ReactやNext.jsのフォームやモーダルを、キーボード操作と画面読み上げに対応させるスキル。ラベル、エラー表示、フォーカス移動を実装・見直しします。
- フォームのラベルとエラー表示の改善
- ドロップダウンのキーボード操作確認
- モーダル開閉時のフォーカス管理
2,482 件 ・ 関連度順
概要と使いどころ
ReactやNext.jsのフォームやモーダルを、キーボード操作と画面読み上げに対応させるスキル。ラベル、エラー表示、フォーカス移動を実装・見直しします。
Webの電子署名画面で署名・日付・入力欄を数値座標で配置する手順をまとめたスキル。署名者ごとの欄の割り当てを確認し、送信前の下書き確認まで整理します。
輸出入商品の関税分類、通関書類の確認、制裁対象との照合を支援します。米国・EU・英国・アジア太平洋の貿易実務を対象に、関税優遇や税関照会への対応も整理します。
AndroidやKMPのモジュール構成と依存関係を整理し、業務処理・画面・データ取得を分けて設計するスキル。実装例をもとに各層の役割を明確にします。
運送会社の選定、運賃交渉、入札、実績評価、貨物の割り当てを支援します。米国の輸送実務を基に、費用・配送品質・輸送力を踏まえた契約や更新の判断を整理します。
画面デザインの方向性を比べるため、操作できるHTMLの試作を2〜3案作ります。レイアウトや情報量の違いを見比べ、各案の長所と弱点から採用案を検討します。
A lo-fi multi-screen MOBILE flow wireframe — three or four phone frames laid out in a row on a board, showing a connected user flow (Onboarding → Home feed → Item detail → Confirm). Grey-box content inside each device, dashed connector arrows + numbered step labels between screens, and a couple of annotation callouts. Reads like an app flow pinned to a whiteboard before any pixels are committed. Use when the brief asks for "mobile wireframe", "app flow", "user flow wireframe", "lo-fi mobile", "low fidelity", "线框图", "移动端线框", or "App 流程".
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 desktop, app windows, or pixel regions across OS platforms. Useful for marketing screenshots, design reviews, and bug 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。
Capture full-page screenshots of web pages via Chrome DevTools Protocol with zero dependencies. Useful for portfolios, case studies, and audit 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。
Use when reviewing any process that spans multiple screens, steps, or modal stages. Follow the real user journey and compare fields across steps instead of reviewing screens in isolation.
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 reviewing rendered HTML, interactive components, or design-system patterns related to Use semantic table markup for screen readers. Check native semantics first, then inspect keyboard behavior, focus flow, accessible names, and screen-reader output where relevant.
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 with persistent page state. Use when users ask to navigate websites, fill forms, take screenshots, extract web data, test web apps, or automate browser workflows. Trigger phrases include "go to [url]", "click on", "fill out the form", "take a screenshot", "scrape", "automate", "test the website", "log into", or any browser interaction request.
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。
Synthetic terminal-style screen recording guidance for Remotion `TerminalScene`.
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.js post-processing - EffectComposer, bloom, DOF, screen effects. Use when adding visual effects, color grading, blur, glow, or creating custom screen-space shaders.
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. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.
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。
Analyzes pooled CRISPR screen FASTQ reads and guide-count matrices with MAGeCK, validates guide libraries and contrasts, measures replicate and library QC, and produces gene hit rankings with effect sizes and FDR. Use for new knockout, CRISPRi, or CRISPRa screen analysis, enrichment or depletion contrasts, and MAGeCK count/test workflows; existing public dependency-score lookup belongs to DepMap.
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。
Analyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review. Requires a reachable Screenpipe HTTP API, normally on localhost:3030. Detection and embedding inference run locally; the selected LLM receives redacted app/title cluster summaries and matched skill descriptions. Use only when the user explicitly asks to analyze their recent work and propose 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。
Runs a mock interview for a specific job description. Plays the interviewer in a chosen round (recruiter screen, hiring manager, behavioral, coding, system design, case, product sense, panel), persona and difficulty; asks one question at a time, probes vague answers, and gives quote-backed rubric scores after each answer (coach mode) or at the end (realistic). Model answers use only the user's real experience. Use when the user says "mock interview me", "interview me for this job", "practice interview", "pretend you're the interviewer", "grill me for this role", "run a behavioral round", "quick recruiter screen", "hiring-manager mock", "system design mock" or "case interview practice". With Reactive Resume MCP it reads the application and stories and logs the session. For a story bank, company brief, questions to ask or a real-interview debrief, interview-prep; for scheduling or thank-you notes, job-application-manager; for fixing the resume, resume-tailor; for negotiation practice, offer-negotiation.
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. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.
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 agent-browser usage guide. Read this before running any agent-browser commands. Covers the snapshot-and-ref workflow, navigating pages, interacting with elements (click, fill, type, select), extracting text and data, taking screenshots, managing tabs, handling forms and auth, waiting for content, running multiple browser sessions in parallel, and troubleshooting common failures. Use when the user asks to interact with a website, fill a form, click something, extract data, take a screenshot, log into a site, test a web app, or automate any browser task.
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。
Document analysis with inline source screenshots. When you ask Copilot to analyze a document, Eyeball generates a Word doc where every factual claim includes a highlighted screenshot from the source material so you can verify it with your own eyes.
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。
Credit risk data cleaning and variable screening pipeline for pre-loan modeling. Use when working with raw credit data that needs quality assessment, missing value analysis, or variable selection before modeling. it covers data loading and formatting, abnormal period filtering, missing rate calculation, high-missing variable removal,low-IV variable filtering, high-PSI variable removal, Null Importance denoising, high-correlation variable removal, and cleaning report generation. Applicable scenarios arecredit risk data cleaning, variable screening, pre-loan modeling preprocessing.
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。
Stop coding agents from shipping generic UI. Use UIZZE's 800,000+ real web and iOS screens to build product-specific interfaces, define a design contract, cover required states, and run a hard finish gate. Use when designing, implementing, redesigning, critiquing, or pre-ship reviewing a web or iOS interface in Codex, Claude Code, Cursor, Copilot, or another coding agent. Trigger with "anti-ui-slop", "stop UI slop", "ground this UI in real screens", or "run the UI finish gate".
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 AI agents that interact with computers like humans do - viewing screens, moving cursors, clicking buttons, and typing text. Covers Anthropic's Computer Use, OpenAI's Operator/CUA, and open-source alternatives. Critical focus on sandboxing, security, and handling the unique challenges of vision-based control. Use when: computer use, desktop automation agent, screen control AI, vision-based agent, GUI 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。