Skill UI

This agent provides structured summarization for academic papers, reports, and articles. It goes beyond simple summarizing by extracting key findings, generating comparative matrices across multiple sources, and producing properly formatted citations (APA, IEEE, etc.). It is designed for analysts, product managers, and researchers who need actionable, deep insights from dense documentation.

A comprehensive tool for interacting with the arXiv database. It allows users to search for academic papers by topic or ID, retrieve detailed metadata (abstracts, authors, categories), and download the PDF files directly. Ideal for researchers and students needing to efficiently find, save, and summarize scientific literature.

This advanced skill automates the rigorous, iterative review and refinement of complex research topics or papers. It runs multi-round cycles, using an external LLM (MiniMax API) to provide continuous, constructive feedback. The process guides the user through review, fixes, and re-review stages until a positive assessment is achieved or the maximum round limit is reached. It includes robust state persistence for long-running academic workflows.

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 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.

This skill provides a multi-round, deep critical review of research proposals, papers, or experimental results by simulating the perspective of a senior ML reviewer (e.g., NeurIPS/ICML level). It guides the user through identifying logical gaps, missing experiments, and narrative weaknesses, ensuring high fidelity and iterative refinement of technical work.

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.

A comprehensive tool for generating publication-quality figures essential for Machine Learning and AI academic papers. It supports two distinct workflows: generating complex system architecture and workflow diagrams using AI (Gemini), and creating precise, data-driven visualizations (line charts, heatmaps, etc.) using standard libraries like matplotlib and seaborn. Use it when preparing any figure for a conference submission.

A comprehensive tool designed to systematically plan ablation studies for machine learning research papers. It guides the process by having an AI (Codex) simulate a rigorous reviewer, identifying necessary experiments to isolate component contributions and answer critical research questions. It also includes a feasibility review step to manage compute resources and implementation complexity.

A comprehensive knowledge-base-first skill designed for deep literature reviews in advanced communication domains. Use it for topics like 4G/5G/6G, wireless networking, satellite communications, Wi-Fi, routing protocols, and cross-layer optimization. It systematically searches structured academic databases (IEEE, ACM, Zotero, etc.) to provide related work, survey papers, and landscape summaries.

A comprehensive tool and API wrapper for accessing, parsing, and analyzing research papers published on Hugging Face and arXiv. Users can input various URLs or IDs (e.g., arXiv ID) to retrieve structured metadata, full markdown content, and automatically link associated resources such as models, datasets, and application spaces. Ideal for researchers and developers needing structured access to cutting-edge AI knowledge.

A sophisticated, multi-stage workflow designed to generate publication-quality technical illustrations, such as architecture diagrams and complex method figures, for academic papers. It utilizes a strict, iterative loop supervised by an advanced AI (Claude) to refine layout, color compliance, and structural correctness, ensuring high fidelity and professional standards across multiple rendering passes.