Skill UI

A comprehensive guide for authors handling the conditional acceptance stage of POPL. It details the two-gate process: first, satisfying the mandatory committee revisions, and second, de-anonymizing and formatting the paper for the official PACMPL journal issue. Covers metadata management, ORCIDs, open access rights, and logistical planning for the final conference talk.

This tool serves as an orchestrator for developing Public Administration Review (PAR) manuscripts. It guides researchers through the entire writing lifecycle—from initial topic selection and literature positioning to theory building, data analysis, and final submission/rebuttal. It helps users determine the most appropriate article type (e.g., Scholarly Take, Conceptualizing PA) and maps the necessary steps to ensure the work bridges both academic theory and practical public management relevance.

A comprehensive project management skill designed for academic submissions in Recommender Systems (RecSys). It guides users through the entire research lifecycle, from initial venue fit and data freezing to abstract submission, full paper writing, anonymous repository management, rebuttal drafting, and final camera-ready preparation. It provides backward-planning time offsets and risk identification.

A comprehensive pre-submission audit checklist for authors preparing papers for the SIGMOD conference. It covers critical rules such as double-anonymous formatting, ACM template compliance, abstract-plus-COI pre-deadlines, and avoiding common desk-reject hazards. Use this guide to ensure your submission meets the rigorous technical and ethical standards required for top-tier data management publications.

A comprehensive methodological guide for researchers submitting data management papers. It helps users assess if their contribution is a fundamental system advance or merely an application. The guide provides detailed decision frameworks and comparisons between top-tier venues like SIGMOD, PVLDB, KDD, and PODS, ensuring the focus remains on the core data-management primitive.

A comprehensive guide for positioning a paper for ACM SoCC. It instructs authors to write the related work section by bridging both systems literature (e.g., OSDI, NSDI) and data-management literature (e.g., SIGMOD, VLDB). Focus must be on stating the 'delta'—the unique difference—rather than merely listing citations, ensuring dual anonymity and covering all relevant technical lanes.

This guide helps researchers determine the ideal venue for their cloud computing research paper. It outlines the architectural boundaries between pure systems (OSDI/SOSP), pure data management (SIGMOD/VLDB), and the systems-data intersection (SoCC). It provides crucial tests, such as the model-swap and re-label tests, and advises on necessary evidence maturity (measurement studies, experience papers) to ensure a high chance of acceptance.

This comprehensive guide helps researchers determine if their project qualifies as a core data-management primitive, which specific PVLDB category (Regular, EA&B, Scalable Data Science, Vision) it belongs to, and whether a major data conference like VLDB or SIGMOD is the optimal submission venue. It provides a rigorous primitive test and detailed routing advice for top-tier data systems research.

This comprehensive skill provides systematic tools for academic research and writing. Users can search major databases (Google Scholar, PubMed), extract accurate metadata from identifiers (DOI, PMID, arXiv), validate existing citations, and generate correctly formatted BibTeX entries. It ensures reproducible research and maintains high citation accuracy throughout the writing process.

A comprehensive tool designed to help developers compare multiple technical approaches for solving a single problem. It systematically identifies and analyzes the trade-offs, complexity, performance, and learning curves associated with different design patterns (e.g., state management, data fetching, API design). Ideal for architectural reviews and making informed, robust technology stack decisions.

Provides a hardened FastAPI endpoint for OpenMed's core functionalities: clinical Named Entity Recognition (NER), Personally Identifiable Information (PII) extraction, and de-identification. Designed for self-hosted microservices, it handles inference requests, model lifecycle management, and supports dynamic batching, ensuring secure, on-device processing of sensitive clinical data.