deepxiv-trending-digest
Automated pipeline to fetch, summarize, and rank the latest hot research papers into a markdown digest.
Install
mkdir -p .claude/skills/deepxiv-trending-digest && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/14218" && unzip -o skill.zip -d .claude/skills/deepxiv-trending-digest && rm skill.zipInstalls to .claude/skills/deepxiv-trending-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.
Summarize recent hot academic papers using deepxiv trending, brief, head, and section reads, then produce a markdown digest highlighting what each paper is about and which papers deserve deeper reading.Key capabilities
- →Find trending academic papers using DeepXiv
- →Briefly summarize candidate papers to screen them
- →Inspect the structure of promising papers using `--head`
- →Read specific high-value sections of papers using `--section`
- →Generate a markdown digest with recommendations for deeper reading
How it works
The skill pulls trending papers from DeepXiv, briefs each candidate, ranks them for deeper inspection, reads specific sections, and then compiles a markdown digest.
Inputs & outputs
When to use deepxiv-trending-digest
- →Get a weekly research summary
- →Find trending machine learning papers
- →Create a report of top papers for a team
- →Filter high-potential papers for deep reading
About this skill
DeepXiv Trending Digest
Use this skill when the user wants a recent hot-paper roundup, trending paper summary, weekly paper digest, or a markdown report based on DeepXiv trending papers.
Goal
Turn recent DeepXiv trending papers into a concise markdown digest:
- Find currently hot papers with
deepxiv trending - Brief each candidate with
deepxiv paper <id> --brief - Select the most promising papers for deeper inspection
- Inspect structure with
deepxiv paper <id> --head - Read only the most relevant sections with
deepxiv paper <id> --section ... - Write a clean
.mdsummary with recommendations
Default Workflow
1. Pull trending papers
Start with a small, recent set unless the user asks otherwise.
deepxiv trending --days 7 --limit 10 --json
Default heuristics:
- Use
--days 7for "recent hot papers" - Use
--limit 10for a manageable first pass - If the user asks for a broader roundup, use
--days 14or--days 30
2. Brief every candidate
For each selected arXiv ID, fetch a brief first:
deepxiv paper <arxiv_id> --brief
Capture:
- title
- arXiv ID
- publish date
- keywords
- TLDR
- citations if present
- GitHub URL if present
Do not jump to full text yet. --brief is the default screening step.
3. Rank for deeper reading
After reading briefs, choose the top 1-3 papers for deeper inspection.
Use signals like:
- strong novelty or surprising result
- practical relevance
- likely user interest
- unusually clear contribution
- useful code release
- especially strong social or research momentum
If a paper sounds incremental, unclear, or out of scope, keep it in the digest but skip deep reading.
4. Inspect paper structure
For the chosen papers:
deepxiv paper <arxiv_id> --head
Use --head to decide whether to drill down and which section matters most.
Look for sections such as:
- Introduction
- Method / Approach / Framework
- Experiments / Results / Evaluation
- Discussion / Limitations
Prefer section reads over full paper reads.
5. Read only high-value sections
Read at most 1-2 sections per paper unless the user explicitly asks for a deep dive.
Examples:
deepxiv paper <arxiv_id> --section Introduction
deepxiv paper <arxiv_id> --section Method
deepxiv paper <arxiv_id> --section Results
Selection guidance:
- Read
Introductionif the contribution is still fuzzy - Read
Methodif the core idea matters - Read
Resultsif the claim sounds strong and needs verification - Read
LimitationsorDiscussionif tradeoffs matter
Avoid reading everything.
Markdown Output
Write a markdown file in the current workspace unless the user gave a different path.
Recommended filename:
trending-paper-digest-YYYY-MM-DD.md
Recommended structure:
# Trending Paper Digest
Date: YYYY-MM-DD
Window: Last 7 days
Source: deepxiv trending
## Executive Summary
- 2-4 bullets with the main themes across the trending list
- Mention the 1-3 most promising papers
## Papers Reviewed
### 1. Paper Title (`arXiv:xxxx.xxxxx`)
What it is about:
Short paragraph based mainly on `--brief`.
Why it matters:
- Bullet
- Bullet
Worth deeper reading?
Yes/Maybe/No, with one sentence.
If deeper review was done:
Sections checked:
- Introduction
- Method
Deeper notes:
Short paragraph with the key insight, evidence, or caveat.
### 2. ...
## Recommended Deep Dives
### Paper Title
- Why it stands out
- Which section to read next
- What question it could answer
## Cross-Cutting Trends
- Repeated themes
- Common methods
- Shared limitations or hype signals
Writing Rules
- Keep the digest skimmable
- Prefer short paragraphs and flat bullets
- Separate "what it says" from "whether it is worth deeper reading"
- Be explicit when a conclusion is based only on
--brief - Be explicit when a conclusion is based on
--heador a section read - Do not pretend to have verified claims you have not checked
Decision Rules
- If briefs are enough for the user's request, stop there
- Use
--headonly for the most promising papers - Use
--sectiononly after--headsuggests a high-value section - Do not read full paper markdown unless the user explicitly asks for a full analysis
Minimal Example
deepxiv trending --days 7 --limit 5 --json
deepxiv paper 2603.20639 --brief
deepxiv paper 2603.26221 --brief
deepxiv paper 2603.20639 --head
deepxiv paper 2603.20639 --section Introduction
Then write the digest as markdown and clearly label:
- all reviewed papers
- which papers were only briefed
- which papers received deeper inspection
When not to use it
- →When the user needs a full, in-depth analysis of every paper
- →When the papers are not from DeepXiv or similar academic repositories
- →When the goal is to write a detailed research paper rather than a digest
Limitations
- →The skill focuses on DeepXiv trending papers
- →The skill aims for a concise digest, not a full analysis of each paper
- →The skill recommends reading at most 1-2 sections per paper unless explicitly asked
How it compares
This skill provides a structured workflow for efficiently digesting trending academic papers by prioritizing brief summaries and targeted section reads, unlike reading full papers sequentially.
Compared to similar skills
deepxiv-trending-digest side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| deepxiv-trending-digest (this skill) | 0 | 3mo | Review | Intermediate |
| read-arxiv-paper | 16 | 5mo | No flags | Intermediate |
| arxiv-to-md | 4 | 7mo | No flags | Beginner |
| arxiv-viewer | 4 | 6mo | Review | Beginner |
Try saying
Example prompts that trigger this skill in your AI assistant.
You might also like
read-arxiv-paper
karpathy
Use this skill when when asked to read an arxiv paper given an arxiv URL
arxiv-to-md
solatis
Convert arXiv papers to LLM-consumable markdown. Invoke when user provides an arXiv ID or URL, or when syncing academic papers from a PDF folder to a markdown destination.
arxiv-viewer
actionbook
View, search, and download academic papers from arXiv. Supports API queries, web scraping via Actionbook, and HTML paper reading via ar5iv. Use when user asks about arxiv papers, academic papers, research papers, paper summaries, latest papers, or wants to search/download/read papers.
daily-news-report
sickn33
Scrapes content based on a preset URL list, filters high-quality technical information, and generates daily Markdown reports.
summarize
khaterdev
Summarize articles, documents, or web pages
extract-transcript
pamelafox
>-