
Citation Management
- 1k installs
- 32k repo stars
- Updated July 29, 2026
- k-dense-ai/scientific-agent-skills
citation-management is an agent skill that generates and maintains accurate BibTeX citation files and formatted bibliographic references for research-heavy technical documentation.
About
citation-management is a scientific-agent-skills workflow for producing and maintaining BibTeX bibliographies in research-oriented projects. It ships template entries for common source types including journal articles, with fields such as author, title, journal, volume, number, pages, and year demonstrated on references like AlphaFold in Nature. The skill helps agents and developers keep .bib files consistent, properly escaped, and ready for LaTeX or Pandoc pipelines instead of hand-typing references that break builds. Use it when technical docs, ML papers, or agent knowledge bases need durable citation files and formatted reference lists.
- Provides ready-to-use BibTeX templates for journal articles, books, conference papers and other academic source types
- Includes correctly escaped special characters, DOI fields and author name formatting examples
- Supports high-impact scientific references such as AlphaFold, DNA structure and CRISPR-Cas9 papers
- Enables consistent citation management across research notes, papers and agent-generated literature reviews
- Works as both a static template library and a living reference for LLM citation formatting
Citation Management by the numbers
- 1,020 all-time installs (skills.sh)
- +47 installs in the week ending Jul 29, 2026 (Skillselion tracking)
- Ranked #249 of 1,881 Documentation skills by installs in the Skillselion catalog
- Security screen: MEDIUM risk (skills.sh audit)
- Data as of Jul 29, 2026 (Skillselion catalog sync)
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| Installs | 1k |
|---|---|
| repo stars | ★ 32k |
| Security audit | 2 / 3 scanners passed |
| Last updated | July 29, 2026 |
| Repository | k-dense-ai/scientific-agent-skills ↗ |
How do you generate accurate BibTeX citations for papers?
Generate and maintain accurate BibTeX citation files and formatted references for research-heavy AI agents and technical documentation.
Who is it for?
Researchers and technical writers maintaining BibTeX bibliographies for LaTeX papers, ML reports, or scientific agent documentation.
Skip if: Teams using only APA inline citations in Google Docs without BibTeX, LaTeX, or automated bibliography tooling.
When should I use this skill?
A developer needs BibTeX files, bibliography entries, or formatted citations added or corrected in research documentation.
What you get
BibTeX .bib files, formatted bibliographic entries, and citation-ready reference lists
- BibTeX .bib file
- formatted bibliography entries
- citation template library
Files
Citation Management
Overview
Manage citations systematically throughout the research and writing process. This skill provides tools and strategies for searching academic databases (Google Scholar, PubMed), extracting accurate metadata from multiple sources (CrossRef, PubMed, arXiv), validating citation information, and generating properly formatted BibTeX entries.
Critical for maintaining citation accuracy, avoiding reference errors, and ensuring reproducible research. Integrates seamlessly with the literature-review skill for comprehensive research workflows.
When to Use This Skill
Use this skill when:
- Searching for specific papers on Google Scholar or PubMed
- Converting DOIs, PMIDs, or arXiv IDs to properly formatted BibTeX
- Extracting complete metadata for citations (authors, title, journal, year, etc.)
- Validating existing citations for accuracy
- Cleaning and formatting BibTeX files
- Finding highly cited papers in a specific field
- Verifying that citation information matches the actual publication
- Building a bibliography for a manuscript or thesis
- Checking for duplicate citations
- Ensuring consistent citation formatting
Visual Enhancement with Scientific Schematics
When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.
If your document does not already contain schematics or diagrams:
- Use the scientific-schematics skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
- Nano Banana Pro will automatically generate, review, and refine the schematic
For new documents: Scientific schematics should be generated by default to visually represent key concepts, workflows, architectures, or relationships described in the text.
How to generate schematics:
python scripts/generate_schematic.py "your diagram description" -o figures/output.pngThe AI will automatically:
- Create publication-quality images with proper formatting
- Review and refine through multiple iterations
- Ensure accessibility (colorblind-friendly, high contrast)
- Save outputs in the figures/ directory
When to add schematics:
- Citation workflow diagrams
- Literature search methodology flowcharts
- Reference management system architectures
- Citation style decision trees
- Database integration diagrams
- Any complex concept that benefits from visualization
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
---
Core Workflow
Citation management follows a systematic process:
Phase 1: Paper Discovery and Search
Goal: Find relevant papers using academic search engines.
Google Scholar Search
Google Scholar provides the most comprehensive coverage across disciplines.
Basic Search:
# Search for papers on a topic
python scripts/search_google_scholar.py "CRISPR gene editing" \
--limit 50 \
--output results.json
# Search with year filter
python scripts/search_google_scholar.py "machine learning protein folding" \
--year-start 2020 \
--year-end 2024 \
--limit 100 \
--output ml_proteins.jsonAdvanced Search Strategies (see references/google_scholar_search.md):
- Use quotation marks for exact phrases:
"deep learning" - Search by author:
author:LeCun - Search in title:
intitle:"neural networks" - Exclude terms:
machine learning -survey - Find highly cited papers using sort options
- Filter by date ranges to get recent work
Best Practices:
- Use specific, targeted search terms
- Include key technical terms and acronyms
- Filter by recent years for fast-moving fields
- Check "Cited by" to find seminal papers
- Export top results for further analysis
PubMed Search
PubMed specializes in biomedical and life sciences literature (35+ million citations).
Basic Search:
# Search PubMed
python scripts/search_pubmed.py "Alzheimer's disease treatment" \
--limit 100 \
--output alzheimers.json
# Search with MeSH terms and filters
python scripts/search_pubmed.py \
--query '"Alzheimer Disease"[MeSH] AND "Drug Therapy"[MeSH]' \
--date-start 2020 \
--date-end 2024 \
--publication-types "Clinical Trial,Review" \
--output alzheimers_trials.jsonAdvanced PubMed Queries (see references/pubmed_search.md):
- Use MeSH terms:
"Diabetes Mellitus"[MeSH] - Field tags:
"cancer"[Title],"Smith J"[Author] - Boolean operators:
AND,OR,NOT - Date filters:
2020:2024[Publication Date] - Publication types:
"Review"[Publication Type] - Combine with E-utilities API for automation
Best Practices:
- Use MeSH Browser to find correct controlled vocabulary
- Construct complex queries in PubMed Advanced Search Builder first
- Include multiple synonyms with OR
- Retrieve PMIDs for easy metadata extraction
- Export to JSON or directly to BibTeX
Phase 2: Metadata Extraction
Goal: Convert paper identifiers (DOI, PMID, arXiv ID) to complete, accurate metadata.
Quick DOI to BibTeX Conversion
For single DOIs, use the quick conversion tool:
# Convert single DOI
python scripts/doi_to_bibtex.py 10.1038/s41586-021-03819-2
# Convert multiple DOIs from a file
python scripts/doi_to_bibtex.py --input dois.txt --output references.bib
# Different output formats
python scripts/doi_to_bibtex.py 10.1038/nature12345 --format jsonComprehensive Metadata Extraction
For DOIs, PMIDs, arXiv IDs, or URLs:
# Extract from DOI
python scripts/extract_metadata.py --doi 10.1038/s41586-021-03819-2
# Extract from PMID
python scripts/extract_metadata.py --pmid 34265844
# Extract from arXiv ID
python scripts/extract_metadata.py --arxiv 2103.14030
# Extract from URL
python scripts/extract_metadata.py --url "https://www.nature.com/articles/s41586-021-03819-2"
# Batch extraction from file (mixed identifiers)
python scripts/extract_metadata.py --input identifiers.txt --output citations.bibMetadata Sources (see references/metadata_extraction.md):
1. CrossRef API: Primary source for DOIs
- Comprehensive metadata for journal articles
- Publisher-provided information
- Includes authors, title, journal, volume, pages, dates
- Free, no API key required
2. PubMed E-utilities: Biomedical literature
- Official NCBI metadata
- Includes MeSH terms, abstracts
- PMID and PMCID identifiers
- Free, API key recommended for high volume
3. arXiv API: Preprints in physics, math, CS, q-bio
- Complete metadata for preprints
- Version tracking
- Author affiliations
- Free, open access
4. DataCite API: Research datasets, software, other resources
- Metadata for non-traditional scholarly outputs
- DOIs for datasets and code
- Free access
What Gets Extracted:
- Required fields: author, title, year
- Journal articles: journal, volume, number, pages, DOI
- Books: publisher, ISBN, edition
- Conference papers: booktitle, conference location, pages
- Preprints: repository (arXiv, bioRxiv), preprint ID
- Additional: abstract, keywords, URL
Phase 2.5: Metadata Enrichment via Web Search (MANDATORY)
Goal: Detect and fill in any missing metadata fields using web search. This phase runs AFTER extraction and BEFORE formatting to ensure every BibTeX entry is complete.
Why This Is Critical: Metadata extraction from APIs (CrossRef, PubMed, arXiv) sometimes returns incomplete records — missing volume, pages, issue number, or DOI. These gaps must be filled before the bibliography is considered ready.
Step 1: Scan for Incomplete Entries
After extracting metadata, scan the BibTeX file for entries missing key fields:
Fields to check per entry type:
| Entry Type | Must Have | Should Have |
|---|---|---|
| @article | author, title, journal, year | volume, pages, number, doi |
| @inproceedings | author, title, booktitle, year | pages, doi |
| @book | author/editor, title, publisher, year | isbn, doi |
| @misc | author, title, year | doi or url |
Any @article entry missing volume, pages, or doi is considered incomplete and must be enriched.
Step 2: Web Search for Missing Metadata
For each incomplete entry, use the parallel-web skill to search for the missing information:
Option A — Search by title and author (best for finding DOI):
parallel-cli search "FIRST_AUTHOR TITLE JOURNAL_NAME volume pages DOI" \
--json --max-results 10 \
-o sources/search_citation_CITATIONKEY.jsonOption B — Extract from DOI page (best when DOI is known but volume/pages missing):
parallel-cli extract "https://doi.org/10.XXXX/YYYY" --json \
--objective "extract complete citation metadata: volume, issue, pages, publication date" \
-o sources/extract_doi_CITATIONKEY.jsonOption C — Search CrossRef API directly (programmatic, fast):
parallel-cli search "crossref DOI metadata FIRST_AUTHOR TITLE" \
--json --max-results 10 \
-o sources/search_crossref_CITATIONKEY.jsonOption D — Search Google Scholar (fallback for hard-to-find papers):
parallel-cli search "google scholar FIRST_AUTHOR TITLE YEAR complete citation" \
--json --max-results 10 \
-o sources/search_scholar_CITATIONKEY.jsonStep 3: Update BibTeX Entries
After finding the missing metadata:
1. Open references.bib 2. Add the missing fields to the incomplete entry 3. Verify the found metadata is consistent with existing fields (same author, title, year) 4. Log each fix:
[HH:MM:SS] METADATA ENRICHED: [CitationKey] - added volume={X}, pages={Y--Z}, doi={10.XXX/YYY} ✅Step 4: Handle Unfindable Metadata
If metadata genuinely cannot be found after web search (very old paper, obscure conference, etc.):
1. Add a note field to the BibTeX entry explaining the gap:
note = {Volume and pages not available — published online only}2. Log the exception:
[HH:MM:SS] METADATA INCOMPLETE: [CitationKey] - pages unavailable (online-only publication) ⚠️3. These exceptions should be rare — most modern papers have complete metadata findable via web search.
Quick Reference: Common Missing Fields and Where to Find Them
| Missing Field | Best Search Strategy |
|---|---|
| DOI | Search "AUTHOR TITLE DOI" via parallel-cli search |
| Volume | Extract from DOI page or search "JOURNAL YEAR TITLE volume" |
| Pages | Extract from DOI page or search publisher website |
| Issue/Number | Extract from DOI page or CrossRef |
| Publisher | Search "JOURNAL publisher" or check journal website |
---
Phase 3: BibTeX Formatting
Goal: Generate clean, properly formatted BibTeX entries.
Understanding BibTeX Entry Types
See references/bibtex_formatting.md for complete guide.
