Extract reusable components, product patterns, and design tokens into a clearer design system with shared APIs, documented defaults, and better reuse. Use when the user wants to refactor repeated UI, consolidate buttons/cards/forms/sections, build a component library, or turn one-off values into reusable 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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Build or refine UI color systems, warmth, semantic color, and color-based hierarchy in designs that are too gray, monochromatic, or missing color meaning. Use when the user mentions dull colors, gray UI, missing warmth, weak semantic color, or a need for stronger color hierarchy.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Improve UX writing, marketing copy, labels, microcopy, instructions, and error messages so interfaces and product messaging are easier to understand and act on. Use when the user mentions confusing copy, unclear labels, bad error text, weak CTAs, hard-to-follow instructions, or wanting better UX writing.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
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.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Improve UI typography by fixing font choices, type scale, hierarchy, weight, and readability so text feels intentional. Use when the user mentions fonts, typography, type scale, readability, text hierarchy, or sizing that feels off.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Create standout, technically ambitious interfaces that feel extraordinary through cinematic transitions, advanced motion, heavy rendering, or other high-ambition implementation work. Use when the user wants to wow, impress, go all-out, or push a feature beyond conventional UI polish—not when simple visual confidence or routine cleanup is enough.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Design or improve search experiences, result presentation, and filtering interfaces. Use when the user asks to add search, redesign search results, improve findability, build autocomplete, add filters, or fix zero-results dead ends.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Diagnose and fix UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Simplify cluttered UI by removing unnecessary elements, choices, features, and structural complexity. Use when the problem is too many controls, options, features, or competing elements—not when the structure is sound and the real issue is only visual intensity or lack of personality.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Evaluate an interface from a UX perspective, assessing hierarchy, information architecture, emotional resonance, cognitive load, and overall quality with quantitative scoring and actionable feedback. Use when the user wants an overall design or UX review—not when the main need is measurable accessibility/performance diagnosis, or final micro-detail polish.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Generate 5 distinct, production-grade UI variations for a requested new or existing section, component, page, flow, or shell, then help the user preview and apply one. Use when the user asks to add or redesign UI like a hero, pricing, navbar, auth flow, dashboard shell, ecommerce surface, or data component.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Improve or implement purposeful motion systems, micro-interactions, gestures, and transition behavior for production-grade UI. Use when the user mentions animation, motion, transitions, micro-interactions, hover states, drawers, toasts, gestures, or making the UI feel more alive.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Adapt designs for narrow, medium, wide, embedded, or print web contexts without losing usability, hierarchy, or target sizing. Use when the user mentions responsive design, breakpoints, narrow layouts, viewport changes, touch-capable browsers, or cross-context adaptation.
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。
aladicf/better-web-ui☆ 452026年5月22日 更新
Build and review Blazor applications across server, WebAssembly, web app, and hybrid scenarios with correct component design, state flow, rendering, and hosting choices.
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。
managedcode/PrompterOne☆ 452026年5月9日 更新
Use Biome in .NET repositories that ship Node-based frontend assets and want a fast combined formatter-linter-import organizer for JavaScript, TypeScript, CSS, JSON, GraphQL, or HTML. Use when a repo prefers a modern all-in-one CLI over a larger ESLint plus Prettier style stack.
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。
managedcode/PrompterOne☆ 452026年5月9日 更新
Use Stylelint in .NET repositories that ship CSS, SCSS, or other stylesheet assets alongside web frontends. Use when a repo needs a dedicated CLI lint gate for selectors, properties, duplicate styles, naming conventions, or design-system rule enforcement.
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。
managedcode/PrompterOne☆ 452026年5月9日 更新
Apply MCAF UI/UX guidance for design systems, accessibility, front-end technology selection, and design-to-development collaboration. Use when bootstrapping a UI project, choosing front-end stack, or tightening design and accessibility practices.
