1,489 件 ・ 関連度順
概要と使いどころ
Use when working with Appwrite — appwrite backend platform management covering project inventory, database collections, user authentication stats, storage bucket usage, function deployments, webhook configuration, and platform health. Use for comprehensive Appwrite project assessment and resource monitoring.
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 working with Aws Systems Manager — aWS Systems Manager parameter store management, session management, patch compliance tracking, and Run Command analysis. Covers parameter inventory, managed instance status, automation execution, maintenance windows, and inventory collection.
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 working with Gcp Firestore Deep — google Cloud Firestore document and collection analysis, index management, security rules review, usage monitoring, and performance diagnostics via gcloud CLI.
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 working with Mongodb — mongoDB database analysis, performance tuning, query optimization, and health monitoring. Covers collection analysis, index recommendations, aggregation pipelines, replica set health, Atlas cluster management, and slow query investigation.
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 working with Firestore — google Cloud Firestore collection analysis, index management, security rules review, usage metrics, and query 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。
A collection of methods in an intelligent software structure allows the user to focus on fine-tuning
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。
With this cross-journal Collection, the editors at Nature Communications , Communications Psychology GAP: no mappable capability in latest signal (our
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。
Crawl and extract a bounded set of pages from one website through Tavily. Use for documentation downloads, site-section collection, or semantic multi-page extraction when map plus individual extract calls are insufficient.
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 read-only MongoDB queries (find) or aggregation pipelines using natural language, with collection schema context and sample documents. Use this skill whenever the user asks to write, create, or generate MongoDB queries, wants to filter/query/aggregate data in MongoDB, asks "how do I query...", needs help with query syntax, or discusses finding/filtering/grouping MongoDB documents. Also use for translating SQL-like requests to MongoDB syntax. Does NOT handle Atlas Search ($search operator), vector/semantic search ($vectorSearch operator), fuzzy matching, autocomplete indexes, or relevance scoring - use search-and-ai for those. Does NOT analyze or optimize existing queries - use mongodb-query-optimizer for that. Does NOT handle aggregation pipelines that involve write operations. Requires MongoDB MCP server.
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。
MongoDB with Mongoose — schemas, models, aggregation pipelines, migrations, and Atlas connections. Use when designing collections, writing queries, or integrating MongoDB into Node.js/Next.js apps.
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。
Scans .NET code for ~50 performance anti-patterns across async, memory, strings, collections, LINQ, regex, serialization, and I/O with tiered severity classification. Use when analyzing .NET code for optimization opportunities, reviewing hot paths, or auditing allocation-heavy 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。
Configure and collect crash dumps for modern .NET applications. USE FOR: enabling automatic crash dumps for CoreCLR or NativeAOT, capturing dumps from running .NET processes, setting up dump collection in Docker or Kubernetes, using dotnet-dump collect or createdump. DO NOT USE FOR: analyzing or debugging dumps, post-mortem investigation with lldb/windbg/dotnet-dump analyze, profiling or tracing, or for .NET Framework processes.
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 reference system that returns the right reference in under 60 seconds. Use when setting up a design reference library, reorganizing existing collections, or helping teams build shared reference systems.
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, reviews, and improves SwiftData code using modern APIs and best practices. Use when reading, writing, or reviewing projects that use SwiftData.
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 guidance for designing, implementing, migrating, and debugging SwiftData persistence in Swift and SwiftUI apps. Use when working with @Model schemas, @Relationship/@Attribute rules, Query or FetchDescriptor data access, ModelContainer/ModelContext configuration, CloudKit sync, SchemaMigrationPlan/history APIs, ModelActor concurrency isolation, or Core Data to SwiftData adoption/coexistence.
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。
Writes, reviews, and improves Swift Testing code using modern APIs and best practices. Use when reading, writing, or reviewing projects that use Swift Testing.
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。
Reviews Swift code for concurrency correctness, modern API usage, and common async/await pitfalls. Use when reading, writing, or reviewing Swift concurrency 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。
Scan an iOS/macOS Xcode project for common App Store rejection patterns before submission. Use when preparing an app for App Store review, after receiving a rejection from Apple, or when auditing metadata, subscriptions, privacy manifests, entitlements, or design compliance. Integrates with the asc CLI for metadata inspection.
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 design, optimize, or evaluate App Store screenshots and preview videos. Also use when the user mentions "screenshots", "app preview", "product page design", "screenshot design", "creative assets", or "what should my screenshots show". For A/B testing screenshots, see ab-test-store-listing. For full ASO audit, 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。
Define, validate, run, resume, and audit repo-local multi-step automations with current `asc workflow` and `.asc/workflow.json`, including step outputs and safe release/TestFlight workflows.
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 improve their app's star rating, increase ratings volume, optimize when and how they prompt users for a review, or recover from a bad rating period. Use when the user mentions "app rating", "star rating", "review prompt", "SKStoreReviewRequest", "In-App Review API", "ask for review", "low rating", "rating drop", "get more reviews", or "recover from 1-star". For responding to reviews, see review-management. For overall ASO health, 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 reduce churn, improve user engagement, or increase lifetime value. Also use when the user mentions "retention", "churn", "users leaving", "engagement", "DAU/MAU", "user activation", or "why are users uninstalling". For onboarding-specific issues, see app-launch. For monetization, see monetization-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。
When the user wants to analyze, respond to, or improve their app reviews and ratings. Also use when the user mentions "reviews", "ratings", "negative reviews", "how to get more reviews", "review response", or "my rating is dropping". For broader ASO audit, see aso-audit. For retention issues causing bad reviews, 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。