'contrast' 검색 결과

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.

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Expert in web accessibility (WCAG 2.1/2.2 AA/AAA compliance), ARIA patterns, keyboard navigation, screen reader testing, color contrast, focus management, and automated accessibility testing

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Accessibility audit skill for scanning, fixing, and verifying WCAG 2.2 Level A and AA compliance across React, Next.js, Vue, Angular, Svelte, and plain HTML codebases. Use when auditing accessibility, fixing a11y violations, checking color contrast, generating compliance reports, or integrating accessibility checks into CI/CD pipelines.

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Rewrite AI-sounding text so it reads like the writer without changing what it says. Use when editing or reviewing prose for AI tells: not-X-but-Y contrasts, one-line closers, staged openers, forced triads, dashes everywhere, inflated claims, sales language, stock AI words, bold labels, or filler. Based on Wikipedia's "Signs of AI writing."

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Detects AI-generated deepfake audio used in voice phishing (vishing) attacks by extracting spectral features (MFCC, spectral centroid, spectral contrast, zero-crossing rate) and classifying samples with machine learning models. Supports batch analysis of audio files, generates confidence scores, and produces forensic reports. Activates for requests involving deepfake voice detection, vishing investigation, AI-generated speech analysis, voice cloning detection, or audio authenticity verification.

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Toggle between light and dark mode in Cursor's browser, screenshot both states, and flag missing token mappings or contrast issues.

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

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Plot per-gene mutation distributions on a protein-domain map (lollipop / needle plots) showing mutation position, recurrence count, and variant classification with maftools, g3-lollipop, trackViewer, and ProteinPaint. Use when visualizing recurrent mutation hotspots on a single gene's protein, marking domain boundaries from UniProt/Pfam, comparing missense vs truncating distributions, or contrasting two cohorts on the same lollipop.

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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.

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Increase visual impact, contrast, personality, and compositional confidence when a design feels bland, generic, or too safe. Use when the design needs more energy, confidence, or memorability—not when the real problem is clutter, over-intensity, or micro-detail polish.

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Systematically audit and remediate accessibility issues in UI, focusing on keyboard navigation, screen reader support, color contrast, semantic HTML, ARIA usage, and motion sensitivity. Use when the user wants to improve accessibility, make a component accessible, fix WCAG violations, add keyboard support, or ensure screen reader compatibility.

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Enhance and standardize a property listing photo with auto-contrast, sharpening, and consistent sizing.

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Windows アプリ開発 (Fluent Design / WinUI 3) のデザインガイドライン。 layout, alignment, spacing, geometry, elevation, breakpoints, Color, materials, Mica, Acrylic, Smoke, Reveal Focus, Reveal Highlight (非推奨), typography, Segoe Fluent Icons, app icons, motion, easing, page transitions, connected animation, parallax, reduce motion, haptics, NavigationView, TitleBar, TabView, CommandBar, menus, keyboard accelerators, access keys, accessibility, high contrast, globalization, RTL, widgets design。

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Interactive cell annotation and image QC for IMC/MIBI using napari, napari-imc, Mantis Viewer, and cytomapper, covering the pixels-to-cell-table bridge, overlaying masks to catch segmentation/spillover artifacts, inter-annotator variability as the accuracy ceiling, contrast-as-threshold, and building class-balanced ground-truth label sets. Use when manually labeling cells, generating training data for a classifier, QC-ing segmentation on the image, confirming clusters are spatially real, or choosing an annotation viewer.

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Differential abundance (DA) and differential state (DS) analysis for flow and mass cytometry - tests which cell populations change in frequency or marker expression between conditions using diffcyt (edgeR/voom/GLMM for DA, limma/LMM for DS), with cydar, CITRUS, and compositional methods (sccomp, scCODA, DCATS) as alternatives. Covers the sample-is-the-experimental-unit principle, design/contrast and mixed-model formulas, compositionality of cluster proportions, and FDR across clusters. Use when comparing populations between groups, choosing a DA method, handling paired/batch designs, or deciding whether compositional correction is needed.

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Performs differential expression on bulk RNA-seq count data with edgeR's negative-binomial GLM and quasi-likelihood F-test framework. Covers DGEList construction, filterByExpr, TMM/TMMwsp normalization, robust dispersion estimation, glmQLFit/glmQLFTest, TREAT for magnitude-bounded hypotheses, contrasts via no-intercept designs, voom and voomWithQualityWeights for heterogeneous samples, and the edgeR v4 bias-corrected APL changes. Use when running bulk DE with edgeR, choosing edgeR over DESeq2 (small n, transcript DE via catchSalmon, large samples), needing TREAT for a fold-change-threshold hypothesis, troubleshooting v3-to-v4 reproducibility, building paired or interaction designs, or handling library-quality heterogeneity.

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Aligns sample metadata with count matrices and constructs design matrices for downstream DE, handling the alphabetical-reference-level trap (relevel BEFORE DESeq), LRT reduced-model rules, the interaction-term resultsNames trap, continuous-covariate scaling and splines, repeated measures via duplicateCorrelation or dream, high-cardinality categorical pseudo-singular designs, sample swap detection via XIST/RPS4Y1 expression and somalier/NGSCheckMate genotypes, SABV (sex-as-biological-variable) mandate, Simpson's-paradox collapsing of technical replicates, and the `~ 0 + group` parameterization for clean contrasts. Use when building a design matrix, troubleshooting reversed fold-change direction, encoding paired or repeated-measures designs, detecting sample swaps, deciding sex-as-covariate, or aggregating technical replicates.

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Plot per-gene mutation distributions on a protein-domain map (lollipop / needle plots) showing mutation position, recurrence count, and variant classification with maftools, g3-lollipop, trackViewer, and ProteinPaint. Use when visualizing recurrent mutation hotspots on a single gene's protein, marking domain boundaries from UniProt/Pfam, comparing missense vs truncating distributions, or contrasting two cohorts on the same lollipop.

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Accessibility implementation guide for SwiftUI apps. Use when implementing VoiceOver support, adding accessibilityLabel/Hint/Value, supporting Dynamic Type, ensuring color contrast, testing accessibility, or reviewing accessibility in PRs. Covers iOS accessibility APIs, WCAG guidelines, and testing tools.

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Modern take on brutalism with bold borders, vivid accent colors, and raw, high-contrast layouts on warm surfaces.

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Clean, high-contrast enterprise design for data-driven workflows with intuitive drag-and-drop patterns and structured layouts.

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Monospace-driven, matrix-inspired design with high-contrast elements, compact density, and a hacker-chic aesthetic.

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Dot-pattern rendering technique that simulates shades with a limited palette for nostalgic, retro, high-contrast visuals.

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Throwback design with vintage-inspired typography, high-contrast retro palettes, and nostalgic visual elements.

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