zLanqing/codex-claude-academic-skills is a collection of three skills for academic writing, editable Word and PowerPoint documents, and scientific computing with MATLAB and Python. Chinese-speaking researchers use it for literature reports, papers, presentations, data analysis, simulations, and publication figures in Claude Code or Codex. The catalogue contains the project's academic workflow skills.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/zLanqing/codex-claude-academic-skillsnpx agentmods add skills/zlanqing/codex-claude-academic-skills/citation-managementWrote 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/zlanqing/codex-claude-academic-skills/citation-management)<a href="https://agentmods.dev/skills/zlanqing/codex-claude-academic-skills/citation-management"><img src="https://agentmods.dev/badge/skills/zlanqing/codex-claude-academic-skills/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/zlanqing/codex-claude-academic-skills/citation-management"><img src="https://agentmods.dev/badge/skills/zlanqing/codex-claude-academic-skills/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 1061 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 1064 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 | $0.00068 | $0.07971 |
| Opus 5 | $0.00034 | $0.03986 |
| Sonnet 5 | $0.00014 | $0.01594 |
| Haiku 4.5 | $0.00007 | $0.00797 |
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 11d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- citation-management — 100% identical, 2 lines differ
- citation-management — 100% identical, 0 lines differ
- citation-management — 100% identical, 0 lines differ
- citation-management — 100% identical, 3 lines differ
- citation-management — 100% identical, 0 lines differ
- citation-management — 98% identical, 2 lines differ
- citation-management — 91% identical, 175 lines differ
- citation-management — 91% identical, 175 lines differ
How it starts
The opening of the file, as written. The whole thing — 1,114 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
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.png
The 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
What ships with it
13 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/bibtex_formatting.md 19 KB
- references/citation_validation.md 16 KB
- references/google_scholar_search.md 17 KB
- references/metadata_extraction.md 19 KB
- references/pubmed_search.md 17 KB
- scripts/doi_to_bibtex.py 6.2 KB runs code
- scripts/extract_metadata.py 20 KB runs code
- scripts/format_bibtex.py 11 KB runs code
- scripts/search_google_scholar.py 8.8 KB runs code
- scripts/search_pubmed.py 13 KB runs code
- scripts/validate_citations.py 17 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.
- 11d ago First seen · 1,114 lines · 68 tokens per session scan A 9813e12cdf02
citation-management is a skill published in the GitHub repository zLanqing/codex-claude-academic-skills (3,735 stars, last pushed 4mo ago), licensed MIT. It adds 68 tokens to every session and 7,971 once invoked, about $0.0003 per session on Opus 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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