562 件 ・ 関連度順
概要と使いどころ
Create, revise, and format thesis or dissertation Word documents with strict academic formatting control. Use when an AI agent needs to generate or revise thesis content, normalize Word styles, follow a school template, fix captions or page numbers or section levels, or produce evidence-based Mermaid figures and LaTeX-formatted code listings for a thesis document.
日本語の概要は準備中です。原文の説明を表示しています。
Systematic academic paper review workflow covering self-review before submission and rebuttal writing after receiving reviewer feedback. Triggers on "review paper", "self-review", "write rebuttal", "respond to reviewers", "analyze review comments", "paper review".
日本語の概要は準備中です。原文の説明を表示しています。
Enhanced academic paper review response workflow with Agy/CLI collaborative analysis and multi-perspective discussion. Produces structured rebuttal documents with evidence-based strategies. Triggers on "rebuttal", "respond to reviewers", "review response", "审稿回复".
日本語の概要は準備中です。原文の説明を表示しています。
Four-layer citation verification for academic papers. Scans LaTeX/BibTeX files, verifies every citation via WebSearch and Google Scholar, generates verification report with fix suggestions. Triggers on "verify citations", "check references", "citation verification", "prevent fake citations", "引用验证".
日本語の概要は準備中です。原文の説明を表示しています。
Remove AI writing patterns from academic prose. Detects and fixes inflated symbolism, promotional language, superficial analyses, vague attributions, AI vocabulary, and formulaic structures. Supports English and Chinese. Triggers on "remove AI patterns", "humanize text", "anti-AI polish", "去除AI写作痕迹", "人性化处理".
日本語の概要は準備中です。原文の説明を表示しています。
Agents should invoke this skill for academic or technical papers, arXiv/PubMed/IEEE/ACM links, PDFs, methodology review, limitations, practical implications, or extracting findings for engineering decisions.
日本語の概要は準備中です。原文の説明を表示しています。
Map paper notes + taxonomy into a signal table of tensions, missing pieces, and promising academic axes for brainstorm discussion. Writes `output/trace/IDEA_SIGNAL_TABLE.md`.
日本語の概要は準備中です。原文の説明を表示しています。
Read a real .pptx using text extraction, OOXML inspection, slide rendering, OCR, visual inventory, and vision-capable screenshot review; then write academic speaker notes grounded in every visible slide element, generate a complete display-version document, and inject clean notes into the PowerPoint notes pane. Use when the user wants speaker notes, presenter notes, a speech script, narration, or annotated notes for an existing PowerPoint deck, especially when slides contain images, charts, tables, SmartArt, axes, legends, or screenshot text.
日本語の概要は準備中です。原文の説明を表示しています。
Help with humanities scholarly writing: sharpen research questions, map supplied readings, plan and draft arguments, review chapters, preserve authorial voice, and respond to reviewers. Use for history, philosophy, literature, and related argumentative scholarship, including 论文、改论文、文献综述、审稿意见、我手写我口, or “review this paragraph” when an academic draft is in context. Not for unrelated copywriting or a standalone literature-search pipeline.
日本語の概要は準備中です。原文の説明を表示しています。
Качество русского текста для агента. Russian text quality for agents: proofreading and AI-slop cleanup for Cyrillic text. Триггеры: очеловечь, вычитай, отредактируй, поправь, причеши, проверь текст, убери канцелярит, humanizer. Молча снимает жёсткие запреты в собственном русском выводе агента; чужой текст молча не трогает. Use when надо убрать из русского текста канцелярит, воду и нейросетевую манеру, не сломав смысл, факты и голос автора. Три режима по запросу: редактура, аудит без переписывания, точечная правка одной категории. Со скиллом едет детерминированный сканер scripts/scan.py: считает хард-баны, категории маркеров, ритм и морфологию, печатает ЧИСТОТА: N/100, поэтому правка измерима («было N, стало M»). Флаг --genre academic/legal/fiction/news снимает маркеры, законные для научного, юридического и новостного регистра. Работает ТОЛЬКО с русским: для английского humanizer, для итальянского humanizer-it. НЕ используй для: перевод, написание с нуля, грамматика без стилистики, код.