Common Entry Types:
@article: Journal articles (most common)@book: Books@inproceedings: Conference papers@incollection: Book chapters@phdthesis: Dissertations@misc: Preprints, software, datasets
Required Fields by Type:
@article{citationkey,
author = {Last1, First1 and Last2, First2},
title = {Article Title},
journal = {Journal Name},
year = {2024},
volume = {10},
number = {3},
pages = {123--145},
doi = {10.1234/example}
}
@inproceedings{citationkey,
author = {Last, First},
title = {Paper Title},
booktitle = {Conference Name},
year = {2024},
pages = {1--10}
}
@book{citationkey,
author = {Last, First},
title = {Book Title},
publisher = {Publisher Name},
year = {2024}
}Formatting and Cleaning
Use the formatter to standardize BibTeX files:
# Format and clean BibTeX file
python scripts/format_bibtex.py references.bib \
--output formatted_references.bib
# Sort entries by citation key
python scripts/format_bibtex.py references.bib \
--sort key \
--output sorted_references.bib
# Sort by year (newest first)
python scripts/format_bibtex.py references.bib \
--sort year \
--descending \
--output sorted_references.bib
# Remove duplicates
python scripts/format_bibtex.py references.bib \
--deduplicate \
--output clean_references.bib
# Validate and report issues
python scripts/format_bibtex.py references.bib \
--validate \
--report validation_report.txtFormatting Operations:
- Standardize field order
- Consistent indentation and spacing
- Proper capitalization in titles (protected with {})
- Standardized author name format
- Consistent citation key format
- Remove unnecessary fields
- Fix common errors (missing commas, braces)
Phase 4: Citation Validation
Goal: Verify all citations are accurate and complete.
Comprehensive Validation
# Validate BibTeX file
python scripts/validate_citations.py references.bib
# Validate against a venue standard (e.g., Nature, NeurIPS, Literature Review)
python scripts/validate_citations.py references.bib --venue nature
python scripts/validate_citations.py references.bib --venue neurips
python scripts/validate_citations.py references.bib --venue review
# Validate with custom minimum citation count
python scripts/validate_citations.py references.bib --min-count 40
# Check references against a written manuscript file (detect missing or unused citations)
python scripts/validate_citations.py references.bib --manuscript paper.md
# Generate detailed validation report
python scripts/validate_citations.py references.bib \
--venue nature \
--manuscript paper.md \
--report validation_report.json \
--verboseValidation Checks (see references/citation_validation.md):
1. DOI Verification:
- DOI resolves correctly via doi.org
- Metadata matches between BibTeX and CrossRef
- No broken or invalid DOIs
2. Required Fields:
- All required fields present for entry type
- No empty or missing critical information
- Author names properly formatted
3. Data Consistency:
- Year is valid (4 digits, reasonable range)
- Volume/number are numeric
- Pages formatted correctly (e.g., 123--145)
- URLs are accessible
4. Duplicate Detection:
- Same DOI used multiple times
- Similar titles (possible duplicates)
- Same author/year/title combinations
5. Format Compliance:
- Valid BibTeX syntax
- Proper bracing and quoting
- Citation keys are unique
- Special characters handled correctly
Validation Output:
{
"total_entries": 150,
"valid_entries": 145,
"errors": [
{
"citation_key": "Smith2023",
"error_type": "missing_field",
"field": "journal",
"severity": "high"
},
{
"citation_key": "Jones2022",
"error_type": "invalid_doi",
"doi": "10.1234/broken",
"severity": "high"
}
],
"warnings": [
{
"citation_key": "Brown2021",
"warning_type": "possible_duplicate",
"duplicate_of": "Brown2021a",
"severity": "medium"
}
]
}Citation Count Standards by Venue
Citations must always be high in number based on standards for journal and conference publications in the venue of choice or recommendation. Never settle for a sparse reference list; establish an authoritative, rich context with dense, verified citations.
| Venue Type | Target Citation Count |
|---|---|
| High-impact multidisciplinary journals (Nature, Science, Cell) | 35-50+ |
| ML / CS conferences (NeurIPS, ICML, ICLR, CVPR, ACL) | 30-45+ |
| Comprehensive literature reviews / market research reports | 40-65+ |
| Medical journals (NEJM, Lancet, JAMA) | 30-45+ |
Always adjust the citation target upward depending on standard density and practices of the target venue. Avoid 'lazy' citation over-repetition — do not repeatedly cite the same 1 or 2 papers to support multiple unrelated claims; draw from a diverse, high-quality set of reputable references.
Enforce these standards programmatically with validate_citations.py --venue <venue> or --min-count <N>.
Mandatory Post-Writing Reference Checks (Non-Negotiable)
Once the entire scientific report or paper has been drafted and written, perform a comprehensive post-writing verification of all citations before compiling the final deliverables:
1. Verify No Missing or Unresolved Citations: Check the draft or compiled document to ensure that every in-text citation correctly resolves to a reference in references.bib. There must be ZERO broken citation keys, missing identifiers, or unresolved references (e.g., [?] or [citation needed]). 2. Verify No Unused (Dangling) Bibliography Entries: Check that every entry in references.bib is actually cited in the body of the report. Remove any unused entries to keep the bibliography perfectly clean. 3. Verify Citation Quantity Against Target Standards: Ensure the final citation count meets or exceeds the high standard of the chosen or recommended venue (see table above). If the count is below standard, perform additional literature search first, find high-quality papers, and integrate them into appropriate sections. 4. Verify Metadata Completeness: Confirm that all cited entries contain complete, fully-verified fields (all author names, complete journal/conference names, exact year, volume, issue, page range, and valid DOI).
Run all of these checks in one command:
python scripts/validate_citations.py references.bib \
--venue <venue> \
--manuscript paper.md \
--report post_writing_check.jsonPhase 5: Integration with Writing Workflow
Building References for Manuscripts
Complete workflow for creating a bibliography:
# 1. Search for papers on your topic
python scripts/search_pubmed.py \
'"CRISPR-Cas Systems"[MeSH] AND "Gene Editing"[MeSH]' \
--date-start 2020 \
--limit 200 \
--output crispr_papers.json
# 2. Extract DOIs from search results and convert to BibTeX
python scripts/extract_metadata.py \
--input crispr_papers.json \
--output crispr_refs.bib
# 3. Add specific papers by DOI
python scripts/doi_to_bibtex.py 10.1038/nature12345 >> crispr_refs.bib
python scripts/doi_to_bibtex.py 10.1126/science.abcd1234 >> crispr_refs.bib
# 4. Format and clean the BibTeX file
python scripts/format_bibtex.py crispr_refs.bib \
--deduplicate \
--sort year \
--descending \
--output references.bib
# 5. Validate all citations
python scripts/validate_citations.py references.bib \
--auto-fix \
--report validation.json \
--output final_references.bib
# 6. Review validation report and fix any remaining issues
cat validation.json
# 7. Use in your LaTeX document
# \bibliography{final_references}Integration with Literature Review Skill
This skill complements the literature-review skill:
Literature Review Skill → Systematic search and synthesis Citation Management Skill → Technical citation handling
Combined Workflow: 1. Use literature-review for comprehensive multi-database search 2. Use citation-management to extract and validate all citations 3. Use literature-review to synthesize findings thematically 4. Use citation-management to verify final bibliography accuracy
# After completing literature review
# Verify all citations in the review document
python scripts/validate_citations.py my_review_references.bib --report review_validation.json
# Format for specific citation style if needed
python scripts/format_bibtex.py my_review_references.bib \
--style nature \
--output formatted_refs.bibSearch Strategies
Google Scholar Best Practices
Finding Seminal and High-Impact Papers (CRITICAL):
Always prioritize papers based on citation count, venue quality, and author reputation:
Citation Count Thresholds:
| Paper Age | Citations | Classification |
|---|---|---|
| 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:Natureorsource: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 rangeExample 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:methodPubMed 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 termBuilding Complex Queries:
# 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:
# 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.bibsearch_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:
# 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.bibextract_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:
# 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, yamlvalidate_citations.py
Validate BibTeX entries for accuracy, completeness, citation count standard compliance, and manuscript integration.
Features:
- DOI verification via doi.org and CrossRef
- Required field checking
- Duplicate detection
- Format validation
- Publication standard citation count checks against specified venues (Nature, NeurIPS, review, etc.) or custom thresholds.
- Mandatory post-writing checks matching manuscript citations (Markdown or LaTeX) with defined BibTeX entries to detect unresolved/missing or unused references.
- Detailed reporting
Usage:
# Basic validation
python scripts/validate_citations.py references.bib
# Validate against a venue standard (e.g., Nature, NeurIPS, Literature Review)
python scripts/validate_citations.py references.bib --venue nature
python scripts/validate_citations.py references.bib --venue neurips
python scripts/validate_citations.py references.bib --venue review
# Validate with custom minimum citation count
python scripts/validate_citations.py references.bib --min-count 40
# Check references against a written manuscript file (detect missing or unused citations)
python scripts/validate_citations.py references.bib --manuscript paper.md
# Combined full validation
python scripts/validate_citations.py references.bib \
--venue nature \
--manuscript paper.md \
--report validation_report.json \
--verboseformat_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:
# 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.bibdoi_to_bibtex.py
Quick DOI to BibTeX conversion.
Features:
- Fast single DOI conversion
- Batch processing
- Multiple output formats
- Clipboard support
Usage:
# 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 --clipboardBest 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 (volume, pages, DOI missing)
- Solution: Run Phase 2.5 metadata enrichment — web search for every missing field before proceeding. NEVER leave an @article entry without volume, pages, and DOI.
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
# 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
# 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 --verboseExample 3: Cleaning an Existing BibTeX File
# 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.jsonExample 4: Finding and Citing Seminal Papers
# 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 papersIntegration 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 guidepubmed_search.md: PubMed and E-utilities API documentationmetadata_extraction.md: Metadata sources and field requirementscitation_validation.md: Validation criteria and quality checksbibtex_formatting.md: BibTeX entry types and formatting rules
Scripts (in scripts/):
search_google_scholar.py: Google Scholar search automationsearch_pubmed.py: PubMed E-utilities API clientextract_metadata.py: Universal metadata extractorvalidate_citations.py: Citation validation and verificationformat_bibtex.py: BibTeX formatter and cleanerdoi_to_bibtex.py: Quick DOI to BibTeX converter
Assets (in assets/):
bibtex_template.bib: Example BibTeX entries for all typescitation_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
# 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 scrapingOptional Tools
# For advanced validation
pip install crossref-commons # Enhanced CrossRef API access
pip install pylatexenc # LaTeX special character handlingSummary
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.
