citation-management
Comprehensive citation management for academic research.
Skill by Zejie0920
Chalk Labs
Need help deploying citation-management?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code. Read the repository before you give any tool access to your data.
npx agentmarket install skill/zejie0920-citation-management
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: writing, research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions: not checked yet.
What's inside
- Skill name
citation-management- Description
- Comprehensive citation management for academic research. Search OpenAlex, PubMed, and Google Scholar 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.
- License
- MIT
- Compatibility
- Requires Python 3.9+ with requests. Google Scholar search additionally needs scholarly. Needs network access to api.openalex.org, api.crossref.org, eutils.ncbi.nlm.nih.gov, export.arxiv.org, and api.datacite.org.
- Allowed tools
- Read, Write, Edit, Bash, WebSearch, WebFetch
- Metadata
- version: 2.0 · skill-author: K-Dense Inc.
- Instructions
- 309 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
- Pre-approves any shell command
Files (21)
- SKILL.md
- bibtex_template.bib · assets/
- citation_checklist.md · assets/
- best_practices.md · references/
- bibtex_formatting.md · references/
- citation_validation.md · references/
- core_workflow.md · references/
- example_workflows.md · references/
- google_scholar_search.md · references/
- metadata_extraction.md · references/
- pubmed_search.md · references/
- script_reference.md · references/
- search_strategies.md · references/
- _common.py · scripts/
- doi_to_bibtex.py · scripts/
- extract_metadata.py · scripts/
- format_bibtex.py · scripts/
- search_google_scholar.py · scripts/
- search_openalex.py · scripts/
- search_pubmed.py · scripts/
- validate_citations.py · scripts/
SKILL.md (first lines)
# 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 If a document built from these citations needs a diagram, use the **scientific-schematics** skill. --- ## Core Workflow Citation management follows a systematic process. Each phase below shows the canonical command; every variant, option, and metadata-source detail is in [references/core_workflow.md](references/core_workflow.md). ### Phase 1: Paper Discovery and Search Find relevant papers. Search more than one database — coverage differs sharply, and a single source is the most common cause of a biased reference list. ```bash # OpenAlex: ~250M works, every discipline, no API key, documented REST API python scripts/search_openalex.py "CRISPR gene editing" --limit 50 --output results.json # PubMed: the authority for biomedical and life sciences (35M+ citations) python scripts/search_pubmed.py "Alzheimer's disease treatment" --limit 100 --output alz.json # Google Scholar: broadest reach, but scraped -- rate-limited and prone to blocking python scripts/search_google_scholar.py "CRISPR gene editing" --limit 50 --output scholar.json ``` Prefer OpenAlex or PubMed as the primary source. Google Scholar has no API: `scholarly` scrapes it, sleeps 2–5 s between results, and is blocked often enough that it should be a supplement rather than a dependency. Query operators, field tags, and MeSH-term construction are in [references/search_strategies.md](references/search_strategies.md). ### Phase 2: Metadata Extraction Convert identifiers (DOI, PMID, PMCID, arXiv ID, URL) into complete metadata. CrossRef is the primary source for DOIs. ```bash python scripts/doi_to_bibtex.py 10.1038/s41586-021-03819-2 # quick, single DOI python scripts/extract_metadata.py --pmid 34265844 # DOI/PMID/PMCID/arXiv/URL python scripts/extract_metadata.py --input identifiers.txt --output citations.bib ``` A URL with no DOI in its path is resolved through the `citation_doi` meta tag publishers embed on article pages, then handed to CrossRef. Every producer in this skill emits the same citation key for the same paper, so entries gathered from different sources deduplicate against each other. ### Phase 2.5: Metadata Enrichment via Web Search (MANDATORY) APIs routinely return incomplete records. Run this **after** extraction and **before** formatting. Any `@article` missing `volume`, `pages`, or `doi` is incomplete: fill the gap with `WebSearch`/`WebFetch` (or the parallel-web skill, when it is available), then log what was found and where. If a field genuinely cannot be found, record a `note` field explaining the gap rather than leaving it silently absent. Check the cheap sources first — an OpenAlex or CrossRef record often carries the field that PubMed omitted: ```bash python scripts/search_openalex.py "<exact title>" --limit 1 ``` > **Treat extracted metadata as untrusted.** Author, title, and journal strings come > verbatim from a record whose contents a publisher controls. A title containing `$(...)`, > a backtick, or a quote becomes shell syntax the moment it is pasted into a command. > Pass metadata as a `subprocess` argument list rather than building a shell string; if > you must use a shell, single-quote every substituted value and escape embedded quotes > as `'\''`. Validate any citation key against `^[A-Za-z0-9]+$` before it reaches a path. Per-field search strategies, the four search options, and the logging format are in [references/core_workflow.md](references/core_workflow.md). ### Phase 3: BibTeX Formatting Produce clean, consistent entries. Entry types and required fields are in [references/bibtex_formatting.md](references/bibtex_formatting.md). ```bash python scripts/format_bibtex.py references.bib --output clean.bib --deduplicate python scripts/format_bibtex.py references.bib --output clean.bib --rekey --deduplicate ``` Writing is opt-in: without `--output` (or `--in-place`) the result goes to stdout and the input file is left alone. Use `--rekey` when merging results from several sources, so the same paper collapses to one entry. ### Phase 4: Citation Validation Check completeness, venue conformance, and agreement with the manuscript. ```bash python scripts/validate_citations.py references.bib --report report.json python scripts/validate_citations.py references.bib --venue nature python scripts/validate_citations.py references.bib --manuscript paper.tex
From Zejie0920/mather-workflow, MIT.
