🧪 Skills
Scholar Research
Search, analyze, and summarize peer-reviewed academic papers from open access sources. Provides credibility scoring, visualization, timeline generation, and...
v1.0.0
Description
name: scholar-research description: "Search, analyze, and summarize peer-reviewed academic papers from open access sources. Provides credibility scoring, visualization, timeline generation, and figure extraction for top papers."
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
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