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。
managedcode/PrompterOne☆ 452026年5月9日 更新
Implement and execute approved research Experiment, Tuning, or Design Cards with reproducible logs, metrics, environment, and artifacts. Use for bounded coding, debugging, and runs; not for changing claims, priorities, budgets, or the Research Spine.
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。
cpt13-g/build-research-evidence☆ 452026年10月21日 更新
Analyze and engineer protein glycosylation. Scan sequences for canonical N-glycosylation sequons (N-X-S/T with X not proline, including overlapping sites), predict O-GalNAc hotspots, read glycan notation, and reach the curated external tooling (NetNGlyc, NetOGlyc, GlycoShield, GlycoWorkbench, GlyTouCan, GlyConnect). Use this skill for therapeutic antibody glycoengineering and afucosylation for ADCC, Fc glycan control, glycan shielding in vaccine immunogen design, sequon removal or insertion, and half-life engineering through sialylation. Also trigger on N-glycosylation, sequon, NXS/NXT, O-glycosylation, glycoform heterogeneity, afucosylation, high-mannose, GlyTouCan, or WURCS.
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。
K-Dense-AI/drug-discovery-agent-skills☆ 452026年10月19日 更新
Design small interfering RNA and antisense oligonucleotide sequences against a transcript, and screen them for the failure modes specific to nucleic-acid drugs. Use this skill to tile a target transcript, apply positional and thermodynamic selection rules including duplex asymmetry and nearest-neighbour melting temperature, scan candidates for seed-region complementarity to off-target transcripts, and lay out a chemical modification pattern — gapmer architecture, 2'-O-methyl and 2'-MOE wings, locked nucleic acid, and phosphorothioate placement. Also trigger on siRNA, antisense oligonucleotide, ASO, gapmer, RNase H, seed region, duplex asymmetry, 2'-MOE, locked nucleic acid, phosphorothioate, or GalNAc conjugate.
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。
K-Dense-AI/drug-discovery-agent-skills☆ 452026年10月19日 更新
Generate and optimise novel small molecules with REINVENT 4 — de novo sampling from a chemical language model, scaffold decoration with LibInvent, fragment linking with LinkInvent, and similarity-constrained analogue generation with Mol2Mol. Use this skill to set up reinforcement-learning or curriculum runs, compose a multi-parameter scoring function from docking scores, predictive models, and physicochemical desirability, and read the resulting sampled sets. Also trigger on REINVENT, LibInvent, LinkInvent, Mol2Mol, scaffold hopping, R-group replacement, linker design, chemical language model, or reinforcement-learning molecule optimisation.
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。
K-Dense-AI/drug-discovery-agent-skills☆ 452026年10月19日 更新
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
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。
K-Dense-AI/drug-discovery-agent-skills☆ 452026年10月19日 更新
Design new proteins that bind a chosen surface, using BindCraft's AlphaFold2-guided hallucination or the RFdiffusion backbone plus ProteinMPNN sequence pipeline. Use this skill to specify a target epitope by hotspot residue, trim a receptor to the region worth designing against, set up a design campaign, and filter the output on the in-silico metrics that predict experimental success — interface predicted TM-score, predicted aligned error at the interface, buried surface area, and shape complementarity. Also trigger on BindCraft, RFdiffusion, ProteinMPNN, minibinder, hallucination, inverse folding, hotspot residue, epitope targeting, ipTM, or de novo binder.
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。
K-Dense-AI/drug-discovery-agent-skills☆ 452026年10月19日 更新
Decide whether a protein has a pocket worth targeting, and where it is, before committing to a docking or design campaign. Use this skill to run fpocket cavity detection, rank cavities by druggability and volume, compare apo and holo conformations to spot induced fit, identify allosteric and cryptic cavities that only open in simulation, and convert a chosen cavity into the search box coordinates a docking run needs. Also trigger on fpocket, cavity detection, druggability score, alpha sphere, cryptic pocket, allosteric site, pocket volume, hotspot mapping, or undruggable target assessment.
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。
K-Dense-AI/drug-discovery-agent-skills☆ 452026年10月19日 更新