「best」の検索結果

Get best practices for developing applications with Spring Boot and Kotlin.

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Socratic mentoring for junior developers and AI newcomers. Guides through questions, never answers. Triggers: "help me understand", "explain this code", "I'm stuck", "Im stuck", "I'm confused", "Im confused", "I don't understand", "I dont understand", "can you teach me", "teach me", "mentor me", "guide me", "what does this error mean", "why doesn't this work", "why does not this work", "I'm a beginner", "Im a beginner", "I'm learning", "Im learning", "I'm new to this", "Im new to this", "walk me through", "how does this work", "what's wrong with my code", "what's wrong", "can you break this down", "ELI5", "step by step", "where do I start", "what am I missing", "newbie here", "junior dev", "first time using", "how do I", "what is", "is this right", "not sure", "need help", "struggling", "show me", "help me debug", "best practice", "too complex", "overwhelmed", "lost", "debug this", "/socratic", "/hint", "/concept", "/pseudocode". Progressive clue systems, teaching techniques, and success metrics.

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Ensure that Java types are documented with Javadoc comments and follow best practices for documentation.

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Best practices for writing JavaScript/TypeScript tests using Jest, including mocking strategies, test structure, and common patterns.

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Get best practices for JUnit 5 unit testing, including data-driven tests

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GraalVM Native Image expert that adds native image support to Java applications, builds the project, analyzes build errors, applies fixes, and iterates until successful compilation using Oracle best practices.

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Get best practices for developing applications with Spring Boot.

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Use this skill to get context about Fabric Lakehouse and its features for software systems and AI-powered functions. It offers descriptions of Lakehouse data components, organization with schemas and shortcuts, access control, and code examples. This skill supports users in designing, building, and optimizing Lakehouse solutions using best practices.

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Get best practices for Entity Framework Core

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Best practices for git workflow automation including atomic commits, branch naming, conventional commit format, and changelog generation.

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Use this skill whenever the user mentions IP geolocation feeds, RFC 8805, geofeeds, or wants help creating, tuning, validating, or publishing a self-published IP geolocation feed in CSV format. Intended user audience is a network operator, ISP, mobile carrier, cloud provider, hosting company, IXP, or satellite provider asking about IP geolocation accuracy, or geofeed authoring best practices. Helps create, refine, and improve CSV-format IP geolocation feeds with opinionated recommendations beyond RFC 8805 compliance. Do NOT use for private or internal IP address management — applies only to publicly routable IP addresses.

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Generates a comprehensive and best-practice-oriented .editorconfig file based on project analysis and user preferences.

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Ensure that C# types are documented with XML comments and follow best practices for documentation.

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Get best practices for C# async programming

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Get best practices for MSTest 3.x/4.x unit testing, including modern assertion APIs and data-driven tests

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Get best practices for NUnit unit testing, including data-driven tests

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Get best practices for XUnit unit testing, including data-driven tests

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Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file

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Generate production-ready Python code using Dataverse SDK with error handling, optimization, and best practices

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Get best practices for TUnit unit testing, including data-driven tests

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Comprehensive Blazor development expertise covering Blazor Server, WebAssembly, and Hybrid apps. Use when building Blazor components, implementing state management, handling routing, JavaScript interop, forms and validation, authentication, or optimizing Blazor applications. Includes best practices, architecture patterns, and troubleshooting guidance.

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Triage and resolve Arch Linux issues with pacman, systemd, and rolling-release best practices.

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OpenAI's general-purpose speech recognition model. Supports 99 languages, transcription, translation to English, and language identification. Six model sizes from tiny (39M params) to large (1550M params). Use for speech-to-text, podcast transcription, or multilingual audio processing. Best for robust, multilingual ASR.

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Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.

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