Skill UI

A comprehensive guide for systematic statistical analysis, designed for academic research. This skill assists in selecting the correct hypothesis tests (t-test, ANOVA, regression, chi-square), checking assumptions (normality, homogeneity), performing advanced analyses (Bayesian methods, power analysis), calculating effect sizes, and generating full APA-formatted reports for publication.

A robust Python client wrapper for interacting with the Zotero Web API v3. This skill allows users to programmatically manage academic references, including retrieving, creating, updating, and deleting items, collections, tags, and attachments. Ideal for academic researchers building automated workflows, bulk exporting citations (e.g., BibTeX), or integrating Zotero data into larger research applications.

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.

This skill provides comprehensive tools for AI engineers and researchers to publish, manage, and link research papers directly on the Hugging Face Hub. It supports creating dedicated paper pages, linking papers to corresponding models and datasets, claiming authorship, and generating professional, markdown-based research articles with LaTeX support. Use it to streamline the entire academic publishing workflow from initial draft to final publication.

This skill guides users in systematically organizing and documenting a year's worth of past projects into the specific SRED format. It processes scattered evidence—including GitHub PRs, Notion documents, and Linear tickets—to evaluate project suitability, generate comprehensive descriptions, and create structured, standardized reports within Notion. Ideal for formal academic submissions or professional portfolio creation.

Simulates the persona of Geoffrey Hinton, a Turing Award winner and pioneer of deep learning. This skill adopts his first-person voice, combining deep technical knowledge (including backpropagation, deep belief networks, and Boltzmann machines) with academic rigor, epistemic humility, and characteristic British humor. It is ideal for in-depth discussions on the theoretical foundations, history, and principles of complex system learning in AI.

This skill automates the complex and tedious process of porting academic papers written in LaTeX from one publisher's journal template (e.g., Springer) to another (e.g., MDPI, IEEE). It executes a structured multi-stage workflow, including content extraction, structural mapping, systematic fixing of common LaTeX issues (like float placement and math environments), and final compilation to ensure the output adheres to the target journal's specifications.

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.

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 implements an autonomous, multi-round research review loop, simulating the rigorous peer-review process of top-tier conferences. It iteratively reviews, identifies weaknesses, suggests fixes, and re-reviews a research document using the MiniMax API. The system manages state persistence across multiple rounds, ensuring continuous improvement until a 'ready' assessment is achieved or the maximum round limit is reached. Ideal for academic writing, thesis refinement, or comprehensive project documentation.

This skill verifies the novelty of research ideas against recent academic literature. It extracts core technical claims, searches databases like arXiv and Google Scholar, and cross-model verifies findings to determine if an idea is truly new or already published. It outputs a structured report with a novelty score and recommendation.

Generate publication-quality figures and comparison tables from experiment results for academic papers. Automatically selects plot types from data and produces vector PDFs at 300 DPI.