Total 31,189 skills, Backend Development has 3057 skills
Showing 12 of 3057 skills
Generate Python FastAPI code following project design patterns. Use when creating models, schemas, repositories, services, controllers, database migrations, authentication, or tests. Enforces layered architecture, async patterns, OWASP security, and Alembic migration naming conventions (yyyymmdd_HHmm_feature).
Use when working with JavaScript in WordPress plugins or themes. Covers wp_enqueue_script, wp_localize_script, wp_add_inline_script, jQuery in WordPress (noConflict mode, $.ajax), AJAX handlers (wp_ajax_, admin-ajax.php, wp_create_nonce, check_ajax_referer), wp.ajax, wp.apiFetch (wp-api-fetch), wp-util and wp.template (Underscore templates), Heartbeat API, script dependencies, defer/async loading strategies (WordPress 6.3+), wp_set_script_translations, and frontend-backend communication patterns.
Domain-Driven Design system for software development. Use when designing new systems with DDD principles, refactoring existing codebases toward DDD, generating code scaffolding (entities, aggregates, repositories, domain events), facilitating Event Storming sessions, creating bounded context maps, or performing code reviews with a DDD lens. Covers both strategic design (bounded contexts, subdomains, context maps, ubiquitous language) and tactical design (entities, value objects, aggregates, domain services, repositories). Supports all major architecture patterns (Hexagonal/Ports & Adapters, CQRS, Event Sourcing, Clean Architecture) with language-agnostic guidance and concrete examples in Python and TypeScript.
Build MCP servers using the LeanMCP SDK with decorator-based TypeScript. Use this skill when users ask for "leanmcp", "MCP with decorators", "MCP with authentication", "MCP with elicitation", "MCP with environment injection", or want a simpler, more elegant way to build MCP servers. LeanMCP provides automatic schema generation, dependency injection, authentication, and user input collection.
Build FastAPI applications using Clean Architecture principles with proper layer separation (Domain, Infrastructure, API), dependency injection, repository pattern, and comprehensive testing. Use this skill when designing or implementing Python backend services that require maintainability, testability, and scalability.
Use when writing database access code, creating schemas, or managing transactions with PostgreSQL - enforces transaction safety with TX_ naming, read-write separation, type safety for UUIDs/JSONB, and snake_case conventions to prevent data corruption and type errors
Expert guidance for building production-ready FastAPI applications with modular architecture where each business domain is an independent module with own routes, models, schemas, services, cache, and migrations. Uses UV + pyproject.toml for modern Python dependency management, project name subdirectory for clean workspace organization, structlog (JSON+colored logging), pydantic-settings configuration, auto-discovery module loader, async SQLAlchemy with PostgreSQL, per-module Alembic migrations, Redis/memory cache with module-specific namespaces, central httpx client, OpenTelemetry/Prometheus observability, conversation ID tracking (X-Conversation-ID header+cookie), conditional Keycloak/app-based RBAC authentication, DDD/clean code principles, and automation scripts for rapid module development. Use when user requests FastAPI project setup, modular architecture, independent module development, microservice architecture, async database operations, caching strategies, logging patterns, configuration management, authentication systems, observability implementation, or enterprise Python web services. Supports max 3-4 route nesting depth, cache invalidation patterns, inter-module communication via service layer, and comprehensive error handling workflows.
Write systems code in the style of Linus Torvalds, creator of Linux and Git. Emphasizes pragmatic excellence, performance awareness, subsystem design, and uncompromising code review. Use when writing kernel-level code or high-performance systems.
System Architect Specialist. Use this to design system architecture, creating C4 models and ADRs (Decision Records).
Professional Pydantic v2.12 development for data validation, serialization, and type-safe models. Use when working with Pydantic for (1) creating or modifying BaseModel classes, (2) implementing validators and serializers, (3) configuring model behavior, (4) handling JSON schema generation, (5) working with settings management, (6) debugging validation errors, (7) integrating with ORMs or APIs, or (8) any production-grade Python data validation tasks. Includes complete API reference, concept guides, examples, and migration patterns.
Real-time communication patterns with WebSocket, Socket.io, Server-Sent Events, and scaling strategies
Distributed locking patterns with Redis and PostgreSQL for coordination across instances. Use when implementing exclusive access, preventing race conditions, or coordinating distributed resources.