「generate」の検索結果

Turn a real document (PDF, PPTX, DOCX, Keynote export, slide deck, proposal, whitepaper, report) into a finished AI-generated video using the Ozor MCP. Use this skill whenever the user attaches, uploads, references, or points to a document file and wants a video from it — e.g. 'make a video from this pitch deck', 'turn this PDF into a video', 'video from my proposal.docx', 'generate a video from this PowerPoint', 'create a video from this report', 'this whitepaper → video'. This skill runs the document-to-video pipeline: analyze_document → present the plan to the user → update_plan if needed → generate_from_plan → export_video → wait_for_export → get_embed_code. It always uses the plan-based flow so slide visuals are preserved. Do NOT use this skill for plain-text creative briefs (use ozor-generate) or for URLs/landing pages (use ozor-url-to-video).

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。

Generate release notes from merged PR history and commits. Categorizes changes by type and creates GitHub releases with semantic versioning. Use when the user asks to create a release or generate release notes (e.g., "リリースノート", "release note", "リリース作成"). Do NOT use for changelogs, commit summaries, or PR descriptions.

Using Bogus to generate realistic fake data specialized skill. Used when generating realistic names, addresses, phone numbers, emails, company info and other test data. Covers Faker class, multi-language support, custom rules, bulk data generation, etc. Keywords: bogus, faker, fake data, fake data, realistic data, realistic data, fake name, fake address, fake email, Faker<T>, RuleFor, Generate, faker.Name, faker.Address, faker.Internet, generate fake data, generate fake data, seed data

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。

Using AutoFixture to automatically generate test data basic skill. Used when quickly generating test objects, reducing boilerplate code, and implementing anonymous testing. Covers Fixture.Create, CreateMany, circular reference handling, and xUnit integration. Keywords: autofixture, fixture, auto-generate test data, test data generation, anonymous testing, anonymous testing, fixture.Create, CreateMany, fixture.Build, Create<T>, AutoFixture.Xunit2, OmitOnRecursionBehavior, IFixture, generate test data, generate test data

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。

ジョークの題材に合うミームのテンプレートを探し、文字入り画像の下書きを作るスキル。ローカルのSVG・PNG出力やImgflipでのURL発行に対応します。

• ジョークに合うミーム形式を選びたいとき
• 名前や話題からテンプレートを探す
• 文字入りSVG・PNGの下書き作成

AIエージェントが実装の多くを担う開発チーム向けに、計画、責任分担、レビュー基準、テスト要件を整理し、生成コードを扱う開発プロセスを設計するスキル。

• AI生成コードを扱う開発ルールの整備
• コードレビュー基準と承認条件の設定
• エージェントが作業しやすい設計の検討

製品やブランドの特徴をもとに、32×32でも見分けやすい、丸くシンプルなマスコット画像を設計・生成するスキル。モチーフや配色の異なる候補を並べて比較できます。

• アプリや製品のマスコット作成
• ブランドに合うキャラクター案の検討
• マスコットの配色や輪郭の比較

記事の内容を分析し、図解や挿絵を入れる位置を提案します。図の種類・画風・配色をそろえて画像を生成し、生成用の指示文を保存して本文へ挿入するスキルです。

• 技術記事に説明図を加えたいとき
• チュートリアルの手順を図解したいとき
• 記事内の挿絵の見た目を統一したいとき

Generate images using AI. Use when asked to generate, create, or make images, textures, icons, sprites, artwork, visual assets, or mockups. Supports OpenAI (gpt-image-2) and Google Gemini (Nano Banana). Requires an API key for the chosen provider.

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。

Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.

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。

Generate Playwright tests. Use when user says "write tests", "generate tests", "add tests for", "test this component", "e2e test", "create test for", "test this page", or "test this feature".

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。

Generates professional slide deck images from content. Creates outlines with style instructions, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", "slide deck", or "PPT".