% BibTeX Template File
% Examples of properly formatted entries for all common types
% =============================================================================
% JOURNAL ARTICLES
% =============================================================================
@article{Jumper2021,
author = {Jumper, John and Evans, Richard and Pritzel, Alexander and Green, Tim and Figurnov, Michael and Ronneberger, Olaf and Tunyasuvunakool, Kathryn and Bates, Russ and {\v{Z}}{\'\i}dek, Augustin and Potapenko, Anna and others},
title = {Highly Accurate Protein Structure Prediction with {AlphaFold}},
journal = {Nature},
year = {2021},
volume = {596},
number = {7873},
pages = {583--589},
doi = {10.1038/s41586-021-03819-2}
}
@article{Watson1953,
author = {Watson, James D. and Crick, Francis H. C.},
title = {Molecular Structure of Nucleic Acids: A Structure for Deoxyribose Nucleic Acid},
journal = {Nature},
year = {1953},
volume = {171},
number = {4356},
pages = {737--738},
doi = {10.1038/171737a0}
}
@article{Doudna2014,
author = {Doudna, Jennifer A. and Charpentier, Emmanuelle},
title = {The New Frontier of Genome Engineering with {CRISPR-Cas9}},
journal = {Science},
year = {2014},
volume = {346},
number = {6213},
pages = {1258096},
doi = {10.1126/science.1258096}
}
% =============================================================================
% BOOKS
% =============================================================================
@book{Kumar2021,
author = {Kumar, Vinay and Abbas, Abul K. and Aster, Jon C.},
title = {Robbins and Cotran Pathologic Basis of Disease},
publisher = {Elsevier},
year = {2021},
edition = {10},
address = {Philadelphia, PA},
isbn = {978-0-323-53113-9}
}
@book{Alberts2014,
author = {Alberts, Bruce and Johnson, Alexander and Lewis, Julian and Morgan, David and Raff, Martin and Roberts, Keith and Walter, Peter},
title = {Molecular Biology of the Cell},
publisher = {Garland Science},
year = {2014},
edition = {6},
address = {New York, NY},
isbn = {978-0-815-34432-2}
}
% Book with editor instead of author
@book{Sambrook2001,
editor = {Sambrook, Joseph and Russell, David W.},
title = {Molecular Cloning: A Laboratory Manual},
publisher = {Cold Spring Harbor Laboratory Press},
year = {2001},
edition = {3},
address = {Cold Spring Harbor, NY},
isbn = {978-0-879-69576-7}
}
% =============================================================================
% CONFERENCE PAPERS (PROCEEDINGS)
% =============================================================================
@inproceedings{Vaswani2017,
author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N. and Kaiser, {\L}ukasz and Polosukhin, Illia},
title = {Attention is All You Need},
booktitle = {Advances in Neural Information Processing Systems 30 (NeurIPS 2017)},
year = {2017},
pages = {5998--6008},
address = {Long Beach, CA},
url = {https://proceedings.neurips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html}
}
@inproceedings{He2016,
author = {He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
title = {Deep Residual Learning for Image Recognition},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2016},
pages = {770--778},
address = {Las Vegas, NV},
doi = {10.1109/CVPR.2016.90}
}
% =============================================================================
% BOOK CHAPTERS
% =============================================================================
@incollection{Brown2020,
author = {Brown, Peter O. and Botstein, David},
title = {Exploring the New World of the Genome with {DNA} Microarrays},
booktitle = {DNA Microarrays: A Molecular Cloning Manual},
editor = {Eisen, Michael B. and Brown, Patrick O.},
publisher = {Cold Spring Harbor Laboratory Press},
year = {2020},
pages = {1--45},
address = {Cold Spring Harbor, NY}
}
% =============================================================================
% PHD THESES / DISSERTATIONS
% =============================================================================
@phdthesis{Johnson2023,
author = {Johnson, Mary L.},
title = {Novel Approaches to Cancer Immunotherapy Using {CRISPR} Technology},
school = {Stanford University},
year = {2023},
type = {{PhD} dissertation},
address = {Stanford, CA}
}
% =============================================================================
% MASTER'S THESES
% =============================================================================
@mastersthesis{Smith2022,
author = {Smith, Robert J.},
title = {Machine Learning Methods for Protein Structure Prediction},
school = {Massachusetts Institute of Technology},
year = {2022},
type = {{Master's} thesis},
address = {Cambridge, MA}
}
% =============================================================================
% TECHNICAL REPORTS
% =============================================================================
@techreport{WHO2020,
author = {{World Health Organization}},
title = {Clinical Management of {COVID-19}: Interim Guidance},
institution = {World Health Organization},
year = {2020},
type = {Technical Report},
number = {WHO/2019-nCoV/clinical/2020.5},
address = {Geneva, Switzerland}
}
% =============================================================================
% PREPRINTS
% =============================================================================
% bioRxiv preprint
@misc{Zhang2024preprint,
author = {Zhang, Yi and Chen, Li and Wang, Hui and Liu, Xin},
title = {Novel Therapeutic Targets in {Alzheimer}'s Disease},
year = {2024},
howpublished = {bioRxiv},
doi = {10.1101/2024.01.15.575432},
note = {Preprint}
}
% arXiv preprint
@misc{Brown2024arxiv,
author = {Brown, Alice and Green, Bob},
title = {Advances in Quantum Computing},
year = {2024},
howpublished = {arXiv},
note = {arXiv:2401.12345}
}
% =============================================================================
% DATASETS
% =============================================================================
@misc{AlphaFoldDB2021,
author = {{DeepMind} and {EMBL-EBI}},
title = {{AlphaFold} Protein Structure Database},
year = {2021},
howpublished = {Database},
url = {https://alphafold.ebi.ac.uk/},
doi = {10.1093/nar/gkab1061},
note = {Version 4}
}
% =============================================================================
% SOFTWARE / CODE
% =============================================================================
@misc{McKinney2010pandas,
author = {McKinney, Wes},
title = {pandas: A Foundational {Python} Library for Data Analysis and Statistics},
year = {2010},
howpublished = {Software},
url = {https://pandas.pydata.org/},
note = {Python Data Analysis Library}
}
% =============================================================================
% WEBSITES / ONLINE RESOURCES
% =============================================================================
@misc{NCBI2024,
author = {{National Center for Biotechnology Information}},
title = {{PubMed}: Database of Biomedical Literature},
year = {2024},
howpublished = {Website},
url = {https://pubmed.ncbi.nlm.nih.gov/},
note = {Accessed: 2024-01-15}
}
% =============================================================================
% SPECIAL CASES
% =============================================================================
% Article with organization as author
@article{NatureEditorial2023,
author = {{Nature Editorial Board}},
title = {The Future of {AI} in Scientific Research},
journal = {Nature},
year = {2023},
volume = {615},
pages = {1--2},
doi = {10.1038/d41586-023-00001-1}
}
% Article with no volume number (some journals)
@article{OpenAccess2024,
author = {Williams, Sarah and Thomas, Michael},
title = {Open Access Publishing in the 21st Century},
journal = {Journal of Scholarly Communication},
year = {2024},
pages = {e123456},
doi = {10.1234/jsc.2024.123456}
}
% Conference paper with DOI
@inproceedings{Garcia2023,
author = {Garc{\'i}a-Mart{\'i}nez, Jos{\'e} and M{\"u}ller, Hans},
title = {International Collaboration in Science},
booktitle = {Proceedings of the International Conference on Academic Publishing},
year = {2023},
pages = {45--52},
doi = {10.1109/ICAP.2023.123456}
}
% Article with PMID but no DOI (older papers)
@article{OldPaper1995,
author = {Anderson, Philip W.},
title = {Through the Glass Lightly},
journal = {Science},
year = {1995},
volume = {267},
number = {5204},
pages = {1615--1616},
note = {PMID: 17808148}
}
Citation Quality Checklist
Use this checklist to ensure your citations are accurate, complete, and properly formatted before final submission.
Pre-Submission Checklist
✓ Metadata Accuracy
- [ ] All author names are correct and properly formatted
- [ ] Article titles match the actual publication
- [ ] Journal/conference names are complete (not abbreviated unless required)
- [ ] Publication years are accurate
- [ ] Volume and issue numbers are correct
- [ ] Page ranges are accurate
✓ Required Fields
- [ ] All @article entries have: author, title, journal, year
- [ ] All @book entries have: author/editor, title, publisher, year
- [ ] All @inproceedings entries have: author, title, booktitle, year
- [ ] Modern papers (2000+) include DOI when available
- [ ] All entries have unique citation keys
✓ DOI Verification
- [ ] All DOIs are properly formatted (10.XXXX/...)
- [ ] DOIs resolve correctly to the article
- [ ] No DOI prefix in the BibTeX field (no "doi:" or "https://doi.org/")
- [ ] Metadata from CrossRef matches your BibTeX entry
- [ ] Run:
python scripts/validate_citations.py references.bib --check-dois
✓ Formatting Consistency
- [ ] Page ranges use double hyphen (--) not single (-)
- [ ] No "pp." prefix in pages field
- [ ] Author names use "and" separator (not semicolon or ampersand)
- [ ] Capitalization protected in titles ({AlphaFold}, {CRISPR}, etc.)
- [ ] Month names use standard abbreviations if included
- [ ] Citation keys follow consistent format
✓ Duplicate Detection
- [ ] No duplicate DOIs in bibliography
- [ ] No duplicate citation keys
- [ ] No near-duplicate titles
- [ ] Preprints updated to published versions when available
- [ ] Run:
python scripts/validate_citations.py references.bib
✓ Special Characters
- [ ] Accented characters properly formatted (e.g., {\"u} for ü)
- [ ] Mathematical symbols use LaTeX commands
- [ ] Chemical formulas properly formatted
- [ ] No unescaped special characters (%, &, $, #, etc.)
✓ BibTeX Syntax
- [ ] All entries have balanced braces {}
- [ ] Fields separated by commas
- [ ] No comma after last field in each entry
- [ ] Valid entry types (@article, @book, etc.)
- [ ] Run:
python scripts/validate_citations.py references.bib
✓ File Organization
- [ ] Bibliography sorted in logical order (by year, author, or key)
- [ ] Consistent formatting throughout
- [ ] No formatting inconsistencies between entries
- [ ] Run:
python scripts/format_bibtex.py references.bib --sort year
Automated Validation
Step 1: Format and Clean
python scripts/format_bibtex.py references.bib \
--deduplicate \
--sort year \
--descending \
--output clean_references.bibWhat this does:
- Removes duplicates
- Standardizes formatting
- Fixes common issues (page ranges, DOI format, etc.)
- Sorts by year (newest first)
Step 2: Validate
python scripts/validate_citations.py clean_references.bib \
--check-dois \
--report validation_report.json \
--verboseWhat this does:
- Checks required fields
- Verifies DOIs resolve
- Detects duplicates
- Validates syntax
- Generates detailed report
Step 3: Review Report
cat validation_report.jsonAddress any:
- Errors: Must fix (missing fields, broken DOIs, syntax errors)
- Warnings: Should fix (missing recommended fields, formatting issues)
- Duplicates: Remove or consolidate
Step 4: Final Check
python scripts/validate_citations.py clean_references.bib --verboseGoal: Zero errors, minimal warnings
Manual Review Checklist
Critical Citations (Top 10-20 Most Important)
For your most important citations, manually verify:
- [ ] Visit DOI link and confirm it's the correct article
- [ ] Check author names against the actual publication
- [ ] Verify year matches publication date
- [ ] Confirm journal/conference name is correct
- [ ] Check that volume/pages match
Common Issues to Watch For
Missing Information:
- [ ] No DOI for papers published after 2000
- [ ] Missing volume or page numbers for journal articles
- [ ] Missing publisher for books
- [ ] Missing conference location for proceedings
Formatting Errors:
- [ ] Single hyphen in page ranges (123-145 → 123--145)
- [ ] Ampersands in author lists (Smith & Jones → Smith and Jones)
- [ ] Unprotected acronyms in titles (DNA → {DNA})
- [ ] DOI includes URL prefix (https://doi.org/10.xxx → 10.xxx)
Metadata Mismatches:
- [ ] Author names differ from publication
- [ ] Year is online-first instead of print publication
- [ ] Journal name abbreviated when it should be full
- [ ] Volume/issue numbers swapped
Duplicates:
- [ ] Same paper cited with different citation keys
- [ ] Preprint and published version both cited
- [ ] Conference paper and journal version both cited
Field-Specific Checks
Biomedical Sciences
- [ ] PubMed Central ID (PMCID) included when available
- [ ] MeSH terms appropriate (if using)
- [ ] Clinical trial registration number included (if applicable)
- [ ] All references to treatments/drugs accurately cited
Computer Science
- [ ] arXiv ID included for preprints
- [ ] Conference proceedings properly cited (not just "NeurIPS")
- [ ] Software/dataset citations include version numbers
- [ ] GitHub links stable and permanent
General Sciences
- [ ] Data availability statements properly cited
- [ ] Retracted papers identified and removed
- [ ] Preprints checked for published versions
- [ ] Supplementary materials referenced if critical
Final Pre-Submission Steps
1 Week Before Submission
- [ ] Run full validation with DOI checking
- [ ] Fix all errors and critical warnings
- [ ] Manually verify top 10-20 most important citations
- [ ] Check for any retracted papers
3 Days Before Submission
- [ ] Re-run validation after any manual edits
- [ ] Ensure all in-text citations have corresponding bibliography entries
- [ ] Ensure all bibliography entries are cited in text
- [ ] Check citation style matches journal requirements
1 Day Before Submission
- [ ] Final validation check
- [ ] LaTeX compilation successful with no warnings
- [ ] PDF renders all citations correctly
- [ ] Bibliography appears in correct format
- [ ] No placeholder citations (Smith et al. XXXX)
Submission Day
- [ ] One final validation run
- [ ] No last-minute edits without re-validation
- [ ] Bibliography file included in submission package
- [ ] Figures/tables referenced in text match bibliography
Quality Metrics
Excellent Bibliography
- ✓ 100% of entries have DOIs (for modern papers)
- ✓ Zero validation errors
- ✓ Zero missing required fields
- ✓ Zero broken DOIs
- ✓ Zero duplicates
- ✓ Consistent formatting throughout
- ✓ All citations manually spot-checked
Acceptable Bibliography
- ✓ 90%+ of modern entries have DOIs
- ✓ Zero high-severity errors
- ✓ Minor warnings only (e.g., missing recommended fields)
- ✓ Key citations manually verified
- ✓ Compilation succeeds without errors
Needs Improvement
- ✗ Missing DOIs for recent papers
- ✗ High-severity validation errors
- ✗ Broken or incorrect DOIs
- ✗ Duplicate entries
- ✗ Inconsistent formatting
- ✗ Compilation warnings or errors
Emergency Fixes
If you discover issues at the last minute:
Broken DOI
# Find correct DOI
# Option 1: Search CrossRef
# https://www.crossref.org/
# Option 2: Search on publisher website
# Option 3: Google Scholar
# Re-extract metadata
python scripts/extract_metadata.py --doi CORRECT_DOIMissing Information
# Extract from DOI
python scripts/extract_metadata.py --doi 10.xxxx/yyyy
# Or from PMID (biomedical)
python scripts/extract_metadata.py --pmid 12345678
# Or from arXiv
python scripts/extract_metadata.py --arxiv 2103.12345Duplicate Entries
# Auto-remove duplicates
python scripts/format_bibtex.py references.bib \
--deduplicate \
--output fixed_references.bibFormatting Errors
# Auto-fix common issues
python scripts/format_bibtex.py references.bib \
--output fixed_references.bib
# Then validate
python scripts/validate_citations.py fixed_references.bibLong-Term Best Practices
During Research
- [ ] Add citations to bibliography file as you find them
- [ ] Extract metadata immediately using DOI
- [ ] Validate after every 10-20 additions
- [ ] Keep bibliography file under version control
During Writing
- [ ] Cite as you write
- [ ] Use consistent citation keys
- [ ] Don't delay adding references
- [ ] Validate weekly
Before Submission
- [ ] Allow 2-3 days for citation cleanup
- [ ] Don't wait until the last day
- [ ] Automate what you can
- [ ] Manually verify critical citations
Tool Quick Reference
Extract Metadata
# From DOI
python scripts/doi_to_bibtex.py 10.1038/nature12345
# From multiple sources
python scripts/extract_metadata.py \
--doi 10.1038/nature12345 \
--pmid 12345678 \
--arxiv 2103.12345 \
--output references.bibValidate
# Basic validation
python scripts/validate_citations.py references.bib
# With DOI checking (slow but thorough)
python scripts/validate_citations.py references.bib --check-dois
# Generate report
python scripts/validate_citations.py references.bib \
--report validation.json \
--verboseFormat and Clean
# Format and fix issues
python scripts/format_bibtex.py references.bib
# Remove duplicates and sort
python scripts/format_bibtex.py references.bib \
--deduplicate \
--sort year \
--descending \
--output clean_refs.bibSummary
Minimum Requirements: 1. Run format_bibtex.py --deduplicate 2. Run validate_citations.py 3. Fix all errors 4. Compile successfully
Recommended: 1. Format, deduplicate, and sort 2. Validate with --check-dois 3. Fix all errors and warnings 4. Manually verify top citations 5. Re-validate after fixes
Best Practice: 1. Validate throughout research process 2. Use automated tools consistently 3. Keep bibliography clean and organized 4. Document any special cases 5. Final validation 1-3 days before submission
Remember: Citation errors reflect poorly on your scholarship. Taking time to ensure accuracy is worthwhile!
