Skill UI

This skill transforms flawed writing — whether pasted text or uploaded documents — into publication-ready prose. It eliminates grammatical, spelling, punctuation, clarity, and tone issues while strictly preserving the author’s original intent and unique voice. Use it for professional document refinement, academic paper polishing, or general text review, ensuring the corrected version maintains your authentic style.

Analyzes research papers to break down structure and summarize key points, offering citation highlights and insights for desk research or literature review planning.

Automates the entire process of converting LaTeX source files into a professional, submission-ready PDF. This tool handles multi-pass compilation (using latexmk), diagnoses common LaTeX errors (such as missing packages, undefined references, and BibTeX syntax errors), and performs post-compilation checks, including page count verification according to specific academic guidelines (ICLR, IEEE, etc.). Ideal for researchers submitting papers.

This skill generates a highly structured, section-by-section academic paper outline. It synthesizes raw research materials—including review conclusions, experimental results, and narrative reports—into a cohesive writing framework. Users can specify target conferences or journals (e.g., ICLR, NeurIPS) and even provide a style reference to guide the structural layout, ensuring the resulting plan meets rigorous academic standards.

This sophisticated tool drafts comprehensive LaTeX research papers by structuring content based on a detailed outline (paper plan) and integrating narrative reports, figures, and bibliographies. It supports various academic venues (ICLR, NeurIPS, etc.) and can optionally match the structural style of reference materials to ensure high publishing quality.

The Research Literature Review tool is designed to search, analyze, and summarize information from diverse academic sources. It integrates local PDF libraries, Zotero collections, Obsidian notes, and multiple web APIs (Semantic Scholar, DeepXiv, etc.). Use it when you need to conduct a comprehensive literature review, find related academic work, or understand the core ideas of a specific research paper.

Deep research and scientific writing assistant that produces LaTeX/BibTeX documents with verified citations for papers, proposals, reports, and reviews, ensuring well-formatted, citation-backed outputs for academic or clinical contexts.

Use this helper to search ten academic paper databases via their REST APIs whenever you need research papers, preprints, citation data, metadata, or open-access PDFs; it routes DOI/PMID/author/topic queries to the right endpoints and returns raw JSON plus the queried databases/paths.

Creates formally structured .docx academic documents with auto-updating TOC, OMML equations, styled headings, footnotes/endnotes, and bibliography formatting for research reports or policy briefs.

Generates professional conference presentation slides from a compiled research paper. This skill produces dual outputs: a polished Beamer LaTeX PDF for high-quality typesetting, and an editable PPTX for flexible adjustments. It supports multiple talk types (Poster, Spotlight, Oral, Invited) and includes detailed guidelines for speaker notes and talk scripting, making it essential for academic researchers preparing for major ML and systems conferences.

Utilize the ScholarEval framework for comprehensive and structured evaluation of academic works, including research papers, proposals, and literature reviews. Assess quality across critical dimensions like problem formulation, methodology rigor, data analysis, and scholarly writing. Provides both quantitative scoring and actionable feedback to enhance publication readiness.

This skill transforms an LLM into a disciplined wiki maintainer for Obsidian. It moves beyond simple RAG by incrementally ingesting sources (papers, notes, articles) to build a persistent, interlinked "Second Brain." The LLM manages cross-references, updates core concepts, and maintains an evolving knowledge graph, ensuring that knowledge compounds over time rather than being re-derived on every query. Ideal for deep research, personal knowledge management (PKM), and building comprehensive internal wikis.