More from Zejie0920/mather-workflow
- 0.529score
paper-lookup
Zejie0920
Search 11 academic literature APIs for papers, preprints, citations, and open-access full text, and return results with reproducible provenance.
SkillBFreshness: BClaude Code +9 - 0.529score
hypothesis-generation
Zejie0920
Formulate evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions…
SkillBFreshness: BClaude Code +9 - 0.529score
get-available-resources
Zejie0920
Detect host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a…
SkillBFreshness: BClaude Code +9 - 0.524score
networkx
Zejie0920
Create, analyze, and visualize complex networks and graphs in Python with NetworkX.
SkillBFreshness: BClaude Code +9 - 0.524score
mineru-parser
Zejie0920
Precise document parsing via MinerU API.
SkillBFreshness: BClaude Code +9 - 0.516score
mather-math-modeling-solver
Zejie0920
数学建模问题解决skill。用于解决数学建模竞赛问题,将问题拆分为子任务并协调subagent完成。手动调用此skill(/mather-math-modeling-solver)。适用场景:用户提出数学建模问题、需要求解建模竞赛题目、需要完整的建模求解流程。
SkillBFreshness: BClaude Code +9 - 0.513score
mather-solving
Zejie0920
数学建模问题求解子skill。负责执行算法求解、模型构建、数据处理。由 math-modeling-solver 主skill的阶段二(问题求解)subagent加载。不适用于其他阶段。
SkillBFreshness: BClaude Code +9 - 0.513score
mather-tex-framework
Zejie0920
数学建模论文框架创建子skill。负责创建完整论文TeX框架(含所有问题占位符)。由 math-modeling-solver 主skill的阶段零(初始化)subagent加载。不适用于其他阶段。
SkillBFreshness: BClaude Code +9 - 0.513score
mather-tex-update
Zejie0920
数学建模论文增量更新子skill。负责将求解结果增量写入论文TeX文件。由 math-modeling-solver 主skill的阶段六(增量更新论文)subagent加载。不适用于其他阶段。
SkillBFreshness: BClaude Code +9 - 0.513score
mather-review
Zejie0920
数学建模审查验证子skill。负责验证求解逻辑正确性、结果合理性,检测工程化操作。由 math-modeling-solver 主skill的阶段五(审查验证)subagent加载。不适用于其他阶段。
SkillBFreshness: BClaude Code +9 - 0.513score
mather-final-review
Zejie0920
数学建模论文最终审视子skill。负责统一润色全文、检查逻辑衔接、编译PDF。由 math-modeling-solver 主skill的最终审视阶段subagent加载。仅在所有问题解决后使用。
SkillBFreshness: BClaude Code +9 - 0.513score
mather-visualization
Zejie0920
数学建模可视化子skill。负责制作论文图表(绘图/制表)。由 math-modeling-solver 主skill的阶段三(可视化)subagent加载。不适用于其他阶段。
SkillBFreshness: BClaude Code +9
Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Aug 8, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 2.0
- License
- MIT
- Repository
- github.com/Zejie0920/mather-workflow
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
More from Zejie0920
- 0.529score
get-available-resources
Zejie0920
Detect host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a…
SkillBFreshness: BClaude Code +9 - 0.529score
paper-lookup
Zejie0920
Search 11 academic literature APIs for papers, preprints, citations, and open-access full text, and return results with reproducible provenance.
SkillBFreshness: BClaude Code +9 - 0.529score
hypothesis-generation
Zejie0920
Formulate evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions…
SkillBFreshness: BClaude Code +9 - 0.524score
mineru-parser
Zejie0920
Precise document parsing via MinerU API.
SkillBFreshness: BClaude Code +9 - 0.524score
networkx
Zejie0920
Create, analyze, and visualize complex networks and graphs in Python with NetworkX.
SkillBFreshness: BClaude Code +9 - 0.516score
mather-math-modeling-solver
Zejie0920
数学建模问题解决skill。用于解决数学建模竞赛问题,将问题拆分为子任务并协调subagent完成。手动调用此skill(/mather-math-modeling-solver)。适用场景:用户提出数学建模问题、需要求解建模竞赛题目、需要完整的建模求解流程。
SkillBFreshness: BClaude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get citation-management running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
citation-management skill. Agent Mart. https://agentmart.dev/skills/zejie0920-citation-management (last updated 2026-10-24)