Citation Management workflow skill. Use this skill when the user needs Manage citations systematically throughout the research and writing process and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Citation Management workflow skill. Use this skill when the user needs Manage citations systematically throughout the research and writing process and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-awesome-skills/skills/citation-management from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
Citation Management
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Visual Enhancement with Scientific Schematics, Search Strategies, Tools and Scripts, Common Pitfalls to Avoid, Integration with Other Skills, Dependencies.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
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
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
SKILL.md
Starts with the smallest copied file that materially changes execution
Supporting context
SKILL.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
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
Use specific, targeted search terms
Imported Workflow Notes
Imported: 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.json
Advanced 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).
Advanced 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 json
Comprehensive 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.bib
Metadata Sources (see references/metadata_extraction.md):
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
PubMed E-utilities: Biomedical literature
Official NCBI metadata
Includes MeSH terms, abstracts
PMID and PMCID identifiers
Free, API key recommended for high volume
arXiv API: Preprints in physics, math, CS, q-bio
Complete metadata for preprints
Version tracking
Author affiliations
Free, open access
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
# 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 issuescat 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:
Use literature-review for comprehensive multi-database search
Use citation-management to extract and validate all citations
Use literature-review to synthesize findings thematically
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.bib
# You have a text file with DOIs (one per line)# dois.txt contains:# 10.1038/s41586-021-03819-2# 10.1126/science.aam9317# 10.1016/j.cell.2023.01.001# Convert all to BibTeX
python scripts/doi_to_bibtex.py --input dois.txt --output references.bib
# Validate the result
python scripts/validate_citations.py references.bib --verbose
Example 3: Cleaning an Existing BibTeX File
# 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 reportcat final_validation.json
Example 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 papers
Imported: 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.
Imported: Summary
The citation-management skill provides:
Comprehensive search capabilities for Google Scholar and PubMed
Automated metadata extraction from DOI, PMID, arXiv ID, URLs
Citation validation with DOI verification and completeness checking
BibTeX formatting with standardization and cleaning tools
Quality assurance through validation and reporting
Integration with scientific writing workflow
Reproducibility through documented search and extraction methods
Use this skill to maintain accurate, complete citations throughout your research and ensure publication-ready bibliographies.
Imported: 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.
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.
Examples
Example 1: Ask for the upstream workflow directly
Use @citation-management-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @citation-management-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @citation-management-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @citation-management-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
Start broad, then narrow:
Begin with general terms to understand the field
Refine with specific keywords and filters
Use synonyms and related terms
Use multiple sources:
Google Scholar for comprehensive coverage
PubMed for biomedical focus
Imported Operating Notes
Imported: Best Practices
Search Strategy
Start broad, then narrow:
Begin with general terms to understand the field
Refine with specific keywords and filters
Use synonyms and related terms
Use multiple sources:
Google Scholar for comprehensive coverage
PubMed for biomedical focus
arXiv for preprints
Combine results for completeness
Leverage citations:
Check "Cited by" for seminal papers
Review references from key papers
Use citation networks to discover related work
Document your searches:
Save search queries and dates
Record number of results
Note any filters or restrictions applied
Metadata Extraction
Always use DOIs when available:
Most reliable identifier
Permanent link to the publication
Best metadata source via CrossRef
Verify extracted metadata:
Check author names are correct
Verify journal/conference names
Confirm publication year
Validate page numbers and volume
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
Maintain consistency:
Use consistent author name format
Standardize journal abbreviations
Use same DOI format (URL preferred)
BibTeX Quality
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
Keep it clean:
Remove unnecessary fields
No redundant information
Consistent formatting
Validate syntax regularly
Organize systematically:
Sort by year or topic
Group related papers
Use separate files for different projects
Merge carefully to avoid duplicates
Validation
Validate early and often:
Check citations when adding them
Validate complete bibliography before submission
Re-validate after any manual edits
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
Manual review for critical citations:
Verify key papers cited correctly
Check author names match publication
Confirm page numbers and volume
Ensure URLs are current
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/citation-management, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
@00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
@00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/n/a
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
assets/n/a
Imported Reference Notes
Imported: Resources
Bundled Resources
References (in references/):
google_scholar_search.md: Complete Google Scholar search guide
pubmed_search.md: PubMed and E-utilities API documentation
metadata_extraction.md: Metadata sources and field requirements
citation_validation.md: Validation criteria and quality checks
bibtex_formatting.md: BibTeX entry types and formatting rules
Scripts (in scripts/):
search_google_scholar.py: Google Scholar search automation
search_pubmed.py: PubMed E-utilities API client
extract_metadata.py: Universal metadata extractor
validate_citations.py: Citation validation and verification
format_bibtex.py: BibTeX formatter and cleaner
doi_to_bibtex.py: Quick DOI to BibTeX converter
Assets (in assets/):
bibtex_template.bib: Example BibTeX entries for all types
Look for review articles from Tier-1 journals for overview
Check "Cited by" for impact assessment and recent follow-up work
Use citation alerts for tracking new citations to key papers
Filter by top venues using source:Nature or source:Science
Search for papers by known field leaders using author:LastName
Advanced Operators (full list in references/google_scholar_search.md):
"exact phrase" # Exact phrase matching
author:lastname # Search by author
intitle:keyword # Search in title only
source:journal # Search specific journal
-exclude # Exclude terms
OR # Alternative terms
2020..2024 # Year range
Example Searches:
# Find recent reviews on a topic
"CRISPR" intitle:review 2023..2024
# Find papers by specific author on topic
author:Church "synthetic biology"
# Find highly cited foundational work
"deep learning" 2012..2015 sort:citations
# Exclude surveys and focus on methods
"protein folding" -survey -review intitle:method
PubMed Best Practices
Using MeSH Terms:
MeSH (Medical Subject Headings) provides controlled vocabulary for precise searching.
[Title] # Search in title only
[Title/Abstract] # Search in title or abstract
[Author] # Search by author name
[Journal] # Search specific journal
[Publication Date] # Date range
[Publication Type] # Article type
[MeSH] # MeSH term
Building Complex Queries:
# 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.
