Skill UI

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.

A comprehensive workflow for preparing and maintaining grounded, venue-compliant rebuttals to external academic reviews. It handles strict text-only character limits, manages responses for multiple reviewers (e.g., OpenReview style), supports follow-up rounds, and enforces safety gates against fabrication or overpromising. Ideal for the post-submission phase of research publishing.

Researcher persona keeps references, notes, and teams coordinated by using Drive folders, Docs summaries, Sheets logs, and Gmail-aware sharing plus workflow announcements for structured collaboration.

PIP kicks in when tasks fail repeatedly or the assistant becomes passive, layering Western big-tech performance rhetoric, a systematic debugging methodology, and proactivity enforcement so every code, ops, research, deployment, or writing task is owned, verified, and driven to completion.

A sophisticated, file-based system designed for organizing and tracking complex, multi-step projects. It utilizes structured Markdown files (task_plan.md, progress.md, findings.md) to maintain a complete record of plans, research findings, and progress updates. Ideal for project analysis, workflow management, and ensuring data integrity throughout the planning lifecycle.

This file-based system provides a structured method for organizing and tracking the progress of complex, multi-stage projects or extensive research tasks. It automatically generates and manages key files like `task_plan.md`, `findings.md`, and `progress.md`. It is ideal for users needing to deconstruct, plan, and maintain comprehensive visibility over large, complex workflows, supporting automatic session recovery and integrity checks.

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 guide details advanced techniques for searching cricket matches by leveraging precise numerical scoring data. Instead of broad terms, users should utilize specific details—such as team totals (e.g., 168/9), runs off balls, wickets taken, or over details—combined with the match type and year to create highly targeted search queries. This method significantly improves search accuracy and efficiency when researching sports statistics.

This technique guides users on decomposing multi-constraint questions, especially in the domain of football trivia or historical research. Instead of searching all criteria simultaneously, it instructs users to rank constraints by distinctiveness (e.g., specific match results first, then historical milestones). By performing incremental, cascading searches, the system dramatically narrows down the result set, leading to more accurate information retrieval.

A guide for refining search queries when researching Indian or South Asian actors. It emphasizes the necessity of including domain keywords such as "Bollywood," "Hindi film," or specific Indian award names (e.g., "Filmfare Award") to filter out irrelevant Western search results and drastically improve search precision.

Access comprehensive LaTeX templates, formatting requirements, and detailed submission guidelines for major academic venues. This skill supports the creation of manuscripts destined for top-tier journals (Nature, Science, Cell), international conferences (NeurIPS, ICML, CVPR), research posters, and major grant proposals (NSF, NIH, DOE). It ensures your work meets the specific formatting standards required by the target publication.

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.