Claude Scientific Writer is an AI-assisted research and writing tool that searches literature and produces documents such as scientific papers, reports, posters, grant proposals, and reviews with citations. Researchers and technical writers can use it as a Claude Code plugin, Python package, or command-line tool, with the catalogue entries defining agent workflows for it.
Borrowing it
Nothing to install: this file belongs to K-Dense-AI/claude-scientific-writer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/K-Dense-AI/claude-scientific-writer/main/.claude/skills/citation-management/SKILL.mdgit clone --depth 1 https://github.com/K-Dense-AI/claude-scientific-writerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/k-dense-ai/claude-scientific-writer/citation-management)<a href="https://agentmods.dev/skills/k-dense-ai/claude-scientific-writer/citation-management"><img src="https://agentmods.dev/badge/skills/k-dense-ai/claude-scientific-writer/citation-management/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/k-dense-ai/claude-scientific-writer/citation-management"><img src="https://agentmods.dev/badge/skills/k-dense-ai/claude-scientific-writer/citation-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 259 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 262 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.03604 |
| Opus 5.5 | $0.00029 | $0.01442 |
| Sonnet 5.5 | $0.00014 | $0.00721 |
| Haiku 4.5 | $0.00007 | $0.00360 |
Grade A, and why
citation-management scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 28d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 347 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
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.
# 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
What ships with it
20 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- assets/bibtex_template.bib 9.0 KB
- assets/citation_checklist.md 10 KB
- references/best_practices.md 2.6 KB
- references/bibtex_formatting.md 19 KB
- references/citation_validation.md 18 KB
- references/core_workflow.md 20 KB
- references/example_workflows.md 3.3 KB
- references/google_scholar_search.md 17 KB
- references/metadata_extraction.md 19 KB
- references/pubmed_search.md 17 KB
- references/script_reference.md 6.4 KB
- references/search_strategies.md 3.7 KB
- scripts/_common.py 11 KB runs code
- scripts/doi_to_bibtex.py 6.2 KB runs code
- scripts/extract_metadata.py 26 KB runs code
- scripts/format_bibtex.py 11 KB runs code
- scripts/search_google_scholar.py 8.4 KB runs code
- scripts/search_openalex.py 10 KB runs code
- scripts/search_pubmed.py 13 KB runs code
- scripts/validate_citations.py 26 KB runs code
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 28d ago Changed · +25 lines · +4 tokens per session 24b73d1d84e3
- 1mo ago First seen · 322 lines · 68 tokens per session scan A 2b5b41cdbd53
citation-management is a skill published in the GitHub repository K-Dense-AI/claude-scientific-writer (2,530 stars, last pushed 7d ago), licensed MIT. It adds 72 tokens to every session and 3,604 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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