「language」の検索結果

Generate specialized skills for each subsystem in the monorepo. Creates shared language skills and subsystem-specific checklists for high-quality AI code generation.

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。

Anime/illustration text-to-image (ANIMA 1.0, ~2B Cosmos DiT). Use for anime, manga, illustrated characters; accepts Danbooru tags + natural language; runs/trains on <6GB VRAM; includes anime inpainting via Anima-LLLite ControlNet

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 implementing shaders — Godot shader language, visual shaders, common visual recipes, and post-processing effects

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。

Grilling session that challenges your plan against the existing domain model, sharpens terminology, and updates documentation (CONTEXT.md, ADRs) inline as decisions crystallise. Use when user wants to stress-test a plan against their project's language and documented 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。

Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.

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。

Interactive QA session where user reports bugs or issues conversationally, and the agent files GitHub issues. Explores the codebase in the background for context and domain language. Use when user wants to report bugs, do QA, file issues conversationally, or mentions "QA session".

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。

Core ML, Create ML, Vision framework, Natural Language framework, on-device ML integration. Use when user wants image classification, text analysis, object detection, sound classification, model optimization, or custom model integration. Covers Core ML vs Foundation Models decision.

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。

Design skills for Apple platform UI — Liquid Glass, animations, game feel (haptics, sound, celebrations), UI prototyping, UX writing, SF Symbols, and typography. Use when implementing design language features, adding juice/feedback, writing interface copy, or choosing type and iconography.

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。

Optimize app title, subtitle, and keywords for maximum App Store discoverability. Use when launching a new app, improving search rankings, entering new markets/languages, or safely optimizing ASO for an app with existing traffic.

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。

The ORFhunteR package is a R and C++ library for an automatic determination and annotation of open reading frames (ORF) in a large set of RNA molecules. It efficiently implements the machine learning model based on vectorization of nucleotide sequences and the random forest classification algorithm. The ORFhunteR package consists of a set of functions written in the R language in conjunction with C++. The efficiency of the package was confirmed by the examples of the analysis of RNA molecules fr

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。

Provides large-scale single-cell omics data manipulation using Genomic Data Structure (GDS) files. It combines dense and sparse matrices stored in GDS files and the Bioconductor infrastructure framework (SingleCellExperiment and DelayedArray) to provide out-of-memory data storage and large-scale manipulation using the R programming 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。

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。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

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。

Turn a repo, product page, or update into a recording-ready video script in a receipts-first format - verifies every claim against live sources, then writes timestamped VO + on-screen direction with a plain-language glossary, assets checklist, anti-tells, and a verify-before-recording list

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。

Find lookalike companies via DiscoLike's 65M+ business domain database. Search by seed domains ("find companies like clay.com and apollo.io") or natural-language ICP text ("B2B cold email outreach"). Supports negation domains (exclude competitors/existing customers) and country filtering. Use when you already know 3-10 reference companies and want hundreds more that look like them. Outputs CSV ready for /blitz-list-builder or the email waterfall.

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。

Expand a 1-4 sentence product brief into a full spec with a design language, acceptance surface, and an ordered feature list.

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 a brand's messaging hierarchy — taglines, value propositions, key messages, and proof points for each audience. Use when the user says "brand messaging", "messaging framework", "value proposition", "tagline", "brand tagline", "key messages", "messaging hierarchy", "what should we say about our brand", "brand copy foundation", "messaging architecture", "elevator pitch", "one-liner", "brand statement", or needs consistent language across all communications. Also use when messaging feels inconsistent across channels or teams.

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。

Define a brand's verbal identity — tone, voice, writing style, vocabulary, and messaging rules. Use when the user says "brand voice", "tone of voice", "how should we write", "writing guidelines", "copy style guide", "brand language", "verbal identity", "how should the brand sound", "tone guide", "our copy doesn't sound right", "copywriter guidelines", "voice and tone", or when onboarding a copywriter or content team. Also use when the user has a brand strategy and wants to define how the brand communicates.

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 a visual identity brief for a brand — logo direction, color palette, typography, imagery style, and design system foundations. Use when the user says "visual identity", "brand identity", "logo brief", "logo direction", "design brief", "brand design", "color palette for my brand", "typography for my brand", "visual language", "design system", "brand look and feel", "what should my brand look like", or is briefing a designer or design agency. Also use when the user has a brand strategy and wants to translate it into visual design direction.

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。

Rewrites scene descriptions using professional cinematography language, structures prompts with a six-slot formula (camera + subject + action + setting + style + lighting), and diagnoses content filter rejections via a preflight linter. Use whenever the user asks for a Seedance 2.0 / Seedance Pro prompt, describes a scene for Seedance generation, mentions Seedance, reports a Seedance generation failure or flagged prompt, or is burning credits on Seedance regenerations.

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 working on accessibility, a11y, WCAG, ARIA, screen readers, keyboard nav, focus order, contrast, alt text, captions, reduced motion, or target sizes; not language/culture/device (see inclusive-design).

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。

Test directory structure patterns by architecture style, language conventions, naming rules, and fixture placement. Decision tree for selecting test organization strategy.

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。

Definition of Ready checklist criteria, antipattern detection patterns, UAT quality rules, and domain language enforcement for product owner 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。

F# language-specific patterns, Railway-Oriented Programming, and Computation Expressions

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。