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daily-paper-generator

Find recent papers on a research topic from arXiv, bioRxiv, or both. Narrow candidates through scored shortlists, then produce structured Chinese and English summaries with paper metadata, limitations, and an explanation of the final selection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Use when the user asks to generate daily paper digests on a general topic. This skill supports both arXiv and bioRxiv (or either one), then produces structured Chinese/English summaries for selected papers.

설치 방법 보기

이럴 때 유용합니다

  • Prepare daily or weekly research paper digests
  • Search recent papers across arXiv and bioRxiv
  • Compare candidate papers using scored shortlists
  • Keep structured Chinese and English reading notes

포함된 파일(6)

  • SKILL.md4.0 KB
  • example/daily paper example.md6.1 KB
  • references/keywords.md1.7 KB
  • references/quality-criteria.md4.4 KB
  • references/writing-style.md4.6 KB
  • scripts/arxiv_search.py9.6 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Daily Paper Generator

Overview

Discover, screen, and summarize recent papers for any research topic.

Supported sources:

  • arXiv
  • bioRxiv
  • both (--source both)

Core workflow:

  1. Define topic query and time window
  2. Search papers from arXiv / bioRxiv
  3. Select Top 10 candidates per field
  4. Score and narrow to Top 3 per field
  5. Choose Top 1 per field
  6. Generate bilingual summaries
  7. Save outputs to daily paper/

When to Use

Use this skill when:

  • The user asks for a daily/weekly paper digest on any topic
  • The user wants recent papers from arXiv and/or bioRxiv
  • The user needs structured bilingual notes for reading and tracking

Output Format

Each summary should contain:

  1. Paper title
  2. Authors and venue/source
  3. Link(s) and date
  4. Chinese review (~300 words)
  5. English review (concise academic prose)
  6. Metadata table
  7. Appendix (optional resources)

Quick Reference

TaskMethod
Search papersUse scripts/arxiv_search.py with `--source arxiv
Topic selectionUse general-topic queries from references/keywords.md
Evaluate qualityUse references/quality-criteria.md
Write Chinese reviewUse references/writing-style.md
Write English reviewFollow scientific writing best practices

Workflow

Step 1: Define query

Choose a concrete topic query. Examples:

  • test-time adaptation for medical imaging
  • multimodal foundation model for healthcare
  • protein language model interpretability

Step 2: Search arXiv and/or bioRxiv

Use helper script:

python skills/daily-paper-generator/scripts/arxiv_search.py \
  --query "test-time adaptation for medical imaging" \
  --source both \
  --months 1 \
  --max-results 80 \
  --output /tmp/papers.json

Notes:

  • --source arxiv: arXiv only
  • --source biorxiv: bioRxiv only
  • --source both: merge both sources and sort by date

Step 3: Top 10 candidate selection (per field)

For each candidate paper:

  1. Check topic relevance from title + abstract
  2. Remove obviously off-topic papers
  3. Keep Top 10 candidates for this field

Minimum rule:

  • Do not jump directly from raw search results to final paper.
  • Keep an explicit Top 10 list first.

Step 4: Top 3 quality shortlist (per field)

For the Top 10 pool:

  1. Score each paper with references/quality-criteria.md
  2. Rank by weighted score
  3. Keep Top 3

Step 5: Final Top 1 selection (per field)

For the Top 3 shortlist:

  1. Compare novelty + method completeness + experimental credibility
  2. Check practical impact for the field
  3. Select Top 1 as the final pick

Required output trace:

  • Top 10 candidate list
  • Top 3 scored shortlist (with weighted scores)
  • Final Top 1 and one-paragraph selection rationale

Step 6: Generate bilingual summaries

For each selected paper, generate:

  • 中文评语:背景、挑战、贡献、方法、结果、局限
  • English Review: concise, factual, non-formulaic

Step 7: Save output

Recommended directory and naming:

daily paper/
  YYYY-MM-DD-HHMM-paper-1.md
  YYYY-MM-DD-HHMM-paper-2.md
  YYYY-MM-DD-HHMM-paper-3.md

Additional Resources

  • references/keywords.md: general-topic query templates
  • references/quality-criteria.md: scoring rubric
  • references/writing-style.md: review writing style
  • example/daily paper example.md: output example
  • scripts/arxiv_search.py: arXiv + bioRxiv search helper

Important Notes

  1. Use explicit topic queries, avoid single-word vague queries.
  2. Keep the time window explicit (--months N).
  3. Distinguish source in metadata (arxiv vs biorxiv).
  4. Use the fixed narrowing rule: Top 10 -> Top 3 -> Top 1 (per field).
  5. If a paper lacks robust evaluation, mark confidence and limitations clearly.
  6. Do not fabricate unavailable fields (institution/GitHub/code links).

리뷰

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