---
name: mkurman/citation-management
source: https://app.decimal.ai/s/mkurman-citation-management@1/SKILL.md
source_sha256: 41d2ba93d826
---

--------|-----------|----------------|
| 0-3 years | 20+ | Noteworthy |
| 0-3 years | 100+ | Highly Influential |
| 3-7 years | 100+ | Significant |
| 3-7 years | 500+ | Landmark Paper |
| 7+ years | 500+ | Seminal Work |
| 7+ years | 1000+ | Foundational |

**Venue Quality Tiers:**
- **Tier 1 (Prefer):** Nature, Science, Cell, NEJM, Lancet, JAMA, PNAS
- **Tier 2 (High Priority):** Impact Factor >10, top conferences (NeurIPS, ICML, ICLR)
- **Tier 3 (Good):** Specialized journals (IF 5-10)
- **Tier 4 (Sparingly):** Lower-impact peer-reviewed venues

**Author Reputation Indicators:**
- Senior researchers with h-index >40
- Multiple publications in Tier-1 venues
- Leadership at recognized institutions
- Awards and editorial positions

**Search Strategies for High-Impact Papers:**
- Sort by citation count (most cited first)
- Look for review articles from Tier-1 journals for overview
- Check "Cited by" for impact assessment and recent follow-up work
- Use citation alerts for tracking new citations to key papers
- Filter by top venues using `source:Nature` or `source:Science`
- Search for papers by known field leaders using `author:LastName`

**Advanced Operators** (full list in `references/google_scholar_search.md`):
```
"exact phrase"           # Exact phrase matching
author:lastname          # Search by author
intitle:keyword          # Search in title only
source:journal           # Search specific journal
-exclude                 # Exclude terms
OR                       # Alternative terms
2020..2024              # Year range
```

**Example Searches**:
```
# Find recent reviews on a topic
"CRISPR" intitle:review 2023..2024

# Find papers by specific author on topic
author:Church "synthetic biology"

# Find highly cited foundational work
"deep learning" 2012..2015 sort:citations

# Exclude surveys and focus on methods
"protein folding" -survey -review intitle:method
```

### PubMed Best Practices

**Using MeSH Terms**:
MeSH (Medical Subject Headings) provides controlled vocabulary for precise searching.

1. **Find MeSH terms** at https://meshb.nlm.nih.gov/search
2. **Use in queries**: `"Diabetes Mellitus, Type 2"[MeSH]`
3. **Combine with keywords** for comprehensive coverage

**Field Tags**:
```
[Title]              # Search in title only
[Title/Abstract]     # Search in title or abstract
[Author]             # Search by author name
[Journal]            # Search specific journal
[Publication Date]   # Date range
[Publication Type]   # Article type
[MeSH]              # MeSH term
```

**Building Complex Queries**:
```bash
# Clinical trials on diabetes treatment published recently
"Diabetes Mellitus, Type 2"[MeSH] AND "Drug Therapy"[MeSH] 
AND "Clinical Trial"[Publication Type] AND 2020:2024[Publication Date]

# Reviews on CRISPR in specific journal
"CRISPR-Cas Systems"[MeSH] AND "Nature"[Journal] AND "Review"[Publication Type]

# Specific author's recent work
"Smith AB"[Author] AND cancer[Title/Abstract] AND 2022:2024[Publication Date]
```

**E-utilities for Automation**:
The scripts use NCBI E-utilities API for programmatic access:
- **ESearch**: Search and retrieve PMIDs
- **EFetch**: Retrieve full metadata
- **ESummary**: Get summary information
- **ELink**: Find related articles

See `references/pubmed_search.md` for complete API documentation.

## Tools and Scripts

### search_google_scholar.py

Search Google Scholar and export results.

**Features**:
- Automated searching with rate limiting
- Pagination support
- Year range filtering
- Export to JSON or BibTeX
- Citation count information

**Usage**:
```bash
# Basic search
python scripts/search_google_scholar.py "quantum computing"

# Advanced search with filters
python scripts/search_google_scholar.py "quantum computing" \
  --year-start 2020 \
  --year-end 2024 \
  --limit 100 \
  --sort-by citations \
  --output quantum_papers.json

# Export directly to BibTeX
python scripts/search_google_scholar.py "machine learning" \
  --limit 50 \
  --format bibtex \
  --output ml_papers.bib
```

### search_pubmed.py

Search PubMed using E-utilities API.

