Skill UI

Generates a structured paper outline from review conclusions and experiment results. Supports multiple venues (ICLR, NeurIPS, ICML, etc.), optional style reference from a source paper, and produces a gap report. Ideal for researchers planning papers before writing.

Drafts a LaTeX research paper section by section from an outline plan. Automatically applies venue-specific formats (ICLR, NeurIPS, CVPR, ACL, AAAI, ACM, IEEE), fetches real BibTeX records from DBLP/CrossRef to avoid hallucinated citations, enforces page-limit and anonymity conventions, and optionally profiles a reference paper for structural style. Use when moving from a paper plan to a complete LaTeX draft.

End-to-end autonomous research workflow covering idea discovery, experiments, review, and paper submission. Supports resumable runs, optional Lean formalization, and configurable checkpoints for human oversight.

Get a multi-round adversarial critical review of your research ideas, papers, or experimental results from an external LLM reviewer backend (Codex or manual). Compiles a briefing, runs ultra-reasoning review rounds, and returns a verdict with logical gaps, missing experiments, and narrative weaknesses.

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 skill structures and derives research formulas, building coherent derivation packages from scattered notes. It helps users formalize theory lines, organize assumptions, and produce paper-ready derivation documents. Ideal for researchers and students who need to clarify mathematical derivations or rewrite theory notes into structured, coherent presentations.

This skill provides comprehensive analysis and structured data extraction for academic research papers hosted on Hugging Face and arXiv. It can read paper content in markdown format, retrieve key metadata (authors, abstracts, GitHub repos), and identify linked assets such as associated models, datasets, and Spaces. Use this when the user provides a Hugging Face or arXiv URL, or explicitly requests a summary or explanation of an AI research topic.

This sophisticated tool generates publication-quality AI illustrations and diagrams for academic papers. It implements a multi-stage, iterative workflow, using advanced LLMs (like Claude and Gemini) to parse user requests, optimize complex layouts, verify academic styling (e.g., CVPR/NeurIPS standards), and render high-fidelity figures. Ideal for researchers needing professional, complex visuals for their manuscripts.

A specialized tool for searching published, peer-reviewed academic papers from major venues like IEEE, ACM, and Springer. Unlike preprint services (like arXiv), this skill provides verified citation counts, detailed venue metadata, and filtering options for finding established, high-impact research literature. Ideal for formal academic research and literature reviews.

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.

Generates structured peer-review quality critiques of academic papers, covering summaries, methodology scrutiny, contribution evaluation, literature positioning, and recommendations across domains whenever a user requests reviews, analyses, or summaries of research publications.

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.