「fea」の検索結果

Design and implement a new feature or component from a GitHub issue. Use for net-new functionality, not bug fixes.

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。

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search 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。

When the user wants to plan a product launch, feature announcement, or release strategy. Also use when the user mentions 'launch,' 'Product Hunt,' 'feature release,' 'announcement,' 'go-to-market,' 'beta launch,' 'early access,' 'waitlist,' or 'product update.' This skill covers phased launches, channel strategy, and ongoing launch momentum.

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。

When the user wants to create or optimize in-app paywalls, upgrade screens, upsell modals, or feature gates. Also use when the user mentions "paywall," "upgrade screen," "upgrade modal," "upsell," "feature gate," "convert free to paid," "freemium conversion," "trial expiration screen," "limit reached screen," "plan upgrade prompt," or "in-app pricing." Distinct from public pricing pages (see page-cro) — this skill focuses on in-product upgrade moments where the user has already experienced value.

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。

Generates a "What's New" / changelog screen shown after app updates with version tracking, feature highlights, and one-time display per version. Use when user wants release notes UI, update notifications, or feature announcements.

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。

Guide to macOS 26 Tahoe APIs and features. Covers Apple Intelligence (FoundationModels), MLX framework, and Continuity. Use when implementing macOS 26 specific features.

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。

Deep competitive analysis for iOS/macOS apps including feature comparison, pricing analysis, strengths/weaknesses, market positioning, and differentiation opportunities. Use when user asks for competitive analysis, competitor research, feature comparison, market positioning, or wants to understand competition in detail.

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。

Apple Intelligence skills for on-device AI features including Foundation Models, Visual Intelligence, App Intents, and intelligent assistants. Use when implementing AI-powered features.

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。

Interface copy that works — voice/tone, the PACE framework, alert anatomy, naming features, empty states, error messages, and the small-word edits that measurably improve UX. Distilled from Apple's writing sessions (2017–2026). Use when writing or reviewing any user-facing text — labels, alerts, onboarding, notifications, empty states, paywalls — or naming a feature.

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This package implements a suite of methods to preprocess data from PTR-TOF-MS instruments (HDF5 format) and generates the 'sample by features' table of peak intensities in addition to the sample and feature metadata (as a single ExpressionSet object for subsequent statistical analysis). This package also permit usefull tools for cohorts management as analyzing data progressively, visualization tools and quality control. The steps include calibration, expiration detection, peak detection and qua

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We propose an Asymmetric Within-Sample Transformation (AWST) to regularize RNA-seq read counts and reduce the effect of noise on the classification of samples. AWST comprises two main steps: standardization and smoothing. These steps transform gene expression data to reduce the noise of the lowly expressed features, which suffer from background effects and low signal-to-noise ratio, and the influence of the highly expressed features, which may be the result of amplification bias and other experi

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Data quality assessment is an integral part of preparatory data analysis to ensure sound biological information retrieval. We present here the MatrixQCvis package, which provides shiny-based interactive visualization of data quality metrics at the per-sample and per-feature level. It is broadly applicable to quantitative omics data types that come in matrix-like format (features x samples). It enables the detection of low-quality samples, drifts, outliers and batch effects in data sets. Visualiz

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Keep README files current with project changes. Use when project structure changes, features added, or setup instructions modified. Suggests README updates based on code changes. Triggers on significant project changes, new features, dependency changes.

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, enhance, or revive GitHub repos - ship one feature PR per watched repo (watched), make the best single enhancement on one external repo (external), or revive the top dormant repo (dormant).

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。

Enumerate every end-to-end feature as strict JSON entries with passes:false, editable-passes-only discipline, and priority order. The ledger fresh-context sessions read to know what's done, what's next, and what they're forbidden to touch.

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。

Run the fixed 6-step session-opening sequence — pwd, read progress, git log, count remaining features, init.sh, smoke-test last feature — before touching any new work. The orientation ritual that lets fresh-context sessions reconstruct project state in under a minute.

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 a single-product deep-dive showcase page as a self-contained HTML file. Triggers on: "build a product showcase page", "deep dive landing page for [product]", "create a product spotlight page", "product feature page", "single product page", "detailed page about [product]", "build a page showing everything about [product]", "create a long-form product page", "build a sales page for [product]", "product deep dive page", "make a feature breakdown page for [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。

Use when creating a feature, designing folder structure, adding repositories/services/view models, wiring dependency injection, or deciding which layer owns logic.

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。

Runs a timeboxed PROBE to validate one core assumption, then optionally PROMOTES the probe into a walking skeleton — the first e2e thin slice of the feature, committed and demo-able. Use after DISCUSS when the feature involves a new mechanism, performance requirement, or external integration.

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。

Detects current wave progress for a feature and resumes at the next step. Scans docs/feature/ for artifacts.

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 SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.

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。

Loads full context for a React Flow (@xyflow/react) user journey mapping project. Use when working on, extending, debugging, or building features for the journey map tool. Triggers on: "journey map project", "open journey map", "work on journey map", "build user journey", "react flow journey project", "journey-map app", or any request to add features like swimlanes, emotion curves, persona nodes, touchpoints, or pain point markers.

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。

Defines where UI components belong in Operately (TurboUI-first). Use when creating, changing, reviewing, or migrating UI components, adding features that need UI, or deciding whether to refactor legacy app UI in app/assets/js/components or app/assets/js/features. Covers pure TurboUI components, component reuse, the app bridge pattern, and legacy migration scenarios.

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。

Apply core PHP language standards and modern 8.x features. Use when working with PHP 8.x features like enums, fibers, readonly properties, or named arguments.

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。