**Features**:
- Complex query support (MeSH, field tags, Boolean)
- Date range filtering
- Publication type filtering
- Batch retrieval with metadata
- Export to JSON or BibTeX

**Usage**:
```bash
# Simple keyword search
python scripts/search_pubmed.py "CRISPR gene editing"

# Complex query with filters
python scripts/search_pubmed.py \
  --query '"CRISPR-Cas Systems"[MeSH] AND "therapeutic"[Title/Abstract]' \
  --date-start 2020-01-01 \
  --date-end 2024-12-31 \
  --publication-types "Clinical Trial,Review" \
  --limit 200 \
  --output crispr_therapeutic.json

# Export to BibTeX
python scripts/search_pubmed.py "Alzheimer's disease" \
  --limit 100 \
  --format bibtex \
  --output alzheimers.bib
```

### extract_metadata.py

Extract complete metadata from paper identifiers.

**Features**:
- Supports DOI, PMID, arXiv ID, URL
- Queries CrossRef, PubMed, arXiv APIs
- Handles multiple identifier types
- Batch processing
- Multiple output formats

**Usage**:
```bash
# Single DOI
python scripts/extract_metadata.py --doi 10.1038/s41586-021-03819-2

# Single PMID
python scripts/extract_metadata.py --pmid 34265844

# Single arXiv ID
python scripts/extract_metadata.py --arxiv 2103.14030

# From URL
python scripts/extract_metadata.py \
  --url "https://www.nature.com/articles/s41586-021-03819-2"

# Batch processing (file with one identifier per line)
python scripts/extract_metadata.py \
  --input paper_ids.txt \
  --output references.bib

# Different output formats
python scripts/extract_metadata.py \
  --doi 10.1038/nature12345 \
  --format json  # or bibtex, yaml
```

### validate_citations.py

Validate BibTeX entries for accuracy and completeness.

**Features**:
- DOI verification via doi.org and CrossRef
- Required field checking
- Duplicate detection
- Format validation
- Auto-fix common issues
- Detailed reporting

**Usage**:
```bash
# Basic validation
python scripts/validate_citations.py references.bib

# With auto-fix
python scripts/validate_citations.py references.bib \
  --auto-fix \
  --output fixed_references.bib

# Detailed validation report
python scripts/validate_citations.py references.bib \
  --report validation_report.json \
  --verbose

# Only check DOIs
python scripts/validate_citations.py references.bib \
  --check-dois-only
```

### format_bibtex.py

Format and clean BibTeX files.

**Features**:
- Standardize formatting
- Sort entries (by key, year, author)
- Remove duplicates
- Validate syntax
- Fix common errors
- Enforce citation key conventions

**Usage**:
```bash
# Basic formatting
python scripts/format_bibtex.py references.bib

# Sort by year (newest first)
python scripts/format_bibtex.py references.bib \
  --sort year \
  --descending \
  --output sorted_refs.bib

# Remove duplicates
python scripts/format_bibtex.py references.bib \
  --deduplicate \
  --output clean_refs.bib

# Complete cleanup
python scripts/format_bibtex.py references.bib \
  --deduplicate \
  --sort year \
  --validate \
  --auto-fix \
  --output final_refs.bib
```

### doi_to_bibtex.py

Quick DOI to BibTeX conversion.

**Features**:
- Fast single DOI conversion
- Batch processing
- Multiple output formats
- Clipboard support

**Usage**:
```bash
# Single DOI
python scripts/doi_to_bibtex.py 10.1038/s41586-021-03819-2

# Multiple DOIs
python scripts/doi_to_bibtex.py \
  10.1038/nature12345 \
  10.1126/science.abc1234 \
  10.1016/j.cell.2023.01.001

# From file (one DOI per line)
python scripts/doi_to_bibtex.py --input dois.txt --output references.bib

# Copy to clipboard
python scripts/doi_to_bibtex.py 10.1038/nature12345 --clipboard
```

## Best Practices

### Search Strategy

1. **Start broad, then narrow**:
   - Begin with general terms to understand the field
   - Refine with specific keywords and filters
   - Use synonyms and related terms

2. **Use multiple sources**:
   - Google Scholar for comprehensive coverage
   - PubMed for biomedical focus
   - arXiv for preprints
   - Combine results for completeness

3. **Leverage citations**:
   - Check "Cited by" for seminal papers
   - Review references from key papers
   - Use citation networks to discover related work

4. **Document your searches**:
   - Save search queries and dates
   - Record number of results
   - Note any filters or restrictions applied

### Metadata Extraction

1. **Always use DOIs when available**:
   - Most reliable identifier
   - Permanent link to the publication
   - Best metadata source via CrossRef

2. **Verify extracted metadata**:
   - Check author names are correct
   - Verify journal/conference names
   - Confirm publication year
   - Validate page numbers and volume

3. **Handle edge cases**:
   - Preprints: Include repository and ID
   - Preprints later published: Use published version
   - Conference papers: Include conference name and location
   - Book chapters: Include book title and editors

4. **Maintain consistency**:
   - Use consistent author name format
   - Standardize journal abbreviations
   - Use same DOI format (URL preferred)

