Daily Paper GeneratorSAFE

Semi-automated research assistant for academic research and software development. Supports Claude Code, Codex CLI, Kimi Code CLI, and OpenCode across ideation, coding, experiments, writing, and publication.

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: daily-paper-generator
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.
version: 0.5.1
---

# 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|biorxiv|both` |
| 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:

```bash
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:

```text
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).

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

What the source does

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Network

declared (3 observation(s))

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pinned

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No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.