BibTeX Formatting Guide
Comprehensive guide to BibTeX entry types, required fields, formatting conventions, and best practices.
Overview
BibTeX is the standard bibliography format for LaTeX documents. Proper formatting ensures:
- Correct citation rendering
- Consistent formatting
- Compatibility with citation styles
- No compilation errors
This guide covers all common entry types and formatting rules.
Entry Types
@article - Journal Articles
Most common entry type for peer-reviewed journal articles.
Required fields:
author: Author namestitle: Article titlejournal: Journal nameyear: Publication year
Optional fields:
volume: Volume numbernumber: Issue numberpages: Page rangemonth: Publication monthdoi: Digital Object Identifierurl: URLnote: Additional notes
Template:
@article{CitationKey2024,
author = {Last1, First1 and Last2, First2},
title = {Article Title Here},
journal = {Journal Name},
year = {2024},
volume = {10},
number = {3},
pages = {123--145},
doi = {10.1234/journal.2024.123456},
month = jan
}Example:
@article{Jumper2021,
author = {Jumper, John and Evans, Richard and Pritzel, Alexander and others},
title = {Highly Accurate Protein Structure Prediction with {AlphaFold}},
journal = {Nature},
year = {2021},
volume = {596},
number = {7873},
pages = {583--589},
doi = {10.1038/s41586-021-03819-2}
}@book - Books
For entire books.
Required fields:
authorOReditor: Author(s) or editor(s)title: Book titlepublisher: Publisher nameyear: Publication year
Optional fields:
volume: Volume number (if multi-volume)series: Series nameaddress: Publisher locationedition: Edition numberisbn: ISBNurl: URL
Template:
@book{CitationKey2024,
author = {Last, First},
title = {Book Title},
publisher = {Publisher Name},
year = {2024},
edition = {3},
address = {City, Country},
isbn = {978-0-123-45678-9}
}Example:
@book{Kumar2021,
author = {Kumar, Vinay and Abbas, Abul K. and Aster, Jon C.},
title = {Robbins and Cotran Pathologic Basis of Disease},
publisher = {Elsevier},
year = {2021},
edition = {10},
address = {Philadelphia, PA},
isbn = {978-0-323-53113-9}
}@inproceedings - Conference Papers
For papers in conference proceedings.
Required fields:
author: Author namestitle: Paper titlebooktitle: Conference/proceedings nameyear: Year
Optional fields:
editor: Proceedings editor(s)volume: Volume numberseries: Series namepages: Page rangeaddress: Conference locationmonth: Conference monthorganization: Organizing bodypublisher: Publisherdoi: DOI
Template:
@inproceedings{CitationKey2024,
author = {Last, First},
title = {Paper Title},
booktitle = {Proceedings of Conference Name},
year = {2024},
pages = {123--145},
address = {City, Country},
month = jun
}Example:
@inproceedings{Vaswani2017,
author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and others},
title = {Attention is All You Need},
booktitle = {Advances in Neural Information Processing Systems 30 (NeurIPS 2017)},
year = {2017},
pages = {5998--6008},
address = {Long Beach, CA}
}Note: @conference is an alias for @inproceedings.
@incollection - Book Chapters
For chapters in edited books.
Required fields:
author: Chapter author(s)title: Chapter titlebooktitle: Book titlepublisher: Publisher nameyear: Publication year
Optional fields:
editor: Book editor(s)volume: Volume numberseries: Series nametype: Type of section (e.g., "chapter")chapter: Chapter numberpages: Page rangeaddress: Publisher locationedition: Editionmonth: Month
Template:
@incollection{CitationKey2024,
author = {Last, First},
title = {Chapter Title},
booktitle = {Book Title},
editor = {Editor, Last and Editor2, Last},
publisher = {Publisher Name},
year = {2024},
pages = {123--145},
chapter = {5}
}Example:
@incollection{Brown2020,
author = {Brown, Peter O. and Botstein, David},
title = {Exploring the New World of the Genome with {DNA} Microarrays},
booktitle = {DNA Microarrays: A Molecular Cloning Manual},
editor = {Eisen, Michael B. and Brown, Patrick O.},
publisher = {Cold Spring Harbor Laboratory Press},
year = {2020},
pages = {1--45},
address = {Cold Spring Harbor, NY}
}@phdthesis - Doctoral Dissertations
For PhD dissertations and theses.
Required fields:
author: Author nametitle: Thesis titleschool: Institutionyear: Year
Optional fields:
type: Type (e.g., "PhD dissertation", "PhD thesis")address: Institution locationmonth: Monthurl: URLnote: Additional notes
Template:
@phdthesis{CitationKey2024,
author = {Last, First},
title = {Dissertation Title},
school = {University Name},
year = {2024},
type = {{PhD} dissertation},
address = {City, State}
}Example:
@phdthesis{Johnson2023,
author = {Johnson, Mary L.},
title = {Novel Approaches to Cancer Immunotherapy Using {CRISPR} Technology},
school = {Stanford University},
year = {2023},
type = {{PhD} dissertation},
address = {Stanford, CA}
}Note: @mastersthesis is similar but for Master's theses.
@mastersthesis - Master's Theses
For Master's theses.
Required fields:
author: Author nametitle: Thesis titleschool: Institutionyear: Year
Template:
@mastersthesis{CitationKey2024,
author = {Last, First},
title = {Thesis Title},
school = {University Name},
year = {2024}
}@misc - Miscellaneous
For items that don't fit other categories (preprints, datasets, software, websites, etc.).
Required fields:
author(if known)titleyear
Optional fields:
howpublished: Repository, website, formaturl: URLdoi: DOInote: Additional informationmonth: Month
Template for preprints:
@misc{CitationKey2024,
author = {Last, First},
title = {Preprint Title},
year = {2024},
howpublished = {bioRxiv},
doi = {10.1101/2024.01.01.123456},
note = {Preprint}
}Template for datasets:
@misc{DatasetName2024,
author = {Last, First},
title = {Dataset Title},
year = {2024},
howpublished = {Zenodo},
doi = {10.5281/zenodo.123456},
note = {Version 1.2}
}Template for software:
@misc{SoftwareName2024,
author = {Last, First},
title = {Software Name},
year = {2024},
howpublished = {GitHub},
url = {https://github.com/user/repo},
note = {Version 2.0}
}@techreport - Technical Reports
For technical reports.
Required fields:
author: Author name(s)title: Report titleinstitution: Institutionyear: Year
Optional fields:
type: Type of reportnumber: Report numberaddress: Institution locationmonth: Month
Template:
@techreport{CitationKey2024,
author = {Last, First},
title = {Report Title},
institution = {Institution Name},
year = {2024},
type = {Technical Report},
number = {TR-2024-01}
}@unpublished - Unpublished Work
For unpublished works (not preprints - use @misc for those).
Required fields:
author: Author name(s)title: Work titlenote: Description
Optional fields:
month: Monthyear: Year
Template:
@unpublished{CitationKey2024,
author = {Last, First},
title = {Work Title},
note = {Unpublished manuscript},
year = {2024}
}@online/@electronic - Online Resources
For web pages and online-only content.
Note: Not standard BibTeX, but supported by many bibliography packages (biblatex).
Required fields:
authorORorganizationtitleurlyear
Template:
@online{CitationKey2024,
author = {{Organization Name}},
title = {Page Title},
url = {https://example.com/page},
year = {2024},
note = {Accessed: 2024-01-15}
}Formatting Rules
Citation Keys
Convention: FirstAuthorYEARkeyword
Examples:
Smith2024protein
Doe2023machine
JohnsonWilliams2024cancer % Multiple authors, no space
NatureEditorial2024 % No author, use publication
WHO2024guidelines % Organization authorRules:
- Alphanumeric plus:
-,_,.,: - No spaces
- Case-sensitive
- Unique within file
- Descriptive
Avoid:
- Special characters:
@,#,&,%,$ - Spaces: use CamelCase or underscores
- Starting with numbers:
2024Smith(some systems disallow)
Author Names
Recommended format: Last, First Middle
Single author:
author = {Smith, John}
author = {Smith, John A.}
author = {Smith, John Andrew}Multiple authors - separate with and:
author = {Smith, John and Doe, Jane}
author = {Smith, John A. and Doe, Jane M. and Johnson, Mary L.}Many authors (10+):
author = {Smith, John and Doe, Jane and Johnson, Mary and others}Special cases:
% Suffix (Jr., III, etc.)
author = {King, Jr., Martin Luther}
% Organization as author
author = {{World Health Organization}}
% Note: Double braces keep as single entity
% Multiple surnames
author = {Garc{\'i}a-Mart{\'i}nez, Jos{\'e}}
% Particles (van, von, de, etc.)
author = {van der Waals, Johannes}
author = {de Broglie, Louis}Wrong formats (don't use):
author = {Smith, J.; Doe, J.} % Semicolons (wrong)
author = {Smith, J., Doe, J.} % Commas (wrong)
author = {Smith, J. & Doe, J.} % Ampersand (wrong)
author = {Smith J} % No commaTitle Capitalization
Protect capitalization with braces:
% Proper nouns, acronyms, formulas
title = {{AlphaFold}: Protein Structure Prediction}
title = {Machine Learning for {DNA} Sequencing}
title = {The {Ising} Model in Statistical Physics}
title = {{CRISPR-Cas9} Gene Editing Technology}Reason: Citation styles may change capitalization. Braces protect.
