dvcrn Scholar Research Skill
Search and analyze academic papers from open access sources with credibility scoring and detailed summaries.
When to Use
- User wants to find papers on a specific topic
- User needs credibility assessment of papers
- User wants summarized research with methodology
- User wants to track field evolution over time
- User needs figures/tables extracted from top papers
Data Sources (Free/Open Access)
The skill searches across these sources:
- arXiv - Pre-prints (Physics, Math, CS, q-bio, q-fin)
- PubMed/PMC - Biomedical & Life sciences
- DOAJ - Peer-reviewed OA journals (all disciplines)
- OpenAlex - 250M+ papers metadata
- CORE - Largest OA full-text aggregator
- Semantic Scholar - Limited free tier
- Unpaywall - Finds free versions of paywalled papers
- CrossRef - All DOI metadata
- bioRxiv - Biology pre-prints
- medRxiv - Medicine pre-prints
- Zenodo - EU research data/papers
- HAL - French OA repository
- J-STAGE - Japanese OA repository
- SSRN - Economics, Law pre-prints
User-Added Sources
Users can add custom sources via config:
{
"custom_sources": [
{"name": "My University", "url": "https://repo.my.edu", "api": "..."}
]
}
Scoring System
Default Weights (Total: 100 + 40 bonus)
Paper Quality (100 points):
| Factor | Weight | Description |
|---|---|---|
| citation_count | 15% | Times cited by other papers |
| publication_recency | 10% | Newer = more relevant |
| author_reputation | 12% | Combined h-index of authors |
| journal_impact | 12% | Impact factor, CiteScore |
| peer_review_status | 10% | Peer-reviewed vs pre-print |
| open_access | 8% | Free to read/download |
| retraction_status | 10% | Not retracted |
| author_network | 8% | Connected to established network |
| funder_acknowledgment | 5% | Clear funding sources |
| reproducibility | 5% | Code/data available |
Bonus Points (up to +40):
- Author Trust: +20 max
- Journal Reputation: +20 max
Customizing Weights
Users can modify weights in config:
{
"scoring": {
"citation_count": 25,
"publication_recency": 5
}
}
Or use preset profiles: "strict", "recent_only", "balanced"
Output Format
Top Papers (default: 5, user-configurable)
[1] Paper Title (Year)
Score: 95/100 | Citations: 234
📄 PDF | 📊 Figures | 🔬 SI
Summary: [One paragraph]
Methodology: [Detailed breakdown]
Field Timeline
📈 FIELD TIMELINE (N papers)
2024: ████████████████████ 15 papers
→ Major: [Breakthrough 1]
→ Trend: [Trend 1]
2023: ████████████████ 12 papers
→ Major: [Breakthrough 2]
Credibility Distribution
📊 Credibility Distribution
Score 90-100: ██ (5) ★ Top
Score 70-89: ████████ (15)
Score 50-69: ██████████████████ (25)
Score 30-49: ██████████ (10)
Score 0-29: ██ (2)
[████████████░░░░░░░░░] Average: 58/100
Workflow
- Search: Query across all enabled sources
- Fetch: Download metadata + PDFs
- Score: Calculate credibility scores
- Sort: Rank by score + relevance
- Present: Top N papers + timeline
- Extract: Figures from top-scored papers (optional)
Usage Examples
Find papers on: machine learning
Fields: computer science, AI
Top papers: 5
Extract figures: true
Find papers on: quantum computing
Fields: physics
Top papers: 10
Extract figures: false
Dependencies
- Python 3.8+
- requests (API calls)
- beautifulsoup4 (parsing)
- pypdf2 (PDF extraction)
- opencv-python (figure detection)
- transformers (summarization)
- matplotlib (visualization)
Configuration
See config.json for:
- API keys
- Source enable/disable
- Scoring weights
- Display preferences
- Custom sources
Notes
- Always prioritize open access sources
- Cite sources in responses
- Warn about pre-print limitations
- Check retraction status when available
- Respect rate limits