Skill UI

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.

Runs multi-round deep research on any GitHub repository using the GitHub API plus web search and fetch, then delivers structured markdown reports with timelines, metrics, Mermaid diagrams and source citations.

Defines a systematic, multi-phase research methodology that prioritizes broad exploration, targeted deep dives, and validation before initiating any content generation, ensuring reliable, multi-angle web intelligence.

This toolkit provides comprehensive automation capabilities for Box cloud storage. It allows users to manage the entire document lifecycle, including file uploading and downloading, deep content searching using metadata filters, creating and modifying folders, and managing collaboration permissions. Ideal for integrating Box into automated business workflows, ensuring documents are always accessible and organized.

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.

This technique guides users through a rigorous two-phase research strategy. First, conduct a broad search to identify potential papers or authors. Crucially, the system instructs the user to use the extracted "author full name" as a highly specific anchor in subsequent queries. Combining the author's name with details like journal, institution, year, or biographical information ensures the most precise and reliable results, significantly narrowing down the search scope and achieving deep academic insights.

This skill acts as a literature-research assistant, orchestrating a Python CLI to interface with APIs like Semantic Scholar and arXiv. It enables users to search for academic papers by topic, retrieve detailed metadata, perform impact analysis using citation tracking, download PDFs, and extract text content. It streamlines the entire academic research workflow from initial discovery to deep reading.

This skill facilitates structured, bidirectional reading and knowledge synthesis for academic texts, theories, and articles. It forces users to first capture the source material's original intent, before critically mapping its relationships, conflicts, and absorptions against the CrossFrame framework. It ensures structured output with clear source boundaries, making it ideal for deep learning and scholarly work.

This guide assists researchers in transforming empirical findings into high-level, institutionally relevant policy implications for top-tier academic journals (e.g., finance and economics). It teaches how to shift focus from actionable 'recommendations' to theoretical 'implications,' ensuring the policy section is evidence-backed, macro-level, and deeply integrated with the paper's core theory and Chinese context.

This guide helps researchers strategically position their database, data management, or analytics papers for the International Conference on Very Large Data Bases (VLDB). It provides deep insights into conference positioning, required evidence (scale, systems depth), optimal structure, and how to compare the work against top venue standards. Use it before submission to refine your narrative and meet the archival standards of a flagship database conference.

This tool assists authors in positioning their academic manuscripts for the Journal of Macro-quality Research. It provides deep insights into the journal's scope, methodological preferences (macro econometrics, CGE, quality measurement), structural requirements, and common rejection pitfalls. It helps users tailor their writing and submission strategy to maximize acceptance chances.

An expert orchestrator and routing guide for manuscripts submitted to the Population and Development Review (PDR). It helps users determine the appropriate specialization path, whether they are starting an idea, refining the theory, or finalizing the submission. It matches the content's lifecycle stage and article type (e.g., Research Article, Notes & Commentary) to the correct development pipeline, ensuring the deep connection between population dynamics and societal policy is maintained.