Examples:
% Good
title = {Advances in {COVID-19} Treatment}
title = {Using {Python} for Data Analysis}
title = {The {AlphaFold} Protein Structure Database}
% Will be lowercase in title case styles
title = {Advances in COVID-19 Treatment} % covid-19
title = {Using Python for Data Analysis} % pythonWhole title protection (rarely needed):
title = {{This Entire Title Keeps Its Capitalization}}Page Ranges
Use en-dash (double hyphen --):
pages = {123--145} % Correct
pages = {1234--1256} % Correct
pages = {e0123456} % Article ID (PLOS, etc.)
pages = {123} % Single pageWrong:
pages = {123-145} % Single hyphen (don't use)
pages = {pp. 123-145} % "pp." not needed
pages = {123–145} % Unicode en-dash (may cause issues)Month Names
Use three-letter abbreviations (unquoted):
month = jan
month = feb
month = mar
month = apr
month = may
month = jun
month = jul
month = aug
month = sep
month = oct
month = nov
month = decOr numeric:
month = {1} % January
month = {12} % DecemberOr full name in braces:
month = {January}Standard abbreviations work without quotes because they're defined in BibTeX.
Journal Names
Full name (not abbreviated):
journal = {Nature}
journal = {Science}
journal = {Cell}
journal = {Proceedings of the National Academy of Sciences}
journal = {Journal of the American Chemical Society}Bibliography style will handle abbreviation if needed.
Avoid manual abbreviation:
% Don't do this in BibTeX file
journal = {Proc. Natl. Acad. Sci. U.S.A.}
% Do this instead
journal = {Proceedings of the National Academy of Sciences}Exception: If style requires abbreviations, use full abbreviated form:
journal = {Proc. Natl. Acad. Sci. U.S.A.} % If required by styleDOI Formatting
URL format (preferred):
doi = {10.1038/s41586-021-03819-2}Not:
doi = {https://doi.org/10.1038/s41586-021-03819-2} % Don't include URL
doi = {doi:10.1038/s41586-021-03819-2} % Don't include prefixLaTeX will format as URL automatically.
Note: No period after DOI field!
URL Formatting
url = {https://www.example.com/article}Use:
- When DOI not available
- For web pages
- For supplementary materials
Don't duplicate:
% Don't include both if DOI URL is same as url
doi = {10.1038/nature12345}
url = {https://doi.org/10.1038/nature12345} % Redundant!Special Characters
Accents and diacritics:
author = {M{\"u}ller, Hans} % ü
author = {Garc{\'i}a, Jos{\'e}} % í, é
author = {Erd{\H{o}}s, Paul} % ő
author = {Schr{\"o}dinger, Erwin} % öOr use UTF-8 (with proper LaTeX setup):
author = {Müller, Hans}
author = {García, José}Mathematical symbols:
title = {The $\alpha$-helix Structure}
title = {$\beta$-sheet Prediction}Chemical formulas:
title = {H$_2$O Molecular Dynamics}
% Or with chemformula package:
title = {\ce{H2O} Molecular Dynamics}Field Order
Recommended order (for readability):
@article{Key,
author = {},
title = {},
journal = {},
year = {},
volume = {},
number = {},
pages = {},
doi = {},
url = {},
note = {}
}Rules:
- Most important fields first
- Consistent across entries
- Use formatter to standardize
Best Practices
1. Consistent Formatting
Use same format throughout:
- Author name format
- Title capitalization
- Journal names
- Citation key style
2. Required Fields
Always include:
- All required fields for entry type
- DOI for modern papers (2000+)
- Volume and pages for articles
- Publisher for books
3. Protect Capitalization
Use braces for:
- Proper nouns:
{AlphaFold} - Acronyms:
{DNA},{CRISPR} - Formulas:
{H2O} - Names:
{Python},{R}
4. Complete Author Lists
Include all authors when possible:
- All authors if <10
- Use "and others" for 10+
- Don't abbreviate to "et al." manually
5. Use Standard Entry Types
Choose correct entry type:
- Journal article →
@article - Book →
@book - Conference paper →
@inproceedings - Preprint →
@misc
6. Validate Syntax
Check for:
- Balanced braces
- Commas after fields
- Unique citation keys
- Valid entry types
7. Use Formatters
Use automated tools:
python scripts/format_bibtex.py references.bibBenefits:
- Consistent formatting
- Catch syntax errors
- Standardize field order
- Fix common issues
Common Mistakes
1. Wrong Author Separator
Wrong:
author = {Smith, J.; Doe, J.} % Semicolon
author = {Smith, J., Doe, J.} % Comma
author = {Smith, J. & Doe, J.} % AmpersandCorrect:
author = {Smith, John and Doe, Jane}2. Missing Commas
Wrong:
@article{Smith2024,
author = {Smith, John} % Missing comma!
title = {Title}
}Correct:
@article{Smith2024,
author = {Smith, John}, % Comma after each field
title = {Title}
}3. Unprotected Capitalization
Wrong:
title = {Machine Learning with Python}
% "Python" will become "python" in title caseCorrect:
title = {Machine Learning with {Python}}4. Single Hyphen in Pages
Wrong:
pages = {123-145} % Single hyphenCorrect:
pages = {123--145} % Double hyphen (en-dash)5. Redundant "pp." in Pages
Wrong:
pages = {pp. 123--145}Correct:
pages = {123--145}6. DOI with URL Prefix
Wrong:
doi = {https://doi.org/10.1038/nature12345}
doi = {doi:10.1038/nature12345}Correct:
doi = {10.1038/nature12345}Example Complete Bibliography
% Journal article
@article{Jumper2021,
author = {Jumper, John and Evans, Richard and Pritzel, Alexander and others},
title = {Highly Accurate Protein Structure Prediction with {AlphaFold}},
journal = {Nature},
year = {2021},
volume = {596},
number = {7873},
pages = {583--589},
doi = {10.1038/s41586-021-03819-2}
}
% Book
@book{Kumar2021,
author = {Kumar, Vinay and Abbas, Abul K. and Aster, Jon C.},
title = {Robbins and Cotran Pathologic Basis of Disease},
publisher = {Elsevier},
year = {2021},
edition = {10},
address = {Philadelphia, PA},
isbn = {978-0-323-53113-9}
}
% Conference paper
@inproceedings{Vaswani2017,
author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and others},
title = {Attention is All You Need},
booktitle = {Advances in Neural Information Processing Systems 30 (NeurIPS 2017)},
year = {2017},
pages = {5998--6008}
}
% Book chapter
@incollection{Brown2020,
author = {Brown, Peter O. and Botstein, David},
title = {Exploring the New World of the Genome with {DNA} Microarrays},
booktitle = {DNA Microarrays: A Molecular Cloning Manual},
editor = {Eisen, Michael B. and Brown, Patrick O.},
publisher = {Cold Spring Harbor Laboratory Press},
year = {2020},
pages = {1--45}
}
% PhD thesis
@phdthesis{Johnson2023,
author = {Johnson, Mary L.},
title = {Novel Approaches to Cancer Immunotherapy},
school = {Stanford University},
year = {2023},
type = {{PhD} dissertation}
}
% Preprint
@misc{Zhang2024,
author = {Zhang, Yi and Chen, Li and Wang, Hui},
title = {Novel Therapeutic Targets in {Alzheimer}'s Disease},
year = {2024},
howpublished = {bioRxiv},
doi = {10.1101/2024.01.001},
note = {Preprint}
}
% Dataset
@misc{AlphaFoldDB2021,
author = {{DeepMind} and {EMBL-EBI}},
title = {{AlphaFold} Protein Structure Database},
year = {2021},
howpublished = {Database},
url = {https://alphafold.ebi.ac.uk/},
doi = {10.1093/nar/gkab1061}
}Summary
BibTeX formatting essentials:
✓ Choose correct entry type (@article, @book, etc.) ✓ Include all required fields ✓ Use `and` for multiple authors ✓ Protect capitalization with braces ✓ Use `--` for page ranges ✓ Include DOI for modern papers ✓ Validate syntax before compilation
Use formatting tools to ensure consistency:
python scripts/format_bibtex.py references.bibProperly formatted BibTeX ensures correct, consistent citations across all bibliography styles!
Citation Validation Guide
Comprehensive guide to validating citation accuracy, completeness, and formatting in BibTeX files.
Overview
Citation validation ensures:
- All citations are accurate and complete
- DOIs resolve correctly
- Required fields are present
- No duplicate entries
- Proper formatting and syntax
- Links are accessible
Validation should be performed:
- After extracting metadata
- Before manuscript submission
- After manual edits to BibTeX files
- Periodically for maintained bibliographies
Validation Categories
1. DOI Verification
Purpose: Ensure DOIs are valid and resolve correctly.
What to Check
DOI format:
Valid: 10.1038/s41586-021-03819-2
Valid: 10.1126/science.aam9317
Invalid: 10.1038/invalid
Invalid: doi:10.1038/... (should omit "doi:" prefix in BibTeX)DOI resolution:
- DOI should resolve via https://doi.org/
- Should redirect to actual article
- Should not return 404 or error
Metadata consistency:
- CrossRef metadata should match BibTeX
- Author names should align
- Title should match
- Year should match
How to Validate
Manual check: 1. Copy DOI from BibTeX 2. Visit https://doi.org/10.1038/nature12345 3. Verify it redirects to correct article 4. Check metadata matches
Automated check (recommended):
python scripts/validate_citations.py references.bib --check-doisProcess: 1. Extract all DOIs from BibTeX file 2. Query doi.org resolver for each 3. Query CrossRef API for metadata 4. Compare metadata with BibTeX entry 5. Report discrepancies
Common Issues
Broken DOIs:
- Typos in DOI
- Publisher changed DOI (rare)
- Article retracted
- Solution: Find correct DOI from publisher site
Mismatched metadata:
- BibTeX has old/incorrect information
- Solution: Re-extract metadata from CrossRef
Missing DOIs:
- Older articles may not have DOIs
- Acceptable for pre-2000 publications
- Add URL or PMID instead
2. Required Fields
Purpose: Ensure all necessary information is present.
Required by Entry Type
@article:
author % REQUIRED
title % REQUIRED
journal % REQUIRED
year % REQUIRED
volume % Highly recommended
pages % Highly recommended
doi % Highly recommended for modern papers@book:
author OR editor % REQUIRED (at least one)
title % REQUIRED
publisher % REQUIRED
year % REQUIRED
isbn % Recommended@inproceedings:
author % REQUIRED
title % REQUIRED
booktitle % REQUIRED (conference/proceedings name)
year % REQUIRED
pages % Recommended@incollection (book chapter):
author % REQUIRED
title % REQUIRED (chapter title)
booktitle % REQUIRED (book title)
publisher % REQUIRED
year % REQUIRED
editor % Recommended
pages % Recommended@phdthesis:
author % REQUIRED
title % REQUIRED
school % REQUIRED
year % REQUIRED@misc (preprints, datasets, etc.):
author % REQUIRED
title % REQUIRED
year % REQUIRED
howpublished % Recommended (bioRxiv, Zenodo, etc.)
doi OR url % At least one requiredValidation Script
python scripts/validate_citations.py references.bib --check-required-fieldsOutput:
Error: Entry 'Smith2024' missing required field 'journal'
Error: Entry 'Doe2023' missing required field 'year'
Warning: Entry 'Jones2022' missing recommended field 'volume'3. Author Name Formatting
Purpose: Ensure consistent, correct author name formatting.
Proper Format
Recommended BibTeX format:
author = {Last1, First1 and Last2, First2 and Last3, First3}Examples:
% Correct
author = {Smith, John}
author = {Smith, John A.}
author = {Smith, John Andrew}
author = {Smith, John and Doe, Jane}
author = {Smith, John and Doe, Jane and Johnson, Mary}
% For many authors
author = {Smith, John and Doe, Jane and others}
% Incorrect
author = {John Smith} % First Last format (not recommended)
author = {Smith, J.; Doe, J.} % Semicolon separator (wrong)
author = {Smith J, Doe J} % Missing commasSpecial Cases
Suffixes (Jr., III, etc.):
author = {King, Jr., Martin Luther}Multiple surnames (hyphenated):
author = {Smith-Jones, Mary}Van, von, de, etc.:
author = {van der Waals, Johannes}
author = {de Broglie, Louis}Organizations as authors:
author = {{World Health Organization}}
% Double braces treat as single authorValidation Checks
Automated validation:
python scripts/validate_citations.py references.bib --check-authorsChecks for:
- Proper separator (and, not &, ; , etc.)
