「labels」の検索結果

Apply platform accessibility best practices to SwiftUI, UIKit, and AppKit code. Essential companion to any SwiftUI, UIKit, or AppKit skill — always use together. Use whenever writing, editing, or reviewing ANY SwiftUI views, UIKit view controllers, AppKit views/window controllers, or platform UI — even when the user doesn't mention accessibility. Also use when the user mentions VoiceOver, Voice Control, Dynamic Type, Reduce Motion, screen reader, a11y, WCAG, accessibility audit, Nutrition Labels, accessibilityLabel, UIAccessibility, NSAccessibility, assistive technologies, or Switch Control. Not for server-side Swift, non-UI packages, or CLI 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。

Write, review, or improve Swift APIs using Swift API Design Guidelines for naming, argument labels, documentation comments, terminology, and general conventions. Use when designing new APIs, refactoring existing interfaces, or reviewing API clarity and fluency.

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。

Implement, review, or improve accessibility in iOS/macOS apps with SwiftUI and UIKit. Use when adding VoiceOver support with accessibility labels, hints, values, and traits; when grouping or reordering accessibility elements; when managing focus with @AccessibilityFocusState; when supporting Dynamic Type with @ScaledMetric; when building custom rotors or accessibility actions; when auditing a11y compliance; or when adapting UI for assistive technologies and system accessibility preferences.

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 someone asks to write, rewrite, review, or improve text that appears inside a product or interface. Examples: "review the UX copy", "is there a better way to phrase this", "rewrite this error message", "write copy for this screen/flow/page", reviewing button labels, improving CLI output messages, writing onboarding copy, settings descriptions, or confirmation dialogs. Trigger whenever the request involves wording shown to end users inside software — apps, web, CLI, email notifications, modals, tooltips, empty states, or alerts. Also trigger for vague requests like "review the UX" where interface copy review is implied. Do NOT trigger for content marketing, blog posts, app store listings, API docs, brand guides, cover letters, or interview questions — this is a technical writing skill for interface 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。

Expert guidance on iOS accessibility best practices, patterns, and implementation. Use when developers mention: (1) iOS accessibility, VoiceOver, Dynamic Type, or assistive technologies, (2) accessibility labels, traits, hints, or values, (3) automated accessibility testing, auditing, or manual testing, (4) Switch Control, Voice Control, or Full Keyboard Access, (5) inclusive design or accessibility culture, (6) making apps work for users with disabilities.

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 Cursor's browser aria snapshots to audit a page for accessibility issues — missing labels, broken tab order, contrast, and ARIA misuse.

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。

Diagnostic test / biomarker accuracy — sensitivity, specificity, PPV, NPV, likelihood ratios, accuracy from a 2x2 table; ROC curve, AUC, and the optimal cutoff (Youden) for a continuous biomarker; and post-test probability via Bayes. Use when you have test results vs a gold standard (binary 2x2, or a continuous score + true labels) and need to judge how good the test is, pick a threshold, or compute the probability of disease given a result. Emphasizes the prevalence-dependence of PPV/NPV.

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。

Drug and chemical toxicity assessment via adverse outcome pathways (AOPs), real-world FAERS adverse event signals, FDA labels, and toxicogenomic associations. Triangulates molecular initiating event to cellular outcome to organ-level toxicity to clinical adverse event. Use for hepatotoxicity/cardiotoxicity/nephrotoxicity prediction and toxicology 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。

Automated WCAG 2.1 AA accessibility testing with axe-core and Lighthouse CI. Auto-detects frontend framework (React, Next.js, Vue, Angular, Svelte, Astro, Flutter, React Native), discovers all routes and interactive components, installs Playwright + axe-core for page-level scanning and jest-axe/vitest-axe for component-level testing. Generates tests for color contrast (4.5:1), alt text, form labels, ARIA attributes, heading order, landmark regions, focus visibility, keyboard navigation (tab order, focus traps, modal focus management, skip-to-content), screen reader compatibility (aria-live regions, error announcements, toast notifications), and Flutter Semantics validation (48dp touch targets, semanticLabel). Reports violations by severity (critical, serious, moderate, minor) with WCAG criterion references. Use when adding a11y testing, auditing accessibility compliance, fixing contrast issues, or validating keyboard and screen reader support.

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 accessibility infrastructure for VoiceOver, Dynamic Type, and accessibility features. Use when improving app accessibility, adding accessibility labels and hints, or auditing compliance.