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。

Generate sandbox security policies from plain-language requirements and optional REST API documentation. Produces L4 or fine-grained L7 network policies and ordered network middleware configuration. Use for API access rules, middleware host selection, failure behavior, or built-in and operator-run middleware attachment. Trigger keywords - generate policy, create policy, update policy, change policy, sandbox policy, network policy, API policy, security policy, allow API, restrict API, network middleware, supervisor middleware.

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。

CLI tool for creating, managing, and exporting AI-generated presentations via the Banana Slides API. Use when the user asks to: (1) generate a PPT/presentation/slides from an idea, outline, or description, (2) export a project to PPTX, PDF, or images, (3) batch-generate multiple presentations, (4) manage projects, pages, materials, or templates programmatically, (5) renovate/redesign an existing PPT or PDF, (6) edit slide images with natural language.

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。

Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.

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。

Generate new screens from text prompts or images, edit existing screens with prompts and design system tokens, and generate design variants using Stitch MCP. Includes prompt enhancement pipeline, design mappings, professional UI/UX terminology, design tokens and theme system capabilities.

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。

When the user wants to create UGC ad campaigns, recruit UGC creators, generate AI UGC content, or scale with user-generated content. Also use when the user mentions 'UGC,' 'user-generated content,' 'creator ads,' 'Spark Ads,' 'whitelisting,' 'AI UGC,' 'Arcads,' 'Creatify,' 'creator brief,' or 'UGC testing.' This skill covers the UGC growth framework from creator recruitment through AI-powered scaling. Do NOT use for technical implementation, code review, or software architecture.

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。

Generate multiple original brand campaign worlds from a supplied visual reference while controlling how close the new work feels without copying protected signature elements. Use when a user provides a brand identity image, poster, editorial campaign, moodboard, or generated concept and asks for inspired alternatives, several distinct brands in one visual family, a closer-to-reference V2, exact wordmarks inside images, or originality-safe image-generation prompts and outputs.

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。

Generate, preview, save, or validate Preline theme CSS using the bundled local generator in this skill. Use when the user asks to create a new Preline theme, match a brand color, translate a mood into a theme, generate light and dark theme CSS, preview theme output without writing files, or review and fix generated theme tokens. Do not use for generic non-Preline CSS work or arbitrary command execution.

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。

Own concrete MSBuild ItemGroup and item-expression questions. USE FOR: Include, Remove, Update, item identity and metadata, transforms, filtering, batching, duplicate or overlapping items, and reviews that verify whether those operations are correct. Generated items stay in scope when the central defect is item identity, metadata, batching, duplicate declarations, or glob/Remove/Update semantics. For a generated artifact missing from compilation or output, wrong target timing/path, or FileWrites clean tracking without a broader item-semantics defect, use including-generated-files. The item operation may be broken, suspected, or already correct. Exclude property-only issues, general incrementality with no item question, broad reviews with no concrete item concern, and non-MSBuild systems.

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。

Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).

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。

Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.

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。

Generate professional slide deck images from academic papers and content. Creates comprehensive outlines with style instructions, auto-detects figures from PDFs, then generates individual slide images. Use when user asks to "create slides", "make a presentation", "generate deck", or "slide deck" for papers.

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。

Explicit-only last resort. Draws game art from code, with no image model - pixel sprites from a PixelSpec, flat vector props, UI and icons from portable SVG, rigged characters with planted feet, FX with a JS runtime, seam-proven autotiles, playable top-down layouts with collision, stylized parallax and ambient plate motion - palette-exact, with QA and review sheets. Use only when the user explicitly asks for code-drawn art, or when generate2dmedia route_media.py finds no image or video route (no-route, exit 3). Never the default - image generation (generate2dsprite, generate2dmap, video2dsprite) comes first for characters, props, maps and FX. Not for painterly, detailed or likeness art, HD-2D plates or realistic fire, smoke or water. Always disclose the result as code-drawn.

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。