- Comma placement
- Empty author fields
- Malformed names
4. Data Consistency
Purpose: Ensure all fields contain valid, reasonable values.
Year Validation
Valid years:
year = {2024} % Current/recent
year = {1953} % Watson & Crick DNA structure (historical)
year = {1665} % Hooke's Micrographia (very old)Invalid years:
year = {24} % Two digits (ambiguous)
year = {202} % Typo
year = {2025} % Future (unless accepted/in press)
year = {0} % Obviously wrongCheck:
- Four digits
- Reasonable range (1600-current+1)
- Not all zeros
Volume/Number Validation
volume = {123} % Numeric
volume = {12} % Valid
number = {3} % Valid
number = {S1} % Supplement issue (valid)Invalid:
volume = {Vol. 123} % Should be just number
number = {Issue 3} % Should be just numberPage Range Validation
Correct format:
pages = {123--145} % En-dash (two hyphens)
pages = {e0123456} % PLOS-style article ID
pages = {123} % Single pageIncorrect format:
pages = {123-145} % Single hyphen (use --)
pages = {pp. 123-145} % Remove "pp."
pages = {123–145} % Unicode en-dash (may cause issues)URL Validation
Check:
- URLs are accessible (return 200 status)
- HTTPS when available
- No obvious typos
- Permanent links (not temporary)
Valid:
url = {https://www.nature.com/articles/nature12345}
url = {https://arxiv.org/abs/2103.14030}Questionable:
url = {http://...} % HTTP instead of HTTPS
url = {file:///...} % Local file path
url = {bit.ly/...} % URL shortener (not permanent)5. Duplicate Detection
Purpose: Find and remove duplicate entries.
Types of Duplicates
Exact duplicates (same DOI):
@article{Smith2024a,
doi = {10.1038/nature12345},
...
}
@article{Smith2024b,
doi = {10.1038/nature12345}, % Same DOI!
...
}Near duplicates (similar title/authors):
@article{Smith2024,
title = {Machine Learning for Drug Discovery},
...
}
@article{Smith2024method,
title = {Machine learning for drug discovery}, % Same, different case
...
}Preprint + Published:
@misc{Smith2023arxiv,
title = {AlphaFold Results},
howpublished = {arXiv},
...
}
@article{Smith2024,
title = {AlphaFold Results}, % Same paper, now published
journal = {Nature},
...
}
% Keep published version onlyDetection Methods
By DOI (most reliable):
- Same DOI = exact duplicate
- Keep one, remove other
By title similarity:
- Normalize: lowercase, remove punctuation
- Calculate similarity (e.g., Levenshtein distance)
- Flag if >90% similar
By author-year-title:
- Same first author + year + similar title
- Likely duplicate
Automated detection:
python scripts/validate_citations.py references.bib --check-duplicatesOutput:
Warning: Possible duplicate entries:
- Smith2024a (DOI: 10.1038/nature12345)
- Smith2024b (DOI: 10.1038/nature12345)
Recommendation: Keep one entry, remove the other.6. Format and Syntax
Purpose: Ensure valid BibTeX syntax.
Common Syntax Errors
Missing commas:
@article{Smith2024,
author = {Smith, John} % Missing comma!
title = {Title}
}
% Should be:
author = {Smith, John}, % Comma after each fieldUnbalanced braces:
title = {Title with {Protected} Text % Missing closing brace
% Should be:
title = {Title with {Protected} Text}Missing closing brace for entry:
@article{Smith2024,
author = {Smith, John},
title = {Title}
% Missing closing brace!
% Should end with:
}Invalid characters in keys:
@article{Smith&Doe2024, % & not allowed in key
...
}
% Use:
@article{SmithDoe2024,
...
}BibTeX Syntax Rules
Entry structure:
@TYPE{citationkey,
field1 = {value1},
field2 = {value2},
...
fieldN = {valueN}
}Citation keys:
- Alphanumeric and some punctuation (-, _, ., :)
- No spaces
- Case-sensitive
- Unique within file
Field values:
- Enclosed in {braces} or "quotes"
- Braces preferred for complex text
- Numbers can be unquoted:
year = 2024
Special characters:
{and}for grouping\for LaTeX commands- Protect capitalization:
{AlphaFold} - Accents:
{\"u},{\'e},{\aa}
Validation
python scripts/validate_citations.py references.bib --check-syntaxChecks:
- Valid BibTeX structure
- Balanced braces
- Proper commas
- Valid entry types
- Unique citation keys
Validation Workflow
Step 1: Basic Validation
Run comprehensive validation:
python scripts/validate_citations.py references.bibChecks all:
- DOI resolution
- Required fields
- Author formatting
- Data consistency
- Duplicates
- Syntax
Step 2: Review Report
Examine validation report:
{
"total_entries": 150,
"valid_entries": 140,
"errors": [
{
"entry": "Smith2024",
"error": "missing_required_field",
"field": "journal",
"severity": "high"
},
{
"entry": "Doe2023",
"error": "invalid_doi",
"doi": "10.1038/broken",
"severity": "high"
}
],
"warnings": [
{
"entry": "Jones2022",
"warning": "missing_recommended_field",
"field": "volume",
"severity": "medium"
}
],
"duplicates": [
{
"entries": ["Smith2024a", "Smith2024b"],
"reason": "same_doi",
"doi": "10.1038/nature12345"
}
]
}Step 3: Fix Issues
High-priority (errors): 1. Add missing required fields 2. Fix broken DOIs 3. Remove duplicates 4. Correct syntax errors
Medium-priority (warnings): 1. Add recommended fields 2. Improve author formatting 3. Fix page ranges
Low-priority: 1. Standardize formatting 2. Add URLs for accessibility
Step 4: Auto-Fix
Use auto-fix for safe corrections:
python scripts/validate_citations.py references.bib \
--auto-fix \
--output fixed_references.bibAuto-fix can:
- Fix page range format (- to --)
- Remove "pp." from pages
- Standardize author separators
- Fix common syntax errors
- Normalize field order
Auto-fix cannot:
- Add missing information
- Find correct DOIs
- Determine which duplicate to keep
- Fix semantic errors
Step 5: Manual Review
Review auto-fixed file:
# Check what changed
diff references.bib fixed_references.bib
# Review specific entries that had errors
grep -A 10 "Smith2024" fixed_references.bibStep 6: Re-Validate
Validate after fixes:
python scripts/validate_citations.py fixed_references.bib --verboseShould show:
✓ All DOIs valid
✓ All required fields present
✓ No duplicates found
✓ Syntax valid
✓ 150/150 entries validValidation Checklist
Use this checklist before final submission:
DOI Validation
- [ ] All DOIs resolve correctly
- [ ] Metadata matches between BibTeX and CrossRef
- [ ] No broken or invalid DOIs
Completeness
- [ ] All entries have required fields
- [ ] Modern papers (2000+) have DOIs
- [ ] Authors properly formatted
- [ ] Journals/conferences properly named
Consistency
- [ ] Years are 4-digit numbers
- [ ] Page ranges use -- not -
- [ ] Volume/number are numeric
- [ ] URLs are accessible
Duplicates
- [ ] No entries with same DOI
- [ ] No near-duplicate titles
- [ ] Preprints updated to published versions
Formatting
- [ ] Valid BibTeX syntax
- [ ] Balanced braces
- [ ] Proper commas
- [ ] Unique citation keys
Final Checks
- [ ] Bibliography compiles without errors
- [ ] All citations in text appear in bibliography
- [ ] All bibliography entries cited in text
- [ ] Citation style matches journal requirements
Best Practices
1. Validate Early and Often
# After extraction
python scripts/extract_metadata.py --doi ... --output refs.bib
python scripts/validate_citations.py refs.bib
# After manual edits
python scripts/validate_citations.py refs.bib
# Before submission
python scripts/validate_citations.py refs.bib --strict2. Use Automated Tools
Don't validate manually - use scripts:
- Faster
- More comprehensive
- Catches errors humans miss
- Generates reports
3. Keep Backup
# Before auto-fix
cp references.bib references_backup.bib
# Run auto-fix
python scripts/validate_citations.py references.bib \
--auto-fix \
--output references_fixed.bib
# Review changes
diff references.bib references_fixed.bib
# If satisfied, replace
mv references_fixed.bib references.bib4. Fix High-Priority First
Priority order: 1. Syntax errors (prevent compilation) 2. Missing required fields (incomplete citations) 3. Broken DOIs (broken links) 4. Duplicates (confusion, wasted space) 5. Missing recommended fields 6. Formatting inconsistencies
5. Document Exceptions
For entries that can't be fixed:
@article{Old1950,
author = {Smith, John},
title = {Title},
journal = {Obscure Journal},
year = {1950},
volume = {12},
pages = {34--56},
note = {DOI not available for publications before 2000}
}6. Validate Against Journal Requirements
Different journals have different requirements:
- Citation style (numbered, author-year)
- Abbreviations (journal names)
- Maximum reference count
- Format (BibTeX, EndNote, manual)
Check journal author guidelines!
Common Validation Issues
Issue 1: Metadata Mismatch
Problem: BibTeX says 2023, CrossRef says 2024.
Cause:
- Online-first vs print publication
- Correction/update
- Extraction error
Solution: 1. Check actual article 2. Use more recent/accurate date 3. Update BibTeX entry 4. Re-validate
Issue 2: Special Characters
Problem: LaTeX compilation fails on special characters.
Cause:
- Accented characters (é, ü, ñ)
- Chemical formulas (H₂O)
- Math symbols (α, β, ±)
Solution:
% Use LaTeX commands
author = {M{\"u}ller, Hans} % Müller
title = {Study of H\textsubscript{2}O} % H₂O
% Or use UTF-8 with proper LaTeX packagesIssue 3: Incomplete Extraction (REQUIRES WEB SEARCH)
Problem: Extracted metadata missing fields (volume, pages, DOI, issue number).
Cause:
- Source API doesn't provide all metadata
- Extraction error
- Incomplete database record
- Online-first publication without final pagination
Solution — MANDATORY web search to fill gaps:
1. Identify the missing fields by scanning the BibTeX entry for empty or absent volume, pages, number, doi fields.
2. Search for the missing metadata using web search (parallel-web skill):
# Search by author + title to find complete citation info
parallel-cli search "AUTHOR_NAME PAPER_TITLE JOURNAL volume pages DOI" \
--json --max-results 10 \
-o sources/search_citation_CITATIONKEY.json3. If DOI is known, extract from DOI resolver page:
parallel-cli extract "https://doi.org/DOI_HERE" --json \
--objective "extract volume, issue number, page range, publication date" \
-o sources/extract_doi_CITATIONKEY.json4. If DOI is unknown, search for it:
parallel-cli search "AUTHOR_NAME PAPER_TITLE JOURNAL_NAME DOI" \
--json --max-results 10 \
-o sources/search_find_doi_CITATIONKEY.json5. Try alternative metadata sources:
- CrossRef API (via DOI): Most reliable for volume/pages
- PubMed (via PMID): Good for biomedical papers
- Google Scholar: Fallback for hard-to-find papers
- Publisher website: Last resort
6. Update the BibTeX entry with the found metadata and log:
[HH:MM:SS] METADATA ENRICHED: [CitationKey] - added volume, pages, doi ✅7. If truly unfindable (rare), add a note field:
note = {Complete pagination not yet assigned — online-first publication}CRITICAL: Never leave an @article entry without volume, pages, and doi unless you have exhausted all search options and documented the reason.
Issue 4: Cannot Find Duplicate
Problem: Same paper appears twice, not detected.
Cause:
- Different DOIs (should be rare)
- Different titles (abbreviated, typo)
- Different citation keys
Solution:
- Manual search for author + year
- Check for similar titles
- Remove manually
Summary
Validation ensures citation quality:
✓ Accuracy: DOIs resolve, metadata correct ✓ Completeness: All required fields present ✓ Consistency: Proper formatting throughout ✓ No duplicates: Each paper cited once ✓ Valid syntax: BibTeX compiles without errors
Always validate before final submission!
Use automated tools:
python scripts/validate_citations.py references.bibFollow workflow: 1. Extract metadata 2. Validate 3. Fix errors 4. Re-validate 5. Submit
Google Scholar Search Guide
Comprehensive guide to searching Google Scholar for academic papers, including advanced search operators, filtering strategies, and metadata extraction.
