Agent SkillsGalaxy-Dawn/claude-scholar › daily-paper-generator

daily-paper-generator

GitHub

该 Skill 用于根据指定主题从 arXiv/bioRxiv 检索最新论文,经筛选评分后生成中英文结构化摘要。适用于每日/每周学术文献综述、阅读追踪及科研灵感发现。

skills/daily-paper-generator/SKILL.md Galaxy-Dawn/claude-scholar

Trigger Scenarios

用户请求生成特定主题的每日或每周论文摘要 用户需要获取 arXiv 或 bioRxiv 的最新研究进展

Install

npx skills add Galaxy-Dawn/claude-scholar --skill daily-paper-generator -g -y
More Options

Use without installing

npx skills use Galaxy-Dawn/claude-scholar@daily-paper-generator

指定 Agent (Claude Code)

npx skills add Galaxy-Dawn/claude-scholar --skill daily-paper-generator -a claude-code -g -y

安装 repo 全部 skill

npx skills add Galaxy-Dawn/claude-scholar --all -g -y

预览 repo 内 skill

npx skills add Galaxy-Dawn/claude-scholar --list

SKILL.md

Frontmatter
{
    "name": "daily-paper-generator",
    "version": "0.5.1",
    "description": "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."
}

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

Task Method
Search papers Use scripts/arxiv_search.py with `--source arxiv
Topic selection Use general-topic queries from references/keywords.md
Evaluate quality Use references/quality-criteria.md
Write Chinese review Use references/writing-style.md
Write English review Follow 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).

Version History

  • 2f7766f Current 2026-07-25 09:08

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Metadata

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Indexed
2026-07-25 09:08

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