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Found 199 Skills
React render performance patterns including React Compiler integration, memoization strategies, TanStack Virtual, and DevTools profiling. Use when debugging slow renders, optimizing large lists, or reducing unnecessary re-renders.
Use when planning system architecture to ensure nothing is missed. Provides structured questions covering scalability, security, data, and operational dimensions before implementation.
Agentic workflow patterns for autonomous LLM reasoning. Use when building ReAct agents, implementing reasoning loops, or creating LLMs that plan and execute multi-step tasks.
Long-term semantic memory across sessions using Mem0. Use when you need to remember, recall, or forget information across sessions, or when referencing what we discussed last time or in a previous session.
DDD aggregate design patterns for consistency boundaries and invariants. Use when designing aggregate roots, enforcing business invariants, handling cross-aggregate references, or optimizing aggregate size.
FastAPI advanced patterns including lifespan, dependencies, middleware, and Pydantic settings. Use when configuring FastAPI lifespan events, creating dependency injection, building Starlette middleware, or managing async Python services with uvicorn.
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.
Creates commits with conventional format and validation. Use when committing changes or generating commit messages.
Visualize planned changes before implementation. Use when reviewing plans, comparing before/after architecture, assessing risk, or analyzing execution order and impact.
Complete git workflow patterns including GitHub Flow branching, atomic commits with interactive staging, merge and rebase strategies, and recovery operations using reflog. Essential patterns for clean history. Use when managing branches, defining branching strategy, or recovering git history.
Unit testing patterns for isolated business logic tests — AAA pattern, parametrized tests (test.each, @pytest.mark.parametrize), fixture scoping (function/module/session), mocking with MSW/VCR at network level, and test data management with factories (FactoryBoy, faker-js). Use when writing unit tests, setting up mocks, structuring test data, optimizing test speed, choosing fixture scope, or reducing test boilerplate. Covers Vitest, Jest, pytest.
Integration and contract testing patterns — API endpoint tests, component integration, database testing, Pact contract verification, property-based testing, and Zod schema validation. Use when testing API boundaries, verifying contracts, or validating cross-service integration.