Skill UI

This skill executes an end-to-end workflow combining research refinement and experiment planning. It transforms vague research directions into a focused final proposal and detailed experiment roadmap. It chains research-refine and experiment-plan to generate method theses, review histories, and validation plans. Ideal for academic research where both methodology and experimental validation are needed simultaneously.

This skill orchestrates deep critical reviews of research work using external AI models like Codex, Gemini, or Claude. It gathers project context, identifies logical gaps, and provides adversarial feedback on methodologies and results. Suitable for academic papers, experimental validation, and refining research ideas through multi-round reasoning.

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.

This skill performs in-depth literature reviews across complex communications domains, including 5G/6G, Wi-Fi, satellite networking, and advanced protocols. It systematically searches user-defined knowledge bases (Zotero, Obsidian, local files) and major academic databases (IEEE, ACM, ScienceDirect) to provide comprehensive survey summaries, related work analyses, and technical landscape overviews.

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.

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.

NOTE: This skill is DEPRECATED and should no longer be used for creating new posters. The functionality has been superseded by /paper-poster-html. Users must immediately migrate to the new HTML/CSS pipeline for accurate, measurement-gated poster generation, avoiding the legacy LaTeX flow.

Prepare and maintain venue-compliant rebuttals to external peer reviews. Parses reviewer feedback, ensures full issue coverage without fabrication, drafts safe text-only responses under character limits, and manages follow-up rounds for venues like ICML and OpenReview.

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.