Skill UI

A comprehensive mentor guiding users through the entire lifecycle of academic literature reviews. It teaches systematic search strategies (PICO/PCC), critical appraisal methods, and advanced synthesis techniques. The skill covers searching major English and Chinese databases (e.g., PubMed, Web of Science, CNKI), organizing findings, and effectively utilizing AI research tools like Elicit and Semantic Scholar to build robust, evidence-based research papers.

This skill guides the systematic gathering and structuring of literature for comprehensive academic reviews, such as an Annual Review of Psychology (ARPsych). It ensures broad coverage by executing traceable searches (database sweeps, citation chasing) and building a detailed evidence matrix (one row per finding). This establishes a robust, documented base of evidence, allowing the user to focus their analytical contribution later without sacrificing completeness.

A comprehensive guide detailing the multi-cycle, rolling model for EDBT research submissions. It covers the entire review pipeline, from initial program committee evaluation and author-feedback exchange, through the accept/revise/reject decision, and critically, the in-cycle revise-and-resubmit stage. The guide also contrasts EDBT's open-access, three-cycle cadence with other top-tier database conferences (e.g., SIGMOD, VLDB).

This process verifies if a specific legal argument has been published previously by searching major academic databases, including SSRN, Westlaw, HeinOnline, and Google Scholar. It is a critical step for legal scholars to confirm originality, sharpen the claim, and refine the contribution before drafting a full paper, thereby preventing wasted effort and strengthening the scholarly impact.

A rigorous guide detailing the advanced writing standards required for top-tier database theoretical papers (e.g., ACM PODS). It emphasizes precision in defining models, stating theorems, matching upper and lower bounds, and structuring the narrative to ensure mathematical completeness and verifiability for peer review.

This guide provides an in-depth breakdown of the academic research paper review cycle, using top-tier database conferences (like SIGMOD) as a case study. It covers the double-anonymous review process, the author feedback phase, interpreting the Accept/Reject/Revise verdicts, and navigating the post-decision revision window and embargo rules. Essential knowledge for authors preparing submissions to top-tier conference proceedings.

This skill guides legal scholars through a systematic preemption check to ensure their academic claim is genuinely novel and not covered by prior work. It simulates comprehensive searches across specialized databases like SSRN, Westlaw, HeinOnline, and Google Scholar. The process helps users accurately draft the critical "what's new" contribution paragraph by classifying the relationship between their claim and existing scholarship.

This skill establishes a rigorous, verification-first methodology for citing jurisprudence from the ICTY, ICTR, and IRMCT. It mandates multi-level checks (existence, content, paragraph) against authoritative databases (irmct.org, UCR) and sources to ensure legal claims are accurate and non-misrepresentative. It guides users through a structured workflow for high-stakes legal research.

Builds data-and-code replication packages for Management World (《管理世界》) after conditional acceptance. Generates Chinese READMEs, audits deposits, handles restricted commercial databases (CSMAR/Wind) and government micro-data, ensuring one-pass editorial reproducibility checks.

A comprehensive skill that applies the two-step test (Concept of Work + Originality) derived from CJEU case law to determine if various types of subject matter (e.g., software, databases, photography, art) qualify for copyright protection under European Union law. It facilitates structured, dual-position argumentation (pro-rightsholder or pro-alleged-infringer) for legal analysis.