daily-paper-generator
Daily Paper Generator
Overview
Discover, screen, and summarize recent papers for any research topic.
Supported sources:
- arXiv
- bioRxiv
- both (
--source both)
Core workflow:
- Define topic query and time window
- Search papers from arXiv / bioRxiv
- Select Top 10 candidates per field
- Score and narrow to Top 3 per field
- Choose Top 1 per field
- Generate bilingual summaries
- 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:
- Paper title
- Authors and venue/source
- Link(s) and date
- Chinese review (~300 words)
- English review (concise academic prose)
- Metadata table
- 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 imagingmultimodal foundation model for healthcareprotein 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:
- Check topic relevance from title + abstract
- Remove obviously off-topic papers
- 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:
- Score each paper with
references/quality-criteria.md - Rank by weighted score
- Keep Top 3
Step 5: Final Top 1 selection (per field)
For the Top 3 shortlist:
- Compare novelty + method completeness + experimental credibility
- Check practical impact for the field
- 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 templatesreferences/quality-criteria.md: scoring rubricreferences/writing-style.md: review writing styleexample/daily paper example.md: output examplescripts/arxiv_search.py: arXiv + bioRxiv search helper
Important Notes
- Use explicit topic queries, avoid single-word vague queries.
- Keep the time window explicit (
--months N). - Distinguish source in metadata (
arxivvsbiorxiv). - Use the fixed narrowing rule: Top 10 -> Top 3 -> Top 1 (per field).
- If a paper lacks robust evaluation, mark confidence and limitations clearly.
- Do not fabricate unavailable fields (institution/GitHub/code links).
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