Overview
Google Scholar provides the most comprehensive coverage of academic literature across all disciplines:
- Coverage: 100+ million scholarly documents
- Scope: All academic disciplines
- Content types: Journal articles, books, theses, conference papers, preprints, patents, court opinions
- Citation tracking: "Cited by" links for forward citation tracking
- Accessibility: Free to use, no account required
Basic Search
Simple Keyword Search
Search for papers containing specific terms anywhere in the document (title, abstract, full text):
CRISPR gene editing
machine learning protein folding
climate change impact agriculture
quantum computing algorithmsTips:
- Use specific technical terms
- Include key acronyms and abbreviations
- Start broad, then refine
- Check spelling of technical terms
Exact Phrase Search
Use quotation marks to search for exact phrases:
"deep learning"
"CRISPR-Cas9"
"systematic review"
"randomized controlled trial"When to use:
- Technical terms that must appear together
- Proper names
- Specific methodologies
- Exact titles
Advanced Search Operators
Author Search
Find papers by specific authors:
author:LeCun
author:"Geoffrey Hinton"
author:Church synthetic biologyVariations:
- Single last name:
author:Smith - Full name in quotes:
author:"Jane Smith" - Author + topic:
author:Doudna CRISPR
Tips:
- Authors may publish under different name variations
- Try with and without middle initials
- Consider name changes (marriage, etc.)
- Use quotation marks for full names
Title Search
Search only in article titles:
intitle:transformer
intitle:"attention mechanism"
intitle:review climate changeUse cases:
- Finding papers specifically about a topic
- More precise than full-text search
- Reduces irrelevant results
- Good for finding reviews or methods
Source (Journal) Search
Search within specific journals or conferences:
source:Nature
source:"Nature Communications"
source:NeurIPS
source:"Journal of Machine Learning Research"Applications:
- Track publications in top-tier venues
- Find papers in specialized journals
- Identify conference-specific work
- Verify publication venue
Exclusion Operator
Exclude terms from results:
machine learning -survey
CRISPR -patent
climate change -news
deep learning -tutorial -reviewCommon exclusions:
-survey: Exclude survey papers-review: Exclude review articles-patent: Exclude patents-book: Exclude books-news: Exclude news articles-tutorial: Exclude tutorials
OR Operator
Search for papers containing any of multiple terms:
"machine learning" OR "deep learning"
CRISPR OR "gene editing"
"climate change" OR "global warming"Best practices:
- OR must be uppercase
- Combine synonyms
- Include acronyms and spelled-out versions
- Use with exact phrases
Wildcard Search
Use asterisk (*) as wildcard for unknown words:
"machine * learning"
"CRISPR * editing"
"* neural network"Note: Limited wildcard support in Google Scholar compared to other databases.
Advanced Filtering
Year Range
Filter by publication year:
Using interface:
- Click "Since [year]" on left sidebar
- Select custom range
Using search operators:
# Not directly in search query
# Use interface or URL parametersIn script:
python scripts/search_google_scholar.py "quantum computing" \
--year-start 2020 \
--year-end 2024Sorting Options
By relevance (default):
- Google's algorithm determines relevance
- Considers citations, author reputation, publication venue
- Generally good for most searches
By date:
- Most recent papers first
- Good for fast-moving fields
- May miss highly cited older papers
- Click "Sort by date" in interface
By citation count (via script):
python scripts/search_google_scholar.py "transformers" \
--sort-by citations \
--limit 50Language Filtering
In interface:
- Settings → Languages
- Select preferred languages
Default: English and papers with English abstracts
Search Strategies
Finding Seminal Papers
Identify highly influential papers in a field:
1. Search by topic with broad terms 2. Sort by citations (most cited first) 3. Look for review articles for comprehensive overviews 4. Check publication dates for foundational vs recent work
Example:
"generative adversarial networks"
# Sort by citations
# Top results: original GAN paper (Goodfellow et al., 2014), key variantsFinding Recent Work
Stay current with latest research:
1. Search by topic 2. Filter to recent years (last 1-2 years) 3. Sort by date for newest first 4. Set up alerts for ongoing tracking
Example:
python scripts/search_google_scholar.py "AlphaFold protein structure" \
--year-start 2023 \
--year-end 2024 \
--limit 50Finding Review Articles
Get comprehensive overviews of a field:
intitle:review "machine learning"
"systematic review" CRISPR
intitle:survey "natural language processing"Indicators:
- "review", "survey", "perspective" in title
- Often highly cited
- Published in review journals (Nature Reviews, Trends, etc.)
- Comprehensive reference lists
Citation Chain Search
Forward citations (papers citing a key paper): 1. Find seminal paper 2. Click "Cited by X" 3. See all papers that cite it 4. Identify how field has developed
Backward citations (references in a key paper): 1. Find recent review or important paper 2. Check its reference list 3. Identify foundational work 4. Trace development of ideas
Example workflow:
# Find original transformer paper
"Attention is all you need" author:Vaswani
# Check "Cited by 120,000+"
# See evolution: BERT, GPT, T5, etc.
# Check references in original paper
# Find RNN, LSTM, attention mechanism originsComprehensive Literature Search
For thorough coverage (e.g., systematic reviews):
1. Generate synonym list:
- Main terms + alternatives
- Acronyms + spelled out
- US vs UK spelling
2. Use OR operators:
("machine learning" OR "deep learning" OR "neural networks")3. Combine multiple concepts:
("machine learning" OR "deep learning") ("drug discovery" OR "drug development")4. Search without date filters initially:
- Get total landscape
- Filter later if too many results
5. Export results for systematic analysis:
python scripts/search_google_scholar.py \
'"machine learning" OR "deep learning" drug discovery' \
--limit 500 \
--output comprehensive_search.jsonExtracting Citation Information
From Google Scholar Results Page
Each result shows:
- Title: Paper title (linked to full text if available)
- Authors: Author list (often truncated)
- Source: Journal/conference, year, publisher
- Cited by: Number of citations + link to citing papers
- Related articles: Link to similar papers
- All versions: Different versions of the same paper
Export Options
Manual export: 1. Click "Cite" under paper 2. Select BibTeX format 3. Copy citation
Limitations:
- One paper at a time
- Manual process
- Time-consuming for many papers
Automated export (using script):
# Search and export to BibTeX
python scripts/search_google_scholar.py "quantum computing" \
--limit 50 \
--format bibtex \
--output quantum_papers.bibMetadata Available
From Google Scholar you can typically extract:
- Title
- Authors (may be incomplete)
- Year
- Source (journal/conference)
- Citation count
- Link to full text (when available)
- Link to PDF (when available)
Note: Metadata quality varies:
- Some fields may be missing
- Author names may be incomplete
- Need to verify with DOI lookup for accuracy
Rate Limiting and Access
Rate Limits
Google Scholar has rate limiting to prevent automated scraping:
Symptoms of rate limiting:
- CAPTCHA challenges
- Temporary IP blocks
- 429 "Too Many Requests" errors
Best practices: 1. Add delays between requests: 2-5 seconds minimum 2. Limit query volume: Don't search hundreds of queries rapidly 3. Use scholarly library: Handles rate limiting automatically 4. Rotate User-Agents: Appear as different browsers 5. Consider proxies: For large-scale searches (use ethically)
In our scripts:
# Automatic rate limiting built in
time.sleep(random.uniform(3, 7)) # Random delay 3-7 secondsEthical Considerations
DO:
- Respect rate limits
- Use reasonable delays
- Cache results (don't re-query)
- Use official APIs when available
- Attribute data properly
DON'T:
- Scrape aggressively
- Use multiple IPs to bypass limits
- Violate terms of service
- Burden servers unnecessarily
- Use data commercially without permission
Institutional Access
Benefits of institutional access:
- Access to full-text PDFs through library subscriptions
- Better download capabilities
- Integration with library systems
- Link resolver to full text
Setup:
- Google Scholar → Settings → Library links
- Add your institution
- Links appear in search results
Tips and Best Practices
Search Optimization
1. Start simple, then refine:
# Too specific initially
intitle:"deep learning" intitle:review source:Nature 2023..2024
# Better approach
deep learning review
# Review results
# Add intitle:, source:, year filters as needed2. Use multiple search strategies:
- Keyword search
- Author search for known experts
- Citation chaining from key papers
- Source search in top journals
3. Check spelling and variations:
- Color vs colour
- Optimization vs optimisation
- Tumor vs tumour
- Try common misspellings if few results
4. Combine operators strategically:
# Good combination
author:Church intitle:"synthetic biology" 2015..2024
# Find reviews by specific author on topic in recent yearsResult Evaluation
1. Check citation counts:
- High citations indicate influence
- Recent papers may have low citations but be important
- Citation counts vary by field
2. Verify publication venue:
- Peer-reviewed journals vs preprints
- Conference proceedings
- Book chapters
- Technical reports
3. Check for full text access:
- [PDF] link on right side
- "All X versions" may have open access version
- Check institutional access
- Try author's website or ResearchGate
4. Look for review articles:
- Comprehensive overviews
- Good starting point for new topics
- Extensive reference lists
Managing Results
1. Use citation manager integration:
- Export to BibTeX
- Import to Zotero, Mendeley, EndNote
- Maintain organized library
2. Set up alerts for ongoing research:
- Google Scholar → Alerts
- Get emails for new papers matching query
- Track specific authors or topics
3. Create collections:
- Save papers to Google Scholar Library
- Organize by project or topic
- Add labels and notes
4. Export systematically:
# Save search results for later analysis
python scripts/search_google_scholar.py "your topic" \
--output topic_papers.json
# Can re-process later without re-searching
python scripts/extract_metadata.py \
--input topic_papers.json \
--output topic_refs.bibAdvanced Techniques
Boolean Logic Combinations
Combine multiple operators for precise searches:
# Highly cited reviews on specific topic by known authors
intitle:review "machine learning" ("drug discovery" OR "drug development")
author:Horvath OR author:Bengio 2020..2024
# Method papers excluding reviews
intitle:method "protein folding" -review -survey
# Papers in top journals only
("Nature" OR "Science" OR "Cell") CRISPR 2022..2024Finding Open Access Papers
# Search with generic terms
machine learning
# Filter by "All versions" which often includes preprints
# Look for green [PDF] links (often open access)
# Check arXiv, bioRxiv versionsIn script:
python scripts/search_google_scholar.py "topic" \
--open-access-only \
--output open_access_papers.jsonTracking Research Impact
For a specific paper: 1. Find the paper 2. Click "Cited by X" 3. Analyze citing papers:
- How is it being used?
- What fields cite it?
- Recent vs older citations?
For an author: 1. Search author:LastName 2. Check h-index and i10-index 3. View citation history graph 4. Identify most influential papers
For a topic: 1. Search topic 2. Sort by citations 3. Identify seminal papers (highly cited, older) 4. Check recent highly-cited papers (emerging important work)
Finding Preprints and Early Work
# arXiv papers
source:arxiv "deep learning"
# bioRxiv papers
source:biorxiv CRISPR
# All preprint servers
("arxiv" OR "biorxiv" OR "medrxiv") your topicNote: Preprints are not peer-reviewed. Always check if published version exists.
Common Issues and Solutions
Too Many Results
Problem: Search returns 100,000+ results, overwhelming.
Solutions: 1. Add more specific terms 2. Use intitle: to search only titles 3. Filter by recent years 4. Add exclusions (e.g., -review) 5. Search within specific journals
Too Few Results
Problem: Search returns 0-10 results, suspiciously few.
Solutions: 1. Remove restrictive operators 2. Try synonyms and related terms 3. Check spelling 4. Broaden year range 5. Use OR for alternative terms
Irrelevant Results
Problem: Results don't match intent.
Solutions: 1. Use exact phrases with quotes 2. Add more specific context terms 3. Use intitle: for title-only search 4. Exclude common irrelevant terms 5. Combine multiple specific terms
CAPTCHA or Rate Limiting
Problem: Google Scholar shows CAPTCHA or blocks access.
Solutions: 1. Wait several minutes before continuing 2. Reduce query frequency 3. Use longer delays in scripts (5-10 seconds) 4. Switch to different IP/network 5. Consider using institutional access
Missing Metadata
Problem: Author names, year, or venue missing from results.
