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.

This skill allows users to search, fetch detailed metadata, download, and summarize academic papers from the arXiv repository. It supports searching by keywords or specific arXiv IDs and provides robust arguments for controlling the results count, output directory, and download scope. Ideal for students, researchers, and anyone requiring scholarly literature.

This skill automates the end-to-end academic paper writing process. It transforms raw narrative reports, research ideas, or existing plans into polished, submission-ready LaTeX source and PDF. The comprehensive pipeline includes planning, figure generation, structured writing, compilation, and an advanced improvement loop, allowing users to achieve publication-quality results. Users can optionally guide the structural style using a reference 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.

This tool systematically structures and derives complex research formulas and theoretical models. It takes scattered equations, messy notes, and ambiguous ideas, transforming them into a coherent, paper-ready derivation package. Use it when you need to build a rigorous theory line, organize explicit assumptions, or clarify the conceptual object underlying a set of formulas.

This skill automatically generates professional, structured conference presentation slides (PDF/PPTX) from a compiled academic paper. It intelligently adapts the content depth and slide count based on the specified talk type (e.g., oral, spotlight) and duration. Users can also optionally guide the structural rhythm of the talk by referencing another source paper's style.

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.

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.

This technique guides users through a rigorous two-phase research strategy. First, conduct a broad search to identify potential papers or authors. Crucially, the system instructs the user to use the extracted "author full name" as a highly specific anchor in subsequent queries. Combining the author's name with details like journal, institution, year, or biographical information ensures the most precise and reliable results, significantly narrowing down the search scope and achieving deep academic insights.