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。

Implement WCAG 2.1 AA accessibility compliance with ARIA labels, keyboard navigation, screen reader support, and color contrast. Use when ensuring accessibility or fixing a11y issues.

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。

Accessibility testing for web applications using Playwright (@playwright/test) with TypeScript and axe-core. Use when asked to write, run, or debug automated accessibility checks, keyboard navigation tests, focus management, ARIA/semantic validations, screen reader compatibility, or WCAG 2.1 Level AA compliance testing. Covers axe-core integration, POUR principles (perceivable, operable, understandable, robust), color contrast, form labels, landmarks, and accessible names.

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。

Detect inconsistencies in ID formatting, date/time display, monetary amounts, and enum/status labels compared to existing patterns in the codebase.

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。

Assign cell types from marker expression in IMC/MIBI data using clustering (PhenoGraph/FlowSOM/Leiden/Pixie), marker-based probabilistic classifiers (Astir), or image-context CNNs (CellSighter), covering the double-positive segmentation artifact, lineage-vs-state markers, the two spillover types, and why a "cell type" in imaging is conditioned on a segmentation guess. Use when phenotyping segmented IMC cells, choosing clustering vs classification, diagnosing implausible double-positive populations, separating lineage from functional markers, or transferring labels across a cohort.

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。

Compose multi-panel publication figures with patchwork, cowplot, gridExtra (R), or matplotlib GridSpec/subfigures (Python) including shared axes/legends/guides collection, panel labels in Nature/Cell convention, and journal-spec sizing. Covers patchwork ≥1.2.0 axes='collect' feature, Type-42 font embedding, and the cairo_pdf save path. Use when composing 2+ subpanels into a single figure for journal submission.

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。

Write or revise MiniMax H3 prompts for text, keyframe, and full-reference modes, preserving mode-specific fields, labels, and timing.

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。

投行 strategic-alternatives pitch book — trading comps / precedent transactions / valuation football field / DCF sensitivity / 战略选项矩阵 / 流程建议。改写 assets/template.html 保留 IB-specific chrome / disclosure bands / source labels。用于 Board / sell-side 讨论材料。**不是** VC 融资 deck。工作流改自 Anthropic financial-services Pitch Agent (Apache-2.0)。

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。

Make a GTK4/libadwaita app accessible — accessible labels and roles, tooltips on icon-only buttons, keyboard navigation, contrast, and testing with Orca/Accerciser. Use when fixing a11y issues or running the accessibility category of a HIG audit.

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 accessible web applications following WCAG 2.1/2.2 guidelines with proper semantic HTML, ARIA attributes, keyboard navigation, screen reader support, and inclusive design. Use when implementing ARIA labels and roles, ensuring keyboard navigation, supporting screen readers, providing text alternatives for images, managing focus, creating accessible forms, building inclusive UI components, testing with accessibility tools, meeting WCAG compliance levels, or designing for users with disabilities.

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 any visual design using Adobe Express templates — including flyers, posters, banners, social media posts (Instagram stories, Facebook posts, LinkedIn graphics), business cards, invitations, greeting cards, resumes, cover letters, brochures, newsletters, certificates, presentations, YouTube thumbnails, email headers, logos, menus, labels, and more. Use this skill whenever the user wants to make, design, create, or build any visual — even if they just say "make me a flyer", "design a poster", "I need something for Instagram", "create an event invite", "make a business card", or any similar request. Also handles requests to find or browse templates, edit text/copy, change background colors, or animate a design. Access: 🔐 Signed-In required | Gen AI: ❌

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。

Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local markdown), triage label vocabulary, and domain doc layout. Run before first use of `to-issues`, `to-prd`, `triage`, `diagnose`, `tdd`, `improve-codebase-architecture`, or `zoom-out` — or if those skills appear to be missing context about the issue tracker, triage labels, or domain docs.

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。

Repair corrupted `??:` labels in ATM task-card notes. Use when notes fields contain `??:` instead of `狀態:` / `驗證:` / `變更:` / `阻塞:`.

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。

Assign cell types from marker expression in IMC/MIBI data using clustering (PhenoGraph/FlowSOM/Leiden/Pixie), marker-based probabilistic classifiers (Astir), or image-context CNNs (CellSighter), covering the double-positive segmentation artifact, lineage-vs-state markers, the two spillover types, and why a "cell type" in imaging is conditioned on a segmentation guess. Use when phenotyping segmented IMC cells, choosing clustering vs classification, diagnosing implausible double-positive populations, separating lineage from functional markers, or transferring labels across a cohort.

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。