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Found 8 Skills
Use when writing or reviewing asyncio code in Jupyter notebooks or '#%%' cell workflows — structuring event-loop ownership, orchestrating async tasks, or choosing compatibility strategies. Also use when hitting RuntimeError: This event loop is already running, asyncio.run() failures in cells, or tasks silently never completing.
Investigate slow requests, event-loop stalls, GC pressure, and stream backpressure using Phargus data. Use for a runtime incident or alert that needs evidence-backed hypotheses and a next experiment.
Selects and implements NestJS runtime features, error and API contracts, security, testing, DevOps, performance, and safe scale. Use for middleware, guards, pipes, interceptors, exception filters, typed failures/results, Problem Details, validation errors, HTTP/GraphQL/RPC/gRPC/WebSocket error mapping, deadlines, cancellation, retry classification, fatal process errors, authentication, authorization, caching, queues, schedulers, CI/CD, containers, Kubernetes, configuration and secrets, migrations, supply-chain controls, health probes, logs/metrics/traces, SLOs and alerts, incident recovery, rollout and rollback, event-loop or database bottlenecks, load tests, horizontal scaling, idempotency, backpressure, and graceful shutdown. Do not use for frontend-only performance or non-NestJS services. When other skills also apply, reconcile ownership before mutation.
Read-only audit of performance and reliability — event-loop discipline, streaming and backpressure, memory and CPU diagnostics, shutdown/timeout/job habits, resilience topology (circuit breakers, retry budgets, queue bounds), and frontend delivery (Core Web Vitals, bundle size, hydration) — with evidence per finding and a SHIP / FIX / BLOCK verdict. Use when a service or page is slow, memory climbs, tail latency is bad, a worker OOMs, before a load event, or 'почему тормозит'. Measures and reports; rewrites no hot paths. Do not use for retry/idempotency contracts (awesome-error-standards) or render style rules (awesome-code-standards).
Subprocess and concurrency discipline for Python: how to run external programs safely, and how to pick the right concurrency model instead of the habitual one. Use when spawning processes with subprocess or asyncio subprocesses, writing threading or ThreadPoolExecutor code, using multiprocessing or ProcessPoolExecutor, sizing worker pools, bounding fan-out, or diagnosing deadlocks, hangs, orphaned children, and zombie processes. Covers argv vs shell, timeouts that kill the whole process tree, pipe deadlocks, start methods (spawn/forkserver/fork), pickling limits, GIL and free-threading, and cancellation. For event-loop and coroutine rules (TaskGroup, blocking calls, cancellation), use python-async-best-practices instead.
Complete guide for asyncio concurrency patterns including event loops, coroutines, tasks, futures, async context managers, and performance optimization
Expert guidance on SwiftNIO best practices, patterns, and implementation. Use when developers mention: (1) SwiftNIO, NIO, ByteBuffer, Channel, ChannelPipeline, ChannelHandler, EventLoop, NIOAsyncChannel, or NIOFileSystem, (2) EventLoopFuture, ServerBootstrap, or DatagramBootstrap, (3) TCP/UDP server or client implementation, (4) ByteToMessageDecoder or wire protocol codecs, (5) binary protocol parsing or serialization, (6) blocking the event loop issues.
Node.js server-side JavaScript runtime with npm ecosystem. Use for backend development.