「aria」の検索結果

Provides comprehensive patterns for deploying Next.js applications to production. Use when configuring Docker containers, setting up GitHub Actions CI/CD pipelines, managing environment variables, implementing preview deployments, or setting up monitoring and logging for Next.js applications. Covers standalone output, multi-stage Docker builds, health checks, OpenTelemetry instrumentation, and production best 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。

Provides and generates complete CRUD workflows for Spring Boot 3 services. Creates feature-focused architecture with Spring Data JPA aggregates, repositories, DTOs, controllers, and REST APIs. Validates domain invariants and transaction boundaries. Use when modeling Java backend services, REST API endpoints, database operations, web service patterns, or JPA entities for Spring Boot applications.

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 extracting first-party expertise from a subject-matter expert before writing content. Produces a knowledge document of contrarian takes, specific examples, and surprising outcomes that AI can't fabricate.

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 several genuinely different throwaway variations (designs, approaches, drafts) for the user to react to. Use when the user can only recognize what they want by seeing it — visual design, UX flows, naming, tone — or asks to brainstorm or prototype before building.

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 anomalies and outliers in construction data: unusual costs, schedule variances, productivity spikes. Statistical and ML-based detection methods.

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。

Fetch construction material prices from open APIs. Track price trends, regional variations, and update cost databases.

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。

Track actual vs planned productivity using CWICR norms. Calculate productivity rates, identify variances, and generate performance 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。

Compare cost estimates across projects, versions, and scenarios. Identify variances, benchmark against standards, and generate comparison 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。

Base/variable split recommendations, accelerators, decelerators, quota retirement methods, SPIFs, cost of sales tracking.

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。

Define a product's motion design language -- duration and easing scales, choreography rules, and signature moves -- and export it as tokens plus ready-to-use Framer Motion variants and CSS. The difference between animations and a motion system: everything moves like it belongs to the same product.

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。

Writes conversion-focused landing page copy - headlines, subheads, value propositions, feature and benefit blocks, social proof, FAQs, and CTA button text - using PAS, AIDA, or StoryBrand. Use when the user wants words for a landing page, sales page, product or pricing page, waitlist page, homepage hero, or ad-to-page flow, including rewriting weak copy, generating headline or CTA variants for A/B tests, or turning a product description into page sections. Use landing-page-optimizer instead for auditing an existing page's performance, and a frontend skill for building the page itself.

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。

A/B test subject line variations using proven copywriting frameworks. Predict open rates based on historical performance.

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。

Convert a light-only site or app to a real dark mode -- semantic token mapping, elevation-based surfaces, recalibrated shadows and imagery -- not a naive inversion. Handles Tailwind, CSS variables, and styled-components, plus the toggle, persistence, and no-flash boot.

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。

Audit and sync design tokens between the source of truth (tokens.json, Figma variables export) and the code that should consume them (Tailwind config, CSS custom properties, theme files). Finds drift -- hardcoded values, orphan tokens, out-of-date copies -- and fixes it in the right direction.

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。

Extract color palettes from images, websites, or designs. Identifies dominant colors, generates complementary schemes, and exports in multiple formats (HEX, RGB, HSL, Tailwind, CSS variables). Use when users need color schemes from images, brand colors, or design system palettes.

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 a complete, premium design system from a brand brief or an existing site — color tokens, type scale, spacing/radius/elevation, motion language, and component specs — exported as Tailwind config, CSS variables, and a usage doc. Built to look editorial and human-crafted, not template-generated. Use when starting a new product/site, unifying an inconsistent UI, or codifying a brand 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。

March Madness, playoff brackets, tournament picks. Upset potential, chalk vs contrarian strategies, historical trends, confidence levels.

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。

Adversarial review and fix loop for code, specs, plans, and migration manifests.

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。

Convenes a multi-LLM expert panel to pressure-test hard-to-reverse decisions. Use when reversibility score is low and adversarial review is warranted.

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。

States load-bearing decisions, invariants, and weak points. Use when judging a design change. Do not use for gating; use night-market-change-control.

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 applying a published cohort study's methodology to a different database. Extracts the design from the source paper, maps variables to the target database with a harmonization table, generates the analysis code and reports every forced deviation.

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 comparing an exposure-outcome association across countries with parallel national surveys (KNHANES, NHANES, CHNS). Harmonizes variables, runs parallel weighted analyses and builds comparison tables for 2-country (KR+US) or 3-country (KR+US+CN) designs.

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 a tabular dataset (CSV, Excel, Parquet, Stata, SAS) needs a data dictionary. Profiles every variable (type, levels, range, missingness) into codebook.md and codebook.json and flags coded values of unknown meaning as [NEEDS DICTIONARY] instead of guessing.

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 one validated cohort analysis must be repeated across many exposure/outcome pairs. Generates one R/Python script per combination from a single methodology template, changing only the variables, and aggregates the results into a summary matrix.

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。