brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent,…
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation
$ npx -y skills add xintaofei/codeg --skill citation-management --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/citation-managementContext preview
The summary Claude sees to decide when to auto-load this skill.
Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation
name: citation-management
description: Comprehensive citation management for academic research. Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries. This skill should be used when you need to find papers, verify citation information, convert DOIs to BibTeX, or ensure reference accuracy in scientific writing.
allowed-tools: Read Write Edit Bash
license: MIT License
required_environment_variables: [{"name": "OPENROUTER_API_KEY", "prompt": "OpenRouter API key for LLM-powered citation steps.", "required_for": "optional features"}, {"name": "NCBI_EMAIL", "prompt": "Email for NCBI Entrez identification.", "required_for": "optional features"}, {"name": "NCBI_API_KEY", "prompt": "NCBI API key to raise Entrez rate limits.", "required_for": "optional features"}]
metadata: {"version": "1.2", "skill-author": "K-Dense Inc.", "openclaw": {"primaryEnv": "OPENROUTER_API_KEY", "envVars": [{"name": "OPENROUTER_API_KEY", "required": false, "description": "OpenRouter API key for LLM-powered citation steps."}, {"name": "NCBI_EMAIL", "required": false, "description": "Email for NCBI Entrez identification."}, {"name": "NCBI_API_KEY", "required": false, "description": "NCBI API key to raise Entrez rate limits."}]}}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.
Use this skill when:
**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:
**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.png
The AI will automatically:
**When to add schematics:**
For detailed guidance on creating schematics, refer to the scientific-schematics skill documentation.
---
Citation management follows a systematic process:
**Goal**: Find relevant papers using academic search engines.
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`):
**Best Practices**:
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.json
**Advanced PubMed Queries** (see `references/pubmed_search.md`):
**Best Practices**:
English | 简体中文 | 繁體中文 | 日本語 | 한국어 | Español | Deutsch | Français | Português | العربية Codeg (Code Generation) is a multi-agent coding workspace: run every AI coding agent in one place — and let them work together.
Repo: xintaofei/codeg
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent,…
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Use when implementation is complete, all tests pass, and you need to decide how to integrate the work
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical…
Use when completing tasks, implementing major features, or before merging to verify work meets requirements