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Found 2,628 Skills
Plans and executes safe refactoring with tests as a safety net. Use when restructuring code, extracting functions, renaming across files, or simplifying complex logic without changing behavior.
Social feed with batch queries, cursor pagination, trending algorithms, and engagement tracking. Efficient database queries for infinite scroll feeds.
Structured JSON logging with correlation IDs, request context propagation across async boundaries, performance timing decorators, and worker metrics collection.
Centralized transformation logic for consistent data shaping across API routes. Includes aggregators, rankers, trend calculators, and data sanitizers.
Implement flash messages for one-time notifications across redirects. Use for success/error messages after form submissions.
Configure Cross-Origin Resource Sharing (CORS) and security headers. Use for APIs accessed from browsers on different domains.
Implement middleware for authentication, logging, CORS, and request processing. Use for cross-cutting concerns and request/response modification.
Use when managing multiple initiatives across time horizons (now/next/later, H1/H2/H3), balancing risk vs return across portfolio, sizing and sequencing bets with dependencies, setting exit/scale criteria for experiments, allocating resources across innovation types (core/adjacent/transformational), or when user mentions portfolio planning, roadmap horizons, betting framework, initiative prioritization, innovation portfolio, or resource allocation across horizons.
CLI for Limitless.ai Pendant with lifelog management, FalkorDBLite semantic graph, vector embeddings, and DAG pipelines. Use for personal memory queries, semantic search across lifelogs/chats/persons/topics, entity extraction, and knowledge graph operations. Triggers include "lifelog", "pendant", "limitless", "personal memory", "semantic search", "graph query", "extraction".
Manage long-running agent sessions. Use for tracking progress in extended tasks, maintaining context across long sessions, and managing multi-step workflows.
Comprehensive guide for production-ready Python backend development and software architecture at scale. Use when designing APIs, building backend services, creating microservices, structuring Python projects, implementing database patterns, writing async code, or any Python backend/server-side development task. Covers Clean Architecture, Domain-Driven Design, Event-Driven Architecture, FastAPI/Django patterns, database design, caching strategies, observability, security, testing strategies, and deployment patterns for high-scale production systems.
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.