When addressing slow application endpoints, high database CPU usage, or standardizing data access patterns.
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。
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概要と使いどころ
When addressing slow application endpoints, high database CPU usage, or standardizing data access patterns.
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。
Comprehensively reviews SwiftUI code for best practices on modern APIs, maintainability, and performance. Use when reading, writing, or reviewing SwiftUI projects.
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 optimized Apple App Store metadata recommendations with ASO best practices. Use this skill when analyzing app listings, optimizing metadata (title, subtitle, description, keywords), performing competitive analysis, or validating App Store listing requirements. Triggers on queries about App Store optimization, metadata review, or screenshot strategy.
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。
Triage TestFlight crashes, beta feedback, and performance diagnostics using asc. Use when the user asks about TF crashes, TestFlight crash reports, beta tester feedback, app hangs, disk writes, launch diagnostics, or wants a crash summary for a build or app.
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 SwiftUI views with modern MV architecture, state management, and view composition patterns. Covers @Observable ownership rules, @State/@Bindable/@Environment wiring, view decomposition, custom ViewModifiers, environment values, async data loading with .task, iOS 26+ APIs, Writing Tools, and performance guidelines. Use when structuring a SwiftUI app, managing state with @Observable, composing view hierarchies, or applying SwiftUI 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。
When the user wants to discover, evaluate, or prioritize App Store keywords. Also use when the user mentions "keyword research", "find keywords", "search volume", "keyword difficulty", "keyword ideas", or "what keywords should I target". For implementing keywords into metadata, see metadata-optimization. For auditing current keyword performance, see aso-audit.
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 set up, interpret, or improve their app analytics and tracking. Also use when the user mentions "analytics", "tracking", "metrics", "KPIs", "App Store Connect analytics", "install tracking", "funnel", "attribution", or "how is my app performing". For A/B testing, see ab-test-store-listing. For retention metrics, see retention-optimization.
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。
Collect and analyze on-device performance metrics and crash diagnostics using MetricKit. Use when setting up MXMetricManager, handling MXMetricPayload or MXDiagnosticPayload, processing crash/hang/disk-write diagnostics via MXCallStackTree, adding custom signpost metrics, or uploading telemetry to an analytics backend.
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 CloudKit and iCloud sync in iOS/macOS apps. Use when working with CKContainer, CKRecord, CKQuery, CKSubscription, CKSyncEngine, CKShare, NSUbiquitousKeyValueStore, or iCloud Drive file coordination; when syncing SwiftData models via ModelConfiguration with cloudKitDatabase; when handling CKError codes for conflict resolution, network failures, or quota limits; or when checking iCloud account status before performing sync operations.
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。
Integrate and optimize Core ML models in iOS apps for on-device machine learning inference. Covers model loading (.mlmodelc, .mlpackage), predictions with auto-generated classes and MLFeatureProvider, compute unit configuration (CPU, GPU, Neural Engine), MLTensor, VNCoreMLRequest, MLComputePlan, multi-model pipelines, and deployment strategies. Use when loading Core ML models, making predictions, configuring compute units, or profiling model 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。
Debug iOS apps and profile performance using LLDB, Memory Graph Debugger, and Instruments. Use when diagnosing crashes, memory leaks, retain cycles, main thread hangs, slow rendering, build failures, or when profiling CPU, memory, energy, and network usage.
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。
Analyze Swift Package Manager dependencies, package plugins, module variants, and CI-oriented build overhead that slow Xcode builds. Use when a developer suspects packages, plugins, or dependency graph shape are hurting clean or incremental build performance, mentions SPM slowness, package resolution time, build plugin overhead, duplicate module builds from configuration drift, circular dependencies between modules, oversized modules needing splitting, or modularization 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。
Benchmark Xcode clean and incremental builds with repeatable inputs, timing summaries, and timestamped `.build-benchmark/` artifacts. Use when a developer wants a baseline, wants to compare before and after changes, asks to measure build performance, mentions build times, build duration, how long builds take, or wants to know if builds got faster or slower.
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。
Expert Core Data guidance (iOS/macOS): stack setup, fetch requests & NSFetchedResultsController, saving/merge conflicts, threading & Swift Concurrency, batch operations & persistent history, migrations, performance, and NSPersistentCloudKitContainer/CloudKit sync.
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。
Diagnose data races, convert callback-based code to async/await, implement actor isolation patterns, resolve Sendable conformance issues, and guide Swift 6 migration. Use when developers mention: (1) Swift Concurrency, async/await, actors, or tasks, (2) "use Swift Concurrency" or "modern concurrency patterns", (3) migrating to Swift 6, (4) data races or thread safety issues, (5) refactoring closures to async/await, (6) @MainActor, Sendable, or actor isolation, (7) concurrent code architecture or performance optimization, (8) concurrency-related linter warnings (SwiftLint or similar; e.g. async_without_await, Sendable/actor isolation/MainActor lint).
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。
Write, review, or improve SwiftUI code following best practices for state management, view composition, performance, macOS-specific APIs, and iOS 26+ Liquid Glass adoption. Use when building new SwiftUI features, refactoring existing views, reviewing code quality, or adopting modern SwiftUI patterns.
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。
Parallel read-only multi-agent review of a current git diff or explicit file scope to find behavioral regressions, security or privacy risks, performance or reliability issues, and contract or test coverage gaps. Use when the user asks for a review swarm, parallel review, diff review, regression review, security review, or wants high-signal issues plus a prioritized fix path without editing files.
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。
Comprehensive code review guidelines for iOS/Swift covering architecture, performance, security, and 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。
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。
TypeScript and Prisma ORM best practices for schema design, type-safe queries, migrations, and error handling. Use when writing Prisma schemas, building database access layers, or debugging query performance in TypeScript projects.
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。
This skill should be used when the user asks how to "use VibeTags", "add VibeTags annotations", "set up AI guardrails", "protect code from AI", "configure AI platforms", asks about @AILocked, @AIContext, @AIDraft, @AIAudit, @AIIgnore, @AIPrivacy, @AICore, @AIPerformance, @AIContract, @AITestDriven, @AIThreadSafe, @AIImmutable, @AIDeprecated, @AIObservability, @AIRegulation, @AIArchitecture, @AILegacyBridge, @AIStrictClasspath, @AIInternationalized, @AIPublicAPI, @AISchemaSafe, @AIStrictExceptions, @AIStrictTypes, @AIParallelTests, @AIIdempotent, @AIFeatureFlag, @AISecure, @AICallersOnly, @AISandboxOnly, @AIMemoryBudget, @AIPure, @AIDomainModel, @AIExtensible, @AIInputSanitized, @AISecureLogging, @AIExplain, @AIPrototype, @AISunset, @AITemporary annotations, or wants to control how AI tools interact with Java code.
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。
Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.
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 convex-doctor static analysis, interpret findings, and fix issues across security, performance, correctness, schema, and architecture categories. Use when running convex-doctor, fixing convex-doctor warnings or errors, improving the convex-doctor score, or when asked about Convex code quality, static analysis, or linting Convex functions.
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。
Critical Git safety rules to prevent destructive operations. Use whenever performing git operations, reverting changes, or managing commits. Prevents accidental loss of work.
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。