日本語の概要は準備中です。原文の説明を表示しています。
Conduct comprehensive deep research on any topic using Dify-powered workflow - searches documentation, academic papers, tutorials, APIs, best practices, and returns structured analysis with insights.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user wants to write, structure, or revise academic paper sections, improve notation consistency, or refine figures and tables. Triggers on phrases like "write the abstract", "structure the methods", "improve this section", "notation consistency", "figure refinement", or "paper structure".
日本語の概要は準備中です。原文の説明を表示しています。
Scholarly writing and research compliance. Use for CRediT, preregistration, Plan S, Nelson Memo, preprints, ORCID, LLM disclosure.
日本語の概要は準備中です。原文の説明を表示しています。
Legal methods for paywalled and geo-blocked content. Use for paywalls, academic papers, or open access via Unpaywall.
日本語の概要は準備中です。原文の説明を表示しています。
Web accessibility patterns for news and academic sites. Use for WCAG audits, alt text, accessible data viz, and assistive tech.
日本語の概要は準備中です。原文の説明を表示しています。
KEGG REST API (academic only). Pathways, genes, compounds, enzymes, diseases, drugs via 7 ops (info/list/find/get/conv/link/ddi). ID conversion (NCBI/UniProt/PubChem). Use bioservices for multi-DB Python.
日本語の概要は準備中です。原文の説明を表示しています。
BRENDA Enzyme DB SOAP/REST queries: kinetic parameters (Km, Vmax, kcat, Ki), EC classes, substrate specificity, inhibitors, cofactors, organism data. 80K+ enzymes, 7M+ values. Free academic registration. For metabolic modeling use cobrapy-metabolic-modeling; metabolites use hmdb-database.
日本語の概要は準備中です。原文の説明を表示しています。
Identify EMERGING trends by connecting dots across unrelated sources. Monitor niche communities, academic research, GitHub, patents, funding, regulatory changes. Predict what will trend in 3-6 months based on weak signals.
日本語の概要は準備中です。原文の説明を表示しています。
Use when a medical AI paper should be found and cited by AI search engines and RAG tools. Optimizes the title, abstract, summary box (Key Points, Research in Context), keywords, preprint, GitHub README/CITATION.cff and Hugging Face card, returning a visible pass/fail checklist.
日本語の概要は準備中です。原文の説明を表示しています。
Use when preparing an academic talk such as a journal club, grand rounds, seminar, conference presentation, or lecture/teaching deck. Analyzes the source, drafts audience-adapted speaker scripts, builds or augments the PPTX with speaker notes and prepares Q&A.
日本語の概要は準備中です。原文の説明を表示しています。
Use the DeepXiv SDK for citation-aware academic and web research through its Python Reader, deepxiv CLI, progressive paper APIs, optional local LangGraph agent, PMC, bioRxiv/medRxiv, and trending workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Create, edit, replicate, import, and export draw.io diagrams with an offline YAML-first workflow: architecture, network topologies, flowcharts, UML/ER, org charts, Mermaid/CSV conversion, existing .drawio bundles, style presets, themes, and non-publication formula diagrams. For publication figures (paper, thesis, IEEE, camera-ready) use drawio-academic-skills instead.
日本語の概要は準備中です。原文の説明を表示しています。
Identify EMERGING trends by connecting dots across unrelated sources. Monitor niche communities, academic research, GitHub, patents, funding, regulatory changes. Predict what will trend in 3-6 months based on weak signals.
日本語の概要は準備中です。原文の説明を表示しています。
Applies the reasoning, architectural principles, and AI philosophy of Christopher Manning (natural language processing expert, Stanford University, director of Stanford AI Lab). Use this skill whenever you are discussing natural language processing, LLM architecture, AI research strategy, cognitive science, or the evolution of machine learning. Trigger this skill for questions about AGI timelines, academic vs. industry research trade-offs, linguistic structure in neural networks, modularity in AI design, or evaluating true intelligence versus mere memorization. Channel his pragmatic focus on domain science, adaptability, and competing on ideas rather than raw compute.
日本語の概要は準備中です。原文の説明を表示しています。