily paper entries in `src/lib/daily.ts`
  • Update daily news entries in `src/app/daily/page.tsx`
  • Extract numerical results from paper abstracts
  • Verify content against official sources

How it works

The skill scrapes ML/AI paper and news content from specified sources, then formats and adds it to the PaperTrace daily feed. It enforces strict anti-hallucination rules for numerical data.

Inputs & outputs

You give it
ML/AI paper abstracts and official news announcements
You get back
Updated `dailyPapers` array in `src/lib/daily.ts` and `newsItems` array in `src/app/daily/page.tsx`

When to use daily-digest

  • Adding a new research paper to digest
  • Updating daily ML news
  • Curating AI paper feeds

About this skill

PaperTrace · 每日日报

为 PaperTrace 生成当天的日报内容,更新到 src/lib/daily.tssrc/app/daily/page.tsx


⛔ 反幻觉原则(所有内容均适用)

论文条目(dailyPapers)的数字必须来自:

  • arXiv abstract 页面(作者、标题、arXiv ID)
  • 论文 abstract 本身(主要结果数字)

新闻条目(newsItems)的内容必须来自:

  • 官方公告(官方博客、官方 HuggingFace 页面、官方 X/Twitter 账号)
  • 官方技术报告或 README

绝对禁止:

  • 用第三方媒体报道的数字填写 why/description(例如 "据报~81%")
  • 把推测性技术细节当作事实(例如训练硬件)
  • 用 "reportedly" / "据报" 等模糊措辞掩盖无法验证的来源

如果官方数字暂时无法获取,宁可省略该数字,不写模糊断言


1. 找内容

Paper 来源(按优先级):

https://huggingface.co/papers        ← 社区人气榜,首选
https://arxiv.org/list/cs.LG/recent
https://arxiv.org/list/cs.CL/recent
https://paperswithcode.com/latest

新闻来源(仅限官方):

官方 HuggingFace 模型页 README
官方博客(openai.com, anthropic.com, deepmind.google, ai.meta.com 等)
官方 X/Twitter 账号(@openai, @anthropic, @deepseek_ai 等)
官方技术报告 PDF

筛选标准(论文):

  • 解决清晰问题,不是 survey
  • 有明确数字结果(从 abstract 中可直接提取)
  • 与受众相关:LLM / Diffusion / RL / Efficient Training / Reasoning

目标:每日 2–5 篇 paper + 0–2 条 news,宁缺毋滥。


2. 生成论文字段

拿到 abstract 后,只使用 abstract 中明确出现的数字:

论文标题:[title]
arXiv ID:[XXXX.XXXXX]
Abstract:[粘贴]

请输出 JSON:
{
  "titleZh": "中文标题",
  "tags": ["从以下选 ≤3 个: Diffusion LM, Pre-training, Fine-tuning, LoRA, Efficient Inference, Reasoning, Alignment, RLHF, Multimodal, Theory, Benchmark, Code, Agent, RAG, Quantization, MoE, Vision"],
  "why": "英文,≤25词,格式:[做了什么] — [为什么重要],数字必须来自 abstract",
  "whyZh": "中文,≤30字,同格式"
}

3. 新闻条目格式

新闻加到 src/app/daily/page.tsxnewsItems 数组顶部

{
  date: "YYYY-MM-DD",           // 官方公告日期
  title: "英文标题",             // 准确描述事件
  titleZh: "中文标题",
  description: "...",           // 仅含官方来源确认的事实
  descriptionZh: "...",
  source: "Official Blog / HuggingFace / ...",  // 明确标注来源
  sourceUrl: "https://...",     // 直接链接到官方来源
  tag: "Release" | "Research" | "Industry",
}

Description 写法原则:

  • 用官方公告原文改写,不添加推测
  • 数字直接引用官方数据(例如从 HuggingFace README)
  • 如确实不确定某个数字,直接省略,不写 "~" 或 "reportedly"

4. 论文条目格式

加到 src/lib/daily.tsdailyPapers 数组顶部

{
  date: "YYYY-MM-DD",
  title: "英文原标题",
  titleZh: "中文标题",
  authors: "第一作者 et al.",
  arxivId: "XXXX.XXXXX",        // 只填 ID;非 arXiv 论文用 paperUrl 字段
  paperUrl: "...",               // 非 arXiv 时填(如 HuggingFace PDF 链接)
  tags: ["Tag1", "Tag2"],
  why: "...",                    // 数字必须来自 abstract 或官方 README
  whyZh: "...",
  pick: true,                    // 最多 1 篇
  slug: "paper-slug",            // 如果已有精读页则填
}

5. 验证

npm run build
  • 确认新条目在 /daily 顶部
  • 中英文切换正常
  • 检查 why/description 中无 "reportedly" / "~数字" / "据报" 等模糊措辞

快速清单

[ ] 确认内容来源为官方(论文/公告/README)
[ ] 从 abstract 提取数字,不从第三方报道引用
[ ] 加 paper 条目到 daily.ts 顶部
[ ] 加 news 条目到 page.tsx newsItems 顶部(如有)
[ ] npm run build 验证
[ ] git commit: "feat(daily): YYYY-MM-DD digest"

When not to use it

  • When using third-party media reports for numerical data
  • When speculating on technical details like training hardware
  • When official numbers are not available and would require vague assertions

Prerequisites

npm

Limitations

  • Numerical data for paper entries must come from arXiv abstract pages or the paper abstract itself
  • News content must come from official announcements, blogs, or technical reports
  • Cannot use third-party media reports for numerical data

How it compares

This workflow ensures that all numerical data and factual statements are directly sourced from official documents, preventing the inclusion of unverified or speculative information.

Compared to similar skills

daily-digest side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
daily-digest (this skill)03moReviewIntermediate
ai-sdk112moReviewAdvanced
react-expert86moReviewAdvanced
remotion-solar-tts03moReviewAdvanced

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