「screenshot」の検索結果

Browser automation CLI for agents: navigate, click/fill, screenshot, extract data, test apps, Electron/Slack, cloud browsers. NOT for the user's real Chrome profile/cookies (mk:chrome-profile).

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 designing UI components, reviewing visual design, building design systems, or checking accessibility. Auto-activates on frontend design tasks and UI reviews.

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。

Full Jira ticket context analysis via the jira-analyst agent — including media (attached images / PDFs / screenshots) and linked issues. Produces structured findings suitable for posting back as a Jira comment. Read-only. Triggers: 'analyze KEY', 'rca for KEY', 'describe KEY with media'. NOT for complexity scoring (mk:jira-evaluator); NOT for story-point estimation (mk:jira-estimator).

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。

Browser automation CLI for AI agents using agent-browser. Use for navigating websites, clicking/filling pages, screenshots, data extraction, web app testing, exploratory QA, dogfooding, Electron apps, Slack automation, Vercel Sandbox browser runs, AWS AgentCore cloud browsers, auth-heavy flows, and long autonomous browser sessions. Prefer over generic browser tools when a fresh/tool-managed Chrome session is fine. NOT for the user's real Chrome cookies/profile (see mk:chrome-profile); NOT for reusable Playwright specs (see mk:qa-manual).

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-first Figma gateway via Figma MCP: analyze designs, implement Figma-to-code for 1–3 screens, extract design tokens, produce a Figma Evidence Packet for planning handoff, screenshot fallback. Advanced operations (Code Connect, canvas writes, design-system/library patterns) are gated references loaded only on explicit intent. Triggers: 'figma', 'design link', 'implement this design', 'design tokens', 'produce a Figma Evidence Packet'.

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 aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.

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。

Browser automation, debugging, and performance analysis using Puppeteer CLI scripts. Use for automating browsers, taking screenshots, analyzing performance, monitoring network traffic, web scraping, form automation, and JavaScript debugging.

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 live website into a working local frontend you can edit. Fetches the page, extracts its design system and structure, and rebuilds it locally in your stack, then screenshot-compares to the original. Use when the user says "url to code", "clone this site locally", "make it look like linear.app", "rebuild this page", or provides a live URL to recreate. Part of the Product Design set. Uses web-fetch + browser automation.

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。

Audit an existing UI for usability, hierarchy, accessibility, and conversion problems. Reviews a live URL, screenshot, or codebase against heuristics and reports prioritized issues with fixes. Use when the user says "audit this UI", "what's wrong with this screen", "UX review", "find the problems", "why is this confusing", or has existing interface to critique. Part of the Product Design set. Can drive a browser for live audits.

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 genome-browser-style multi-track figures with pyGenomeTracks (config-driven), Gviz (R), and IGV batch screenshotting. Covers BigWig coverage tracks, BED/peak overlays, gene-model rendering, Hi-C matrix tracks, BedPE link arcs, spike-in-aware normalization, and the bamCoverage --normalizeUsing trap. Use when producing publication figures of genomic loci with stacked aligned tracks (coverage, peaks, genes, interactions) for ChIP-seq, ATAC-seq, RNA-seq, Hi-C, or generic locus visualization.

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。

Visualizes ChIP-seq data using deepTools (computeMatrix, plotHeatmap, plotProfile, bamCoverage, bamCompare), pyGenomeTracks (modern INI-driven track plots), Gviz (R browser-style), EnrichedHeatmap (ComplexHeatmap-based), ChIPseeker tag heatmaps, and IGV batch screenshots. Handles bigWig normalization choices (CPM, BPM, RPGC, spike-in scaled), bamCompare operations (log2 ratio, subtract) with SES scaling, k-means clustering of heatmaps for biological subgrouping, and spike-in-scaled tracks for global-shift experiments. Use when generating publication-quality ChIP-seq signal heatmaps, profile plots, genome-browser tracks, or comparing samples visually.

