497 件 ・ 関連度順
概要と使いどころ
Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.
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。
Three-round editorial review before publication.
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。
Project-first Research pipeline with live gates, source/PDF evidence, claim boundaries, compute and publication controls; includes an optional PubMed/arXiv standard-library helper.
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。
Apply a scholarly 'nerd' visual style to single-file handwritten HTML document sites: publication-list look, restrained typography, no frameworks. Use when building or reviewing a lab site, a publications page or any new page that should match this house style. Triggers: /scholar-nerd-style, /nerd, nerd style, scholar style, build a page in our style, check page style.
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。
View publication history for catalog resources — who changed what and when. Use when investigating timeline of changes, finding who modified a connector, or correlating changes across capture/collection/materialization chains. Use when user says "what changed", "who changed", "publication history", "catalog history", "when was it published", "timeline of changes", or "what happened to my connector".
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。
Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.
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。
Publication-quality physics plots — vector fields, streamlines, contour maps, 3D surfaces, phase space, spectrograms, and animations. Optimized for journal submission with LaTeX labels, proper colormaps, and multi-panel layouts.
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。
Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.
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。
Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (Type-42) font embedding for journal submission, and CVD-safe palettes. Covers seaborn integration, common chart types, axis formatting, and the small gotchas that distinguish reproducible matplotlib from notebook scratch. Use when producing publication figures in Python — RNA-seq scatter, single-cell embeddings, generic biological plotting.
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。
Build publication-quality figures in R with ggplot2 using the grammar of graphics (data + aesthetics + geometries + scales + facets + themes) with CVD-safe palettes, cairo_pdf TrueType embedding, programmatic aes via tidy evaluation, and the theme_classic publication baseline. Use when producing static figures in R for papers, presentations, or reports.
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。
Build publication-quality figures with matplotlib using the object-oriented Figure/Axes API, constrained_layout, rcParams customization, TrueType (Type-42) font embedding for journal submission, and CVD-safe palettes. Covers seaborn integration, common chart types, axis formatting, and the small gotchas that distinguish reproducible matplotlib from notebook scratch. Use when producing publication figures in Python — RNA-seq scatter, single-cell embeddings, generic biological plotting.
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。
OpenClawのmacOS安定版リリースで、署名、Appleの公証、配布ファイルと更新情報の公開を進めます。事前検証や失敗した処理の再開、公開後の確認も扱います。
AIエージェントの作業ログから、GitHubのPRやissueに添える記録を作ります。関連部分を絞り、機密情報を除いてプレビューと掲載を扱います。
公開前の文章やコードを二つの独立したエージェントが同じ基準で審査し、両方の合格まで修正と再審査を繰り返し、上限を超えたら人へ判断を引き継ぐスキル。
Turn any markdown file into a publication-quality PDF. (gstack)
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。
Handle confidential GitHub Security Advisory response for Paperclip. Use when coordinating advisory triage, private-fork fixes, CVE/publication steps, and immediate security releases.
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 this skill when the user requests to review, analyze, critique, or summarize academic papers, research articles, preprints, or scientific publications. Supports comprehensive structured reviews covering methodology assessment, contribution evaluation, literature positioning, and constructive feedback generation. Trigger on queries involving paper URLs, uploaded PDFs, arXiv links, or requests like "review this paper", "analyze this research", "summarize this study", or "write a peer 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。
Review and edit OpenAI Cookbook notebooks, Markdown, and MDX for technical accuracy, clarity, grammar, consistency, runnable examples, and repository publication requirements. Use for editorial reviews, pre-merge documentation checks, or notebook Markdown-cell sweeps in openai-cookbook.
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 provides a Facebook URL or asks to read personal posts, comments, reactions, friends, timelines, profiles, stories, feeds, groups, events, or saved items, or to discover public events happening near a place, nearby, or in a local area on a date, or to create, edit, publish, or delete their own Marketplace listings. To find, browse, or buy Marketplace listings, use shopping instead. Use pages commands for managed Facebook Page discovery, insights, native draft editing/deletion, same-draft publication, approved posts and native scheduling.
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 prepare or verify a Twenty app for npm or marketplace publication, including README/About copy, package metadata, defineApplication marketplace metadata, logos, screenshots, and public assets.
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。
Orchestrator for the full academic research pipeline: research -> write -> integrity check -> review -> revise -> re-review -> re-revise -> final integrity check -> finalize. Coordinates deep-research, academic-paper, and academic-paper-reviewer into a seamless 10-stage workflow with mandatory, coverage-bounded integrity checks, two-stage peer review, and auditable quality-assurance artifacts. Triggers on: academic pipeline, research to paper, full paper workflow, paper pipeline, end-to-end paper, research-to-publication, complete paper workflow, 연구부터 논문까지, 연구 주제 설정부터 논문 완성까지, 논문 전체 워크플로, flujo de trabajo académico, investigación a artículo, flujo completo de artículo, pipeline de investigación completa, publicación de investigación, flujo de trabajo completo del artículo.
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。
Creates Seaborn statistical visualizations with pandas integration for distributions, relationships, categorical comparisons, regression displays, pair plots, and heatmaps. Supports function and objects interfaces with explicit aggregation, uncertainty, and missing-data handling. Best suited to static exploratory plots; plotly covers interactive figures and scientific-visualization covers publication styling.
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。
Creates and audits truthful, accessible, publication-ready scientific figures with Matplotlib, Seaborn, or Plotly. Use it for figure design, multi-panel layouts, uncertainty and missing-data displays, color/contrast review, image metadata validation, and journal export planning.
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。
Performs pathway and gene-set enrichment analysis on gene lists or ranked gene data and interprets the results. Used when the user has a set of genes (differentially expressed genes from PyDESeq2/Scanpy, CRISPR-screen hits, cluster marker genes, proteomics hits) and wants to know which biological pathways, GO terms, or gene sets are over-represented or enriched. Covers over-representation analysis (ORA / Enrichr / Fisher / hypergeometric), ranked Gene Set Enrichment Analysis (GSEA / preranked), single-sample scoring (ssGSEA/GSVA), and functional profiling via gseapy, g:Profiler, Enrichr libraries, MSigDB, GO, KEGG, Reactome, and WikiPathways — plus gene-ID mapping, choosing the right background universe, multiple-testing correction, redundancy reduction, dotplots/enrichment maps, and publication-ready tables. Use this for "pathway analysis", "enrichment analysis", "GO enrichment", "KEGG/Reactome pathways", "GSEA", "over-representation", "functional annotation", or "what pathways are my genes in".
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。