Results for “literature-review”

Guide users through writing a systematic literature review (SLR) following the PRISMA 2020 framework. Use this skill whenever the user mentions 'systematic review', 'systematic literature review', 'SLR', 'PRISMA', 'PRISMA 2020', 'PRISMA flow diagram', 'PRISMA checklist', or asks for help writing, structuring, or auditing a literature review that follows reporting guidelines. Also trigger when the user asks about inclusion/exclusion criteria for a review, search strategies for databases like Scopus/WoS/PubMed, study selection processes, risk of bias assessment, or narrative synthesis for a review paper. This skill covers the full PRISMA 2020 checklist (27 items), produces a Word document manuscript in strict journal article format, generates an annotated PRISMA flow diagram, and enforces APA 7th Edition referencing throughout. It does NOT cover meta-analysis or statistical pooling. By Chuah Kee Man.

Evaluate scientific manuscripts and grant proposals with structured, checklist-based peer review covering methodology, statistics, reproducibility, ethics, and reporting standards.

Reviews an academic paper using the NeurIPS review form with three reviewer personas, ensemble scoring, and reflection refinement. Extracts text from PDF, runs structured review, and outputs actionable feedback.

Multi-perspective academic paper review with dynamic reviewer personas. Simulates 5 independent reviewers (EIC + 3 peer reviewers + Devil's Advocate) with field-specific expertise. Supports full review, re-review (verification), quick assessment, methodology focus, Socratic guided, and calibration modes. Triggers on: review paper, peer review, manuscript review, referee report, review my paper, critique paper, simulate review, editorial review, calibrate reviewer, reviewer calibration, measure reviewer accuracy.

Correct grammar errors, typos, and improve academic readability in LaTeX, Markdown, or plain-text manuscripts. Scans the document once, then walks through every issue one-by-one asking for approval before applying each fix. Trigger when the user says "readability", "check grammar", "fix typos", "proofread for grammar", "improve readability", "polish wording", "语言润色", "修语法", or asks you to clean up the prose in a paper/chapter/section without wanting full content restructuring.

Transforms uploaded course materials into exam-oriented study notes, practice questions, and scoring-focused explanations.

Simulates a complete international journal peer review process with 5 dynamically configured reviewers, producing structured editorial decisions and revision roadmaps.

基于论文文本的通用读论文助手。用户提供论文文本（文件路径或直接粘贴），解答各类读论文需求——总结、精读、内容问答、概念解释、批判性分析等，并将结果以 Markdown 写入当前工作目录。触发词：读论文、论文总结、精读这篇论文、帮我分析这篇论文、这篇论文讲了什么、论文问答、论文笔记。输入为纯文本/Markdown 论文内容；不做论文检索下载、不做扫描件 OCR、不做论文写作降重。

Revise an academic paper based on internal review comments. Reads review report or annotated manuscript, then applies revisions one by one with user approval. Trigger when user says "self revise" / "paper-selfrevise" / "内部修改" / "根据审稿意见修改".

专业学术论文审稿 skill。以领域专家视角对学术论文（本地 PDF、arXiv ID/URL、粘贴文本）进行系统评审，自动识别论文学科与贡献类型并切换对应领域专家标准，输出顶会 OpenReview 风格（NeurIPS/ICLR/ICML）的标准 review 意见：Summary、Strengths、Weaknesses、Questions to Authors、Overall Score (1-10)、Confidence。输出语言跟随论文语言。触发场景包括：审论文、审稿、论文评审、review this paper、peer review、写评审意见、帮我看看这篇论文能不能中、rebuttal 前自查等。

Look up current research and scientific information across three backends: fast web search, deep multi-source synthesis, and scholarly paper searches. Automatically routes each query to the best backend and saves every result for reproducible citation.

Remove signs of AI-generated writing from academic medical papers. Use when editing or reviewing manuscripts to make them sound more natural and professionally written. Based on Wikipedia's "Signs of AI writing" guide, adapted for medical literature. Detects and fixes patterns including: inflated significance claims, superficial -ing analyses, vague attributions, AI vocabulary words, copula avoidance, excessive hedging, generic conclusions, informal word choices (linked/beyond/via/where/yield), overly assertive causal claims, and artificially condensed expressions. Preserves legitimate academic transitions (Notably, Prior studies have shown, etc.).