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Found 316 Skills
System architecture guidance for Python/React full-stack projects. Use during the design phase when making architectural decisions — component boundaries, service layer design, data flow patterns, database schema planning, and technology trade-off analysis. Covers FastAPI layer architecture (Routes/Services/Repositories/Models), React component hierarchy, state management, and cross-cutting concerns (auth, errors, logging). Produces architecture documents and ADRs. Does NOT cover implementation (use python-backend-expert or react-frontend-expert) or API contract design (use api-design-patterns).
Track which optimization experiment was best. Use when you've run multiple optimization passes, need to compare experiments, want to reproduce past results, need to pick the best prompt configuration, track experiment costs, manage optimization artifacts, decide which optimized program to deploy, or justify your choice to stakeholders. Covers experiment logging, comparison, and promotion to production.
Idiomatic Go HTTP middleware patterns with context propagation, structured logging via slog, centralized error handling, and panic recovery. Use when writing middleware, adding request tracing, or implementing cross-cutting concerns.
Complete development skill set for the ABE Framework, providing a full-stack solution for modern Go HTTP RESTful API application development. Core features include: modular engine architecture, standardized controller route registration, global and route-level middleware system, dependency injection container (supporting global and request-level scopes), multi-language internationalization (i18n) support, access control system based on JWT and Casbin, asynchronous event bus mechanism, high-performance goroutine pool management, extensible plugin mechanism, configuration management system (supporting multi-layer configuration priority), GORM database integration, structured logging system, form validation framework, scheduled task scheduling (Cron), CORS cross-domain support, etc. Suitable for scenarios such as building enterprise-level web services, microservice architecture applications, API gateways, and backend management systems. The framework adopts a loose-coupling design, supports the UseCase business logic pattern, provides a complete error handling mechanism and performance monitoring capabilities, helping enterprises quickly build stable and maintainable distributed application systems.
Implement middleware for authentication, logging, CORS, and request processing. Use for cross-cutting concerns and request/response modification.
Implement request logging, tracing, and observability. Use for debugging, monitoring, and production observability.
Observability patterns for Python applications. Triggers on: logging, metrics, tracing, opentelemetry, prometheus, observability, monitoring, structlog, correlation id.
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.
Exclusive skill set for the GoFrame development framework. Provides a complete framework usage guide for Go language developers, covering best practices for core components such as command-line management, configuration management, logging components, error handling, data validation, type conversion, cache management, template engines, database ORM, and I18n internationalization. Includes project engineering structure specifications, development model guidelines, solutions to common problems, and rich practical code examples. Suitable for building various Go projects such as RESTful APIs, gRPC microservices, and web applications, helping developers quickly master the features of the GoFrame framework and improve development efficiency and code quality.
Microservice Infrastructure Guide, covering core infrastructure of microservice architecture such as conditional configuration, event-driven architecture, inter-service communication, internationalization and logging. It is used when users implement inter-service calls, configure multi-environments, implement asynchronous communication, handle internationalization or standardize log output.
Implements comprehensive observability with OpenTelemetry tracing, Prometheus metrics, and structured logging. Includes instrumentation plans, sample dashboards, and alert candidates. Use for "observability", "monitoring", "tracing", or "metrics".
Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse LLM tracing, and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.