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。

Browse the web for any task — research topics, read articles, interact with web apps, fill forms, take screenshots, extract data, and test web pages. Use whenever a browser would be useful, not just when the user explicitly asks.

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。

Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.

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。

Save a site or section as local files (markdown, screenshots). Use for "download the site", offline docs, or a local copy for reference.

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。

Capture baseline evidence from a live website URL: screenshots, scroll states, hover/click behavior, parallax, timers, and transition recordings. Use when reference artifacts are needed before implementation or comparison; not to build or diagnose a clone.

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。

Patterns for vibe coding that produce production-quality output instead of garbage. Covers prompt engineering for AI coding, verification without reading every line, accept/reject/refine decision framework, architectural guardrails, context management (CLAUDE.md, .cursor/rules), TDD-driven vibe coding, screenshot-driven development, diff review discipline, and the anti-patterns that destroy quality. Activate on: "vibe coding", "AI coding quality", "Claude Code workflow", "AI-assisted development", "how to use AI for coding", "coding with AI", "agentic engineering workflow", "AI code quality", "vibe code without garbage", "production quality AI code", "CLAUDE.md setup", "cursorrules setup", "pre-commit hooks for AI", "TDD with AI", "test-driven vibe coding". NOT for: multi-person collaborative coding sessions (use cooperative-vibe-coding), building AI/LLM applications (use ai-engineer), prompt engineering for non-coding LLM use cases (use prompt-engineer).

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。

Audit social media accounts (TikTok, IG, etc.): scrape profiles, calculate engagement metrics, diagnose performance drops, interpret analytics screenshots.

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 briefs, mockups, and product context into Stitch UI screens, design systems, variants, prototypes, Tailwind-friendly HTML, and screenshots. Use when the user wants to explore a screen, edit an existing Stitch project, compare visual directions, build a multi-screen prototype, or save local design/code-export artifacts from natural-language input.

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。

Drive QA of a SwiftUI app on a real iPhone over USB - screenshot, read the accessibility tree, inspect @Observable state, tap, swipe, and type through an HTTP bridge embedded in the app under test. Use when asked to test an iOS app on a physical device, find bugs on the device, or expose a connected iPhone to a remote agent over Tailscale. Requires the ios-agent-qa runtime; not for simulator or XCTest work.

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 quando o Codex está construindo ou iterando em um jogo web (HTML/JS) e precisa de um loop confiável de desenvolvimento + teste: implementar pequenas mudanças, executar um script de teste baseado em Playwright com rajadas curtas de input e pausas intencionais, inspecionar screenshots/texto e revisar erros de console com render_game_to_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。

Traduza nós do Figma em código pronto para produção com fidelidade visual 1:1 usando o workflow MCP do Figma (contexto de design, screenshots, assets e tradução de convenções de projeto). Ative quando o usuário fornecer URLs do Figma ou IDs de nó, ou solicitar implementar designs ou componentes que devem corresponder às especificações do Figma. Requer uma conexão funcional com servidor MCP do Figma.

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 o servidor Figma MCP para buscar contexto de design, screenshots, variáveis e assets do Figma, além de traduzir nós do Figma em código de produção. Ative quando uma tarefa envolver URLs do Figma, IDs de nós, implementação design-to-code ou configuração e troubleshooting do Figma MCP.

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。

Load this skill when writing, reviewing, or interpreting behavioral accessibility automation — tests that manipulate a rendered page (resizing the viewport, pressing real keys, capturing and comparing screenshots) rather than only inspecting static markup or a single computed accessibility tree. Covers Reflow risk (SC 1.4.10) and Focus Visible risk (SC 2.4.7) checks. Absolutely always report indicator results separately from confirmed failures. Under no circumstances treat a clean behavioral scan as WCAG conformance, or collapse `cantTell`/test-error/indicator outcomes into a single pass/fail signal.

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。

[Frontend] Use when you need to extract design context from Figma URLs via MCP, REST API, or screenshot fallback.

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。