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Found 29 Skills
Search, filter, and format entries from BibTeX or BibLaTeX .bib files for research workflows. Use when a user wants to find papers, search a bibliography, filter a library, or look up references by topic, author, year, venue, DOI, arXiv ID, keywords, annotation, abstract, or entry type. Handles Zotero-exported libraries. Supports compact search expressions such as author:, year-gte, type:, and has:, combined filters, research-oriented output fields, raw BibTeX export, and LaTeX/Typst citation snippet generation.
Export Google Scholar paper(s) to Zotero via BibTeX. Gets citation data from Google Scholar's cite dialog, then pushes to Zotero desktop. Supports single or batch export.
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.
Check the consistency and authenticity risks of citations and references in NSFC proposal text (read-only): Verify the existence of bibkey, format issues such as BibTeX fields and DOI, and generate structured input for the host AI to evaluate item-by-item whether the text expression actually cites the literature; by default, only an audit report is output, and the proposal or .bib file is not directly modified (unless the user explicitly requests it).
Search academic literature via Semantic Scholar MCP, select papers interactively, and generate verified BibTeX entries. 文献检索与BibTeX生成，通过Semantic Scholar MCP。
Guide LaTeX document authoring following best practices and proper semantic markup. Use proactively when: (1) writing or editing .tex files, (2) writing or editing .nw literate programming files, (3) literate-programming skill is active and working with .nw files, (4) user mentions LaTeX, BibTeX, or document formatting, (5) reviewing LaTeX code quality. Ensures proper use of semantic environments (description vs itemize), csquotes (\enquote{} not ``...''), and cleveref (\cref{} not \S\ref{}).
Use this skill when the user wants a systematic literature review, survey, or synthesis across multiple academic papers on a topic. Also covers annotated bibliographies and cross-paper comparisons. Searches arXiv and outputs reports in APA, IEEE, or BibTeX format. Not for single-paper tasks — use academic-paper-review for reviewing one paper.
Use this when the user explicitly requests to "verify/optimize in-text citations of the `{topic}_review.tex` review" or to "run check-review-alignment". Use the host AI's semantic understanding to verify each citation against the literature content one by one. **Only when fatal citation errors are found**, make minimal rewrites to the "sentences containing citations", and reuse the rendering script of `systematic-literature-review` to output PDF/Word (the script does not directly call the LLM API locally). Core principle: **Do not modify for the sake of modifying**. When it is uncertain whether it is a fatal error, keep the original content and issue a warning in the report. ⚠️ Not applicable in the following cases: - The user only wants to generate the main body of a systematic review (should use systematic-literature-review) - The user only wants to add/verify BibTeX entries (should use a dedicated bib management process)
Compile LaTeX papers to PDF with automatic error detection, chktex style checking, and citation/reference validation. Runs the full pdflatex + bibtex pipeline. Use when the user wants to compile a paper, fix compilation errors, or debug LaTeX.
Multi-source literature search, citation verification, MeSH search strategy, citation file management (.nbib/.ris/.bib conversion), and reference management (BibTeX, related articles, ID conversion) via MCP tools (PubMed, CrossRef, arXiv). Use when the user needs coordinated multi-step literature workflows beyond a single MCP call.
Use when normalizing BibTeX, RIS, CSL JSON, citation keys, DOI/arXiv/PMID metadata, references, unused citations, missing citations, or bibliography quality for papers and SOTA work.
For users needing to conduct systematic literature reviews, literature reviews, related work, or literature research: AI automatically generates search terms, performs multi-source retrieval → deduplication → AI reads and scores each paper one by one (1–10 points for semantic relevance and sub-topic grouping) → selects papers based on high-score priority ratio → automatically generates word budget for the review (70% cited sections + 30% non-cited sections, average of three samplings) → free writing in the style of senior domain experts (fixed sections: abstract, introduction, sub-topics, discussion, future outlook, conclusion), with strict verification of main text word count and number of references, and mandatory export to PDF and Word. Supports multilingual translation and intelligent compilation (en/zh/ja/de/fr/es).