Scholar Research

v1.0.0

Search, analyze, and summarize peer-reviewed academic papers from open access sources. Provides credibility scoring, visualization, timeline generation, and...

0· 464· 1 versions· 1 current· 1 all-time· Updated 23h ago· MIT-0
byJingxiang Cheng@jcheng67

Install

openclaw skills install scholar-research

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):

FactorWeightDescription
citation_count15%Times cited by other papers
publication_recency10%Newer = more relevant
author_reputation12%Combined h-index of authors
journal_impact12%Impact factor, CiteScore
peer_review_status10%Peer-reviewed vs pre-print
open_access8%Free to read/download
retraction_status10%Not retracted
author_network8%Connected to established network
funder_acknowledgment5%Clear funding sources
reproducibility5%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

  1. Search: Query across all enabled sources
  2. Fetch: Download metadata + PDFs
  3. Score: Calculate credibility scores
  4. Sort: Rank by score + relevance
  5. Present: Top N papers + timeline
  6. 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

Version tags

academicvk973wc8rme6fmbht3tn7cnhszx820f15aivk973wc8rme6fmbht3tn7cnhszx820f15educationvk973wc8rme6fmbht3tn7cnhszx820f15journalsvk973wc8rme6fmbht3tn7cnhszx820f15latestvk973wc8rme6fmbht3tn7cnhszx820f15researchvk973wc8rme6fmbht3tn7cnhszx820f15