### BibTeX Quality

1. **Follow conventions**:
   - Use meaningful citation keys (FirstAuthor2024keyword)
   - Protect capitalization in titles with {}
   - Use -- for page ranges (not single dash)
   - Include DOI field for all modern publications

2. **Keep it clean**:
   - Remove unnecessary fields
   - No redundant information
   - Consistent formatting
   - Validate syntax regularly

3. **Organize systematically**:
   - Sort by year or topic
   - Group related papers
   - Use separate files for different projects
   - Merge carefully to avoid duplicates

### Validation

1. **Validate early and often**:
   - Check citations when adding them
   - Validate complete bibliography before submission
   - Re-validate after any manual edits

2. **Fix issues promptly**:
   - Broken DOIs: Find correct identifier
   - Missing fields: Extract from original source
   - Duplicates: Choose best version, remove others
   - Format errors: Use auto-fix when safe

3. **Manual review for critical citations**:
   - Verify key papers cited correctly
   - Check author names match publication
   - Confirm page numbers and volume
   - Ensure URLs are current

## Common Pitfalls to Avoid

1. **Single source bias**: Only using Google Scholar or PubMed
   - **Solution**: Search multiple databases for comprehensive coverage

2. **Accepting metadata blindly**: Not verifying extracted information
   - **Solution**: Spot-check extracted metadata against original sources

3. **Ignoring DOI errors**: Broken or incorrect DOIs in bibliography
   - **Solution**: Run validation before final submission

4. **Inconsistent formatting**: Mixed citation key styles, formatting
   - **Solution**: Use format_bibtex.py to standardize

5. **Duplicate entries**: Same paper cited multiple times with different keys
   - **Solution**: Use duplicate detection in validation

6. **Missing required fields**: Incomplete BibTeX entries
   - **Solution**: Validate and ensure all required fields present

7. **Outdated preprints**: Citing preprint when published version exists
   - **Solution**: Check if preprints have been published, update to journal version

8. **Special character issues**: Broken LaTeX compilation due to characters
   - **Solution**: Use proper escaping or Unicode in BibTeX

9. **No validation before submission**: Submitting with citation errors
   - **Solution**: Always run validation as final check

10. **Manual BibTeX entry**: Typing entries by hand
    - **Solution**: Always extract from metadata sources using scripts

## Example Workflows

### Example 1: Building a Bibliography for a Paper

```bash
# Step 1: Find key papers on your topic
python scripts/search_google_scholar.py "transformer neural networks" \
  --year-start 2017 \
  --limit 50 \
  --output transformers_gs.json

python scripts/search_pubmed.py "deep learning medical imaging" \
  --date-start 2020 \
  --limit 50 \
  --output medical_dl_pm.json

# Step 2: Extract metadata from search results
python scripts/extract_metadata.py \
  --input transformers_gs.json \
  --output transformers.bib

python scripts/extract_metadata.py \
  --input medical_dl_pm.json \
  --output medical.bib

# Step 3: Add specific papers you already know
python scripts/doi_to_bibtex.py 10.1038/s41586-021-03819-2 >> specific.bib
python scripts/doi_to_bibtex.py 10.1126/science.aam9317 >> specific.bib

# Step 4: Combine all BibTeX files
cat transformers.bib medical.bib specific.bib > combined.bib

# Step 5: Format and deduplicate
python scripts/format_bibtex.py combined.bib \
  --deduplicate \
  --sort year \
  --descending \
  --output formatted.bib

# Step 6: Validate
python scripts/validate_citations.py formatted.bib \
  --auto-fix \
  --report validation.json \
  --output final_references.bib

# Step 7: Review any issues
cat validation.json | grep -A 3 '"errors"'

# Step 8: Use in LaTeX
# \bibliography{final_references}
```

### Example 2: Converting a List of DOIs

```bash
# You have a text file with DOIs (one per line)
# dois.txt contains:
# 10.1038/s41586-021-03819-2
# 10.1126/science.aam9317
# 10.1016/j.cell.2023.01.001

# Convert all to BibTeX
python scripts/doi_to_bibtex.py --input dois.txt --output references.bib

# Validate the result
python scripts/validate_citations.py references.bib --verbose
```

### Example 3: Cleaning an Existing BibTeX File

```bash
# You have a messy BibTeX file from various sources
# Clean it up systematically

# Step 1: Format and standardize
python scripts/format_bibtex.py messy_references.bib \
  --output step1_formatted.bib

# Step 2: Remove duplicates
python scripts/format_bibtex.py step1_formatted.bib \
  --deduplicate \
  --output step2_deduplicated.bib

# Step 3: Validate and auto-fix
python scripts/validate_citations.py step2_deduplicated.bib \
  --auto-fix \
  --output step3_validated.bib

# Step 4: Sort by year
python scripts/format_bibtex.py step3_validated.bib \
  --sort year \
  --descending \
  --output clean_references.bib

# Step 5: Final validation report
python scripts/validate_citations.py clean_references.bib \
  --report final_validation.json \
  --verbose

# Review report
cat final_validation.json
```

