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Found 316 Skills
Initialize Spec-Driven Development context in any project. Detects stack, conventions, and bootstraps the active persistence backend. Trigger: When user wants to initialize SDD in a project, or says "sdd init", "iniciar sdd", "openspec init".
Build responsive, interactive dashboard layouts with Syncfusion React Dashboard Layout component. Implement draggable and resizable panels, responsive grid systems, dynamic panel management, and state persistence. This skill covers multi-column layouts, floating panel arrangement, extensive customization, drag-drop panel rearrangement, and state management for React applications.
Help developers build with Chainlink Data Streams, including credentials guidance, report decoding, REST and WebSocket report retrieval with official Go/Rust/TypeScript SDKs, High Availability streaming, on-chain report verification, real-time frontend displays, report schema guidance, SQLite persistence, and timestamp lookback. Use this skill whenever the user mentions Chainlink Data Streams, Streams Direct, Data Streams reports, report schemas, report decoding, data-streams-sdk, or real-time low-latency market data from Chainlink.
Use when working with SwiftData - @Model definitions, @Query in SwiftUI, @Relationship macros, ModelContext patterns, CloudKit integration, iOS 26+ features, and Swift 6 concurrency with @MainActor — Apple's native persistence framework
Expert blueprint for save/load systems using JSON/binary serialization, PERSIST group pattern, versioning, and migration. Covers player progress, settings, game state persistence, and error recovery. Use when implementing save systems OR data persistence. Keywords save, load, JSON, FileAccess, user://, serialization, version migration, PERSIST group.
Configure Akka.NET with .NET Aspire for local development and production deployments. Covers actor system setup, clustering, persistence, Akka.Management integration, and Aspire orchestration patterns.
Model Kotlin persistence code correctly for Spring Data JPA and Hibernate. Covers entity design, identity and equality, uniqueness constraints, relationships, fetch plans, and common ORM (Object-Relational Mapping) traps specific to Kotlin. Use when creating or reviewing JPA (Java Persistence API) entities, diagnosing N+1 or LazyInitializationException, placing indexes and uniqueness rules, or preventing Kotlin-specific bugs such as data class entities and broken equals/hashCode.
Use when you need data access with Quarkus Hibernate ORM Panache — including PanacheEntity / PanacheEntityBase, PanacheRepository, named and HQL queries, DTO projections (project(Class)), pagination (Page.of()), N+1 avoidance (JOIN FETCH), optimistic locking (@Version / OptimisticLockException), @NamedQuery for validated reusable queries, transactions, @TestTransaction for test isolation, and immutable-friendly patterns. This is the Quarkus analogue to Spring Data for relational persistence. Part of the skills-for-java project
Apply when working with MasterData v2 entities, schemas, or MasterDataClient in VTEX IO apps, or when anyone designing or implementing a solution must scrutinize whether Master Data is the correct storage. The skill prompts hard questions: native Catalog or other VTEX stores, OMS, or an external database may be better; do not default to MD because it is convenient. Covers JSON Schema, CRUD, triggers, search and scroll, schema lifecycle, purchase-path avoidance, single source of truth, and BFF handoffs. Use for justified custom persistence while avoiding the 60-schema limit.
Build durable workflows with Cloudflare Workflows (GA April 2025). Features step.do, step.sleep, waitForEvent, Vitest testing, automatic retries, and state persistence for long-running tasks. Prevents 12 documented errors. Use when: creating workflows, implementing retries, or troubleshooting NonRetryableError, I/O context, serialization errors, waitForEvent timeouts, getPlatformProxy failures.
This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.
Provides comprehensive guidance for Redis including data structures, commands, pub/sub, persistence, clustering, and caching patterns. Use when the user asks about Redis, needs to use Redis for caching, implement Redis data structures, or work with Redis features.