789 skills · sorted by relevance
Connect json-render interfaces to XState Store for state management. The skill shows how to adapt an atom, a container holding application state, so json-render reads and writes through it.
Interface-based state machine patterns for Unity game states, character controllers, and UI flows. Use when implementing game flow (menu -> gameplay -> game over), character states (idle -> run -> jump -> fall), AI behavior states, or UI screen transitions. Triggers on "state machine", "game states", "character states", "screen flow", "game flow", "add states to", "idle/run/jump", "menu flow", "AI states", "boss phases", or any task involving managing discrete states with transitions between them. Reads ProjectConfig.yaml -> architecture_pattern to adapt patterns for SO-first or DI-first.
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Clean up an iOS app after /ios-qa by removing the DebugBridge package and its debug wiring. The cleanup covers StateServer, DebugOverlay, generated accessor code, and hooks added to the app.
Build Angular interfaces that handle loading, errors, and data display. This skill guides component work involving asynchronous data, which arrives after a request, and helps organize the interface states needed to present it.
List and capture every interface state added or changed by a pull request, a proposed code change. Include error states, toggles, buttons, forms, and edited pages so reviewers can inspect their appearance.
Build Storybook page stories for SigNoz by mapping API requests, display states, and URL parameters. Use msw mock responses, which simulate API replies, and controls to inspect loading, errors, permissions, and other page states.
Connect json-render to Redux or Redux Toolkit so UI state reads and writes use a Redux store. The skill explains how to select the relevant state and dispatch actions that replace it when updates occur.
Helps connect json-render to a writable Jotai atom, a unit that holds application state. Covers adapter setup and sharing a Jotai store so json-render and React components read and update the same values.
Use border-beam to add moving edge highlights or breathing glows to React controls and panels. Connect effects to loading, selection, and focus states while retaining clear text, static indicators, keyboard focus, and support for reduced motion.
Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
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Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
The English summary is being prepared. Showing the original description.
Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
The English summary is being prepared. Showing the original description.
Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
The English summary is being prepared. Showing the original description.
Segments the genome into chromatin states from combinatorial histone modification and chromatin factor ChIP-seq data. Uses ChromHMM (multivariate HMM on binarized signal, v1.27), Segway (Dynamic Bayesian Network on continuous signal), EpiSegMix (flexible-distribution HMM with duration modeling, 2024), EpiLogos (multi-biosample visualization), IDEAS (cell-type-aware joint), and full-stack ChromHMM (Vu Ernst 2022) for cross-cell-type segmentations. Handles state-count selection (15 vs 18 vs 25 states), binarization choice, OverlapEnrichment / NeighborhoodEnrichment downstream analysis, and cross-biosample integration. Use when learning chromatin states from a histone mark panel, characterizing learned states by genomic feature enrichment, or comparing chromatin landscapes across cell types.
The English summary is being prepared. Showing the original description.
Refine interface appearance and interactions by reviewing spacing, typography, rounded corners, shadows, animation, and clickable areas. Get concrete before-and-after recommendations for buttons, cards, forms, and other components, including hover, focus, and loading states.
Work with Linear tickets through Orca's CLI. Find issues, update workflow states, report completion with a PR or MR link and a comment, and create follow-up tickets linked to a parent issue.
Audit CSS class names for inconsistency and ambiguity, then organize them using BEM, a convention that names components, their elements, and variations. Check the rendered interface across screen sizes and interaction states when reviewing changes.
Review styles written directly in HTML or embedded style blocks, and move suitable rules into external stylesheets. Check layouts across screen sizes and interaction states while preserving justified exceptions for critical styles and dynamic values.
Review the loading order of CSS and JavaScript to address rendering delays and flashes of unstyled content. Suggest changes to the document head, script loading, and critical styles, while checking layouts across screen sizes and interaction states.
Review CSS loading that delays a page’s first visible content. Help inline essential styles and defer other stylesheets, using preload and media conditions, while checking rendered layouts at different screen widths and interaction states.
Design and implement web or iOS interfaces using the product’s existing components and design rules. Define required screen states and responsive behavior, consult optional visual references when useful, and inspect the rendered result when supported.
Turn a design into a developer handoff document covering layout, shared design settings, component options, interactions, and screen-size behavior. Include loading and error states, animation details, and accessibility notes to clarify implementation requirements.
Helps connect json-render to a Zustand store, where application values are managed. Covers sharing the entire store or selecting a nested portion, with configurable update behavior for the selected state.
Turn a design into a developer handoff document covering layout, shared design settings, component options, interactions, and screen-size behavior. Include loading and error states, animation details, and accessibility notes to clarify implementation requirements.