### Example 4: Finding and Citing Seminal Papers

```bash
# Find highly cited papers on a topic
python scripts/search_google_scholar.py "AlphaFold protein structure" \
  --year-start 2020 \
  --year-end 2024 \
  --sort-by citations \
  --limit 20 \
  --output alphafold_seminal.json

# Extract the top 10 by citation count
# (script will have included citation counts in JSON)

# Convert to BibTeX
python scripts/extract_metadata.py \
  --input alphafold_seminal.json \
  --output alphafold_refs.bib

# The BibTeX file now contains the most influential papers
```

## Integration with Other Skills

### Literature Review Skill

**Citation Management** provides the technical infrastructure for **Literature Review**:

- **Literature Review**: Multi-database systematic search and synthesis
- **Citation Management**: Metadata extraction and validation

**Combined workflow**:
1. Use literature-review for systematic search methodology
2. Use citation-management to extract and validate citations
3. Use literature-review to synthesize findings
4. Use citation-management to ensure bibliography accuracy

### Scientific Writing Skill

**Citation Management** ensures accurate references for **Scientific Writing**:

- Export validated BibTeX for use in LaTeX manuscripts
- Verify citations match publication standards
- Format references according to journal requirements

### Venue Templates Skill

**Citation Management** works with **Venue Templates** for submission-ready manuscripts:

- Different venues require different citation styles
- Generate properly formatted references
- Validate citations meet venue requirements

## Resources

### Bundled Resources

**References** (in `references/`):
- `google_scholar_search.md`: Complete Google Scholar search guide
- `pubmed_search.md`: PubMed and E-utilities API documentation
- `metadata_extraction.md`: Metadata sources and field requirements
- `citation_validation.md`: Validation criteria and quality checks
- `bibtex_formatting.md`: BibTeX entry types and formatting rules

**Scripts** (in `scripts/`):
- `search_google_scholar.py`: Google Scholar search automation
- `search_pubmed.py`: PubMed E-utilities API client
- `extract_metadata.py`: Universal metadata extractor
- `validate_citations.py`: Citation validation and verification
- `format_bibtex.py`: BibTeX formatter and cleaner
- `doi_to_bibtex.py`: Quick DOI to BibTeX converter

**Assets** (in `assets/`):
- `bibtex_template.bib`: Example BibTeX entries for all types
- `citation_checklist.md`: Quality assurance checklist

### External Resources

**Search Engines**:
- Google Scholar: https://scholar.google.com/
- PubMed: https://pubmed.ncbi.nlm.nih.gov/
- PubMed Advanced Search: https://pubmed.ncbi.nlm.nih.gov/advanced/

**Metadata APIs**:
- CrossRef API: https://api.crossref.org/
- PubMed E-utilities: https://www.ncbi.nlm.nih.gov/books/NBK25501/
- arXiv API: https://arxiv.org/help/api/
- DataCite API: https://api.datacite.org/

**Tools and Validators**:
- MeSH Browser: https://meshb.nlm.nih.gov/search
- DOI Resolver: https://doi.org/
- BibTeX Format: http://www.bibtex.org/Format/

**Citation Styles**:
- BibTeX documentation: http://www.bibtex.org/
- LaTeX bibliography management: https://www.overleaf.com/learn/latex/Bibliography_management

## Dependencies

### Required Python Packages

```bash
# Core dependencies
pip install requests  # HTTP requests for APIs
pip install bibtexparser  # BibTeX parsing and formatting
pip install biopython  # PubMed E-utilities access

# Optional (for Google Scholar)
pip install scholarly  # Google Scholar API wrapper
# or
pip install selenium  # For more robust Scholar scraping
```

### Optional Tools

```bash
# For advanced validation
pip install crossref-commons  # Enhanced CrossRef API access
pip install pylatexenc  # LaTeX special character handling
```

## Summary

The citation-management skill provides:

1. **Comprehensive search capabilities** for Google Scholar and PubMed
2. **Automated metadata extraction** from DOI, PMID, arXiv ID, URLs
3. **Citation validation** with DOI verification and completeness checking
4. **BibTeX formatting** with standardization and cleaning tools
5. **Quality assurance** through validation and reporting
6. **Integration** with scientific writing workflow
7. **Reproducibility** through documented search and extraction methods

Use this skill to maintain accurate, complete citations throughout your research and ensure publication-ready bibliographies.