Skill UI

Analyzes occupational health data to assess work-related risks, ergonomic issues, symptoms, and trends. Use it to generate personalized workplace health advice, screen for occupational hazards, and relate work factors to sleep, exercise, and mental health.

Search and analyze research papers across Zotero, local PDFs, arXiv, Semantic Scholar and the web. Finds related work, summarizes key ideas, and builds literature reviews with citation metadata.

A comprehensive workflow for scraping and extracting structured data from Google search results using the SerpApi. It captures all key components, including organic listings, knowledge graphs, answer boxes, People Also Ask (PAA), local pack results, and related searches. Ideal for SEO monitoring, market research, competitive analysis, or building search-powered features that require deep, structured data insights.

A comprehensive guide for authors submitting papers related to web search, ranking, and data mining to WSDM. It provides critical advice on conference fit assessment, proper manuscript re-framing, required evidence (retrieval/ranking baselines, platform-aware evaluation), and how to position the work against competing top venues like SIGIR and KDD.

This guide details the complex requirements for writing the 'Related Work' section for CIKM submissions. It emphasizes the need for 'three-front coverage' (Retrieval, Mining, and Knowledge Management/Databases) and provides specific instructions on writing the 'boundary-work paragraph.' It also covers critical academic hygiene, such as avoiding venue misattribution, maintaining recency baselines, and accurately stating novel contributions.

A comprehensive guide on structuring and writing the 'Related Work' section for elite computer vision conferences like CVPR. It addresses the high velocity of academic literature, teaching advanced methods like defining explicit technical deltas, structuring arguments by research question, maintaining citation hygiene, and handling complex reviewer feedback on originality and concurrency.

A comprehensive guide for positioning novel research in elite computer vision and AI conferences (e.g., ECCV). It details how to structure the related work section by tracing academic lineage, handling concurrent work, verifying citation hygiene across venues (CVPR, ICCV, ECCV), and transforming simple bibliographies into strong, argumentative prose. Essential for improving novelty visibility.

A comprehensive guide for positioning database research papers for top-tier conferences like ICDE. It teaches authors how to distinguish genuine novelty (new mechanisms) from engineering delta (implementation improvements), conduct deep literature audits, and compare their work against both academic venues and real-world production systems. Essential for improving manuscript eligibility and impact.

A comprehensive guide detailing how to structure the 'Related Work' section for submissions to top data mining conferences like ICDM. It emphasizes positioning the research based on core mechanisms and mining tasks, rather than simply listing results. The guide also provides critical advice on maintaining triple-blind anonymity, verifying citation venues (avoiding misattribution traps), and ensuring the novelty claim is distilled into a single, quotable mechanism-contrast sentence.

Provides strict guidelines for writing the Related Work section in theoretical database papers. It teaches authors how to precisely position their novel results against existing theorems (ICDT/PODS canon), covering complex topics like finite model theory, query complexity, and proper academic citation etiquette, ensuring genuine novelty is highlighted.

This skill guides authors submitting work related to Operations Research (OR). It helps assess whether a manuscript provides a genuine theoretical or methodological advance in fields like optimization, stochastic processes, queueing theory, and mathematical modeling. It emphasizes the necessity of rigorous proofs, mathematical depth, and positioning the contribution against existing OR literature, rather than merely presenting a case study application.

This guide directs authors on how to structure the related work section for academic papers in database theory (e.g., for venues like PODS, ICDT). It emphasizes a 'delta-first' approach, requiring authors to compare their specific *results* (theorems, bounds, dichotomies) directly against the nearest prior *results*, rather than simply cataloging related citations. It also covers complex rules regarding self-citation, anonymity, and overlap declaration with concurrent or prior-version work.