Solutions: 1. Click through to see full details 2. Check "All versions" for better metadata 3. Look up by DOI if available 4. Extract metadata from CrossRef/PubMed instead 5. Manually verify from paper PDF
Duplicate Results
Problem: Same paper appears multiple times.
Solutions: 1. Click "All X versions" to see consolidated view 2. Choose version with best metadata 3. Use deduplication in post-processing:
python scripts/format_bibtex.py results.bib \
--deduplicate \
--output clean_results.bibIntegration with Scripts
search_google_scholar.py Usage
Basic search:
python scripts/search_google_scholar.py "machine learning drug discovery"With year filter:
python scripts/search_google_scholar.py "CRISPR" \
--year-start 2020 \
--year-end 2024 \
--limit 100Sort by citations:
python scripts/search_google_scholar.py "transformers" \
--sort-by citations \
--limit 50Export to BibTeX:
python scripts/search_google_scholar.py "quantum computing" \
--format bibtex \
--output quantum.bibExport to JSON for later processing:
python scripts/search_google_scholar.py "topic" \
--format json \
--output results.json
# Later: extract full metadata
python scripts/extract_metadata.py \
--input results.json \
--output references.bibBatch Searching
For multiple topics:
# Create file with search queries (queries.txt)
# One query per line
# Search each query
while read query; do
python scripts/search_google_scholar.py "$query" \
--limit 50 \
--output "${query// /_}.json"
sleep 10 # Delay between queries
done < queries.txtSummary
Google Scholar is the most comprehensive academic search engine, providing:
✓ Broad coverage: All disciplines, 100M+ documents ✓ Free access: No account or subscription required ✓ Citation tracking: "Cited by" for impact analysis ✓ Multiple formats: Articles, books, theses, patents ✓ Full-text search: Not just abstracts
Key strategies:
- Use advanced operators for precision
- Combine author, title, source searches
- Track citations for impact
- Export systematically to citation manager
- Respect rate limits and access policies
- Verify metadata with CrossRef/PubMed
For biomedical research, complement with PubMed for MeSH terms and curated metadata.
#!/usr/bin/env python3
"""
DOI to BibTeX Converter
Quick utility to convert DOIs to BibTeX format using CrossRef API.
"""
import sys
import requests
import argparse
import time
import json
from typing import Optional, List
class DOIConverter:
"""Convert DOIs to BibTeX entries using CrossRef API."""
def __init__(self):
self.session = requests.Session()
self.session.headers.update({
'User-Agent': 'DOIConverter/1.0 (Citation Management Tool; mailto:support@example.com)'
})
def doi_to_bibtex(self, doi: str) -> Optional[str]:
"""
Convert a single DOI to BibTeX format.
Args:
doi: Digital Object Identifier
Returns:
BibTeX string or None if conversion fails
"""
# Clean DOI (remove URL prefix if present)
doi = doi.strip()
if doi.startswith('https://doi.org/'):
doi = doi.replace('https://doi.org/', '')
elif doi.startswith('http://doi.org/'):
doi = doi.replace('http://doi.org/', '')
elif doi.startswith('doi:'):
doi = doi.replace('doi:', '')
# Request BibTeX from CrossRef content negotiation
url = f'https://doi.org/{doi}'
headers = {
'Accept': 'application/x-bibtex',
'User-Agent': 'DOIConverter/1.0 (Citation Management Tool)'
}
try:
response = self.session.get(url, headers=headers, timeout=15)
if response.status_code == 200:
bibtex = response.text.strip()
# CrossRef sometimes returns entries with @data type, convert to @misc
if bibtex.startswith('@data{'):
bibtex = bibtex.replace('@data{', '@misc{', 1)
return bibtex
elif response.status_code == 404:
print(f'Error: DOI not found: {doi}', file=sys.stderr)
return None
else:
print(f'Error: Failed to retrieve BibTeX for {doi} (status {response.status_code})', file=sys.stderr)
return None
except requests.exceptions.Timeout:
print(f'Error: Request timeout for DOI: {doi}', file=sys.stderr)
return None
except requests.exceptions.RequestException as e:
print(f'Error: Request failed for {doi}: {e}', file=sys.stderr)
return None
def convert_multiple(self, dois: List[str], delay: float = 0.5) -> List[str]:
"""
Convert multiple DOIs to BibTeX.
Args:
dois: List of DOIs
delay: Delay between requests (seconds) for rate limiting
Returns:
List of BibTeX entries (excludes failed conversions)
"""
bibtex_entries = []
for i, doi in enumerate(dois):
print(f'Converting DOI {i+1}/{len(dois)}: {doi}', file=sys.stderr)
bibtex = self.doi_to_bibtex(doi)
if bibtex:
bibtex_entries.append(bibtex)
# Rate limiting
if i < len(dois) - 1: # Don't delay after last request
time.sleep(delay)
return bibtex_entries
def main():
"""Command-line interface."""
parser = argparse.ArgumentParser(
description='Convert DOIs to BibTeX format using CrossRef API',
epilog='Example: python doi_to_bibtex.py 10.1038/s41586-021-03819-2'
)
parser.add_argument(
'dois',
nargs='*',
help='DOI(s) to convert (can provide multiple)'
)
parser.add_argument(
'-i', '--input',
help='Input file with DOIs (one per line)'
)
parser.add_argument(
'-o', '--output',
help='Output file for BibTeX (default: stdout)'
)
parser.add_argument(
'--delay',
type=float,
default=0.5,
help='Delay between requests in seconds (default: 0.5)'
)
parser.add_argument(
'--format',
choices=['bibtex', 'json'],
default='bibtex',
help='Output format (default: bibtex)'
)
args = parser.parse_args()
# Collect DOIs from command line and/or file
dois = []
if args.dois:
dois.extend(args.dois)
if args.input:
try:
with open(args.input, 'r', encoding='utf-8') as f:
file_dois = [line.strip() for line in f if line.strip()]
dois.extend(file_dois)
except FileNotFoundError:
print(f'Error: Input file not found: {args.input}', file=sys.stderr)
sys.exit(1)
except Exception as e:
print(f'Error reading input file: {e}', file=sys.stderr)
sys.exit(1)
if not dois:
parser.print_help()
sys.exit(1)
# Convert DOIs
converter = DOIConverter()
if len(dois) == 1:
bibtex = converter.doi_to_bibtex(dois[0])
if bibtex:
bibtex_entries = [bibtex]
else:
sys.exit(1)
else:
bibtex_entries = converter.convert_multiple(dois, delay=args.delay)
if not bibtex_entries:
print('Error: No successful conversions', file=sys.stderr)
sys.exit(1)
# Format output
if args.format == 'bibtex':
output = '\n\n'.join(bibtex_entries) + '\n'
else: # json
output = json.dumps({
'count': len(bibtex_entries),
'entries': bibtex_entries
}, indent=2)
# Write output
if args.output:
try:
with open(args.output, 'w', encoding='utf-8') as f:
f.write(output)
print(f'Successfully wrote {len(bibtex_entries)} entries to {args.output}', file=sys.stderr)
except Exception as e:
print(f'Error writing output file: {e}', file=sys.stderr)
sys.exit(1)
else:
print(output)
# Summary
if len(dois) > 1:
success_rate = len(bibtex_entries) / len(dois) * 100
print(f'\nConverted {len(bibtex_entries)}/{len(dois)} DOIs ({success_rate:.1f}%)', file=sys.stderr)
if __name__ == '__main__':
main()
#!/usr/bin/env python3
"""
Scientific schematic generation using Nano Banana 2.
Generate any scientific diagram by describing it in natural language.
Nano Banana 2 handles everything automatically with smart iterative refinement.
Smart iteration: Only regenerates if quality is below threshold for your document type.
Quality review: Uses Gemini 3.1 Pro Preview for professional scientific evaluation.
Usage:
# Generate for journal paper (highest quality threshold)
python generate_schematic.py "CONSORT flowchart" -o flowchart.png --doc-type journal
# Generate for presentation (lower threshold, faster)
python generate_schematic.py "Transformer architecture" -o transformer.png --doc-type presentation
# Generate for poster
python generate_schematic.py "MAPK signaling pathway" -o pathway.png --doc-type poster
"""
import argparse
import os
import subprocess
import sys
from pathlib import Path
def main():
"""Command-line interface."""
parser = argparse.ArgumentParser(
description="Generate scientific schematics using AI with smart iterative refinement",
formatter_class=argparse.RawDescriptionHelpFormatter,
epilog="""
How it works:
Simply describe your diagram in natural language
Nano Banana 2 generates it automatically with:
- Smart iteration (only regenerates if quality is below threshold)
- Quality review by Gemini 3.1 Pro Preview
- Document-type aware quality thresholds
- Publication-ready output
Document Types (quality thresholds):
journal 8.5/10 - Nature, Science, peer-reviewed journals
conference 8.0/10 - Conference papers
thesis 8.0/10 - Dissertations, theses
grant 8.0/10 - Grant proposals
preprint 7.5/10 - arXiv, bioRxiv, etc.
report 7.5/10 - Technical reports
poster 7.0/10 - Academic posters
presentation 6.5/10 - Slides, talks
default 7.5/10 - General purpose
Examples:
# Generate for journal paper (strict quality)
python generate_schematic.py "CONSORT participant flow" -o flowchart.png --doc-type journal
# Generate for poster (moderate quality)
python generate_schematic.py "Transformer architecture" -o arch.png --doc-type poster
# Generate for slides (faster, lower threshold)
python generate_schematic.py "System diagram" -o system.png --doc-type presentation
# Custom max iterations
python generate_schematic.py "Complex pathway" -o pathway.png --iterations 2
# Verbose output
python generate_schematic.py "Circuit diagram" -o circuit.png -v
Environment Variables:
OPENROUTER_API_KEY Required for AI generation
"""
)
parser.add_argument("prompt",
help="Description of the diagram to generate")
parser.add_argument("-o", "--output", required=True,
help="Output file path")
parser.add_argument("--doc-type", default="default",
choices=["journal", "conference", "poster", "presentation",
"report", "grant", "thesis", "preprint", "default"],
help="Document type for quality threshold (default: default)")
parser.add_argument("--iterations", type=int, default=2,
help="Maximum refinement iterations (default: 2, max: 2)")
parser.add_argument("--api-key",
help="OpenRouter API key (or use OPENROUTER_API_KEY env var)")
parser.add_argument("-v", "--verbose", action="store_true",
help="Verbose output")
args = parser.parse_args()
# Check for API key
api_key = args.api_key or os.getenv("OPENROUTER_API_KEY")
if not api_key:
print("Error: OPENROUTER_API_KEY environment variable not set")
print("\nFor AI generation, you need an OpenRouter API key.")
print("Get one at: https://openrouter.ai/keys")
print("\nSet it with:")
print(" export OPENROUTER_API_KEY='your_api_key'")
print("\nOr use --api-key flag")
sys.exit(1)
# Find AI generation script
script_dir = Path(__file__).parent
ai_script = script_dir / "generate_schematic_ai.py"
if not ai_script.exists():
print(f"Error: AI generation script not found: {ai_script}")
sys.exit(1)
# Build command
cmd = [sys.executable, str(ai_script), args.prompt, "-o", args.output]
if args.doc_type != "default":
cmd.extend(["--doc-type", args.doc_type])
# Enforce max 2 iterations
iterations = min(args.iterations, 2)
if iterations != 2:
cmd.extend(["--iterations", str(iterations)])
if args.verbose:
cmd.append("-v")
# Execute — pass API key via environment to avoid exposure in process listings
try:
env = os.environ.copy()
if api_key:
env["OPENROUTER_API_KEY"] = api_key
result = subprocess.run(cmd, check=False, env=env)
sys.exit(result.returncode)
except Exception as e:
print(f"Error executing AI generation: {e}")
sys.exit(1)
if __name__ == "__main__":
main()
Related skills
Forks & variants (1)
Citation Management has 1 known copy in the catalog totaling 118 installs. They canonicalize to this original listing.
- k-dense-ai - 118 installs
FAQ
What citation format does citation-management produce?
citation-management generates BibTeX .bib entries with fields like author, title, journal, year, volume, number, and pages, including properly escaped names for LaTeX bibliography builds.
When should developers use citation-management?
citation-management fits research-heavy projects needing accurate BibTeX files for papers, ML reports, or scientific agent docs instead of manually typed references that break LaTeX compiles.
Is Citation Management safe to install?
skills.sh reports 2 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.