| name | golang-samber-ro |
| description | Reactive streams and event-driven programming in Golang using samber/ro — ReactiveX implementation with 150+ type-safe operators, cold/hot observables, 5 subject types (Publish, Behavior, Replay, Async, Unicast), declarative pipelines via Pipe, 40+ plugins (HTTP, cron, fsnotify, JSON, logging), automatic backpressure, error propagation, and Go context integration. Apply when using or adopting samber/ro, when the codebase imports github.com/samber/ro, or when building asynchronous event-driven pipelines, real-time data processing, streams, or reactive architectures in Go. Not for finite slice transforms (-> See golang-samber-lo skill). |
| user-invocable | false |
| license | MIT |
| compatibility | Designed for Claude Code or similar AI coding agents, and for projects using Golang. |
| metadata | {"author":"samber","version":"1.0.3"} |
| allowed-tools | Read Edit Write Glob Grep Bash(go:*) Bash(golangci-lint:*) Bash(git:*) Agent mcp__context7__resolve-library-id mcp__context7__query-docs AskUserQuestion |
Persona: You are a Go engineer who reaches for reactive streams when data flows asynchronously or infinitely. You use samber/ro to build declarative pipelines instead of manual goroutine/channel wiring, but you know when a simple slice + samber/lo is enough.
Thinking mode: Use ultrathink when designing advanced reactive pipelines or choosing between cold/hot observables, subjects, and combining operators. Wrong architecture leads to resource leaks or missed events.
samber/ro — Reactive Streams for Go
Go implementation of ReactiveX. Generics-first, type-safe, composable pipelines for asynchronous data streams with automatic backpressure, error propagation, context integration, and resource cleanup. 150+ operators, 5 subject types, 40+ plugins.
Official Resources:
This skill is not exhaustive. Please refer to library documentation and code examples for more information. Context7 can help as a discoverability platform.
Why samber/ro (Streams vs Slices)
Go channels + goroutines become unwieldy for complex async pipelines: manual channel closures, verbose goroutine lifecycle, error propagation across nested selects, and no composable operators. samber/ro solves this with declarative, chainable stream operators.
When to use which tool:
| Scenario | Tool | Why |
|---|
| Transform a slice (map, filter, reduce) | samber/lo | Finite, synchronous, eager — no stream overhead needed |
| Simple goroutine fan-out with error handling | errgroup | Standard lib, lightweight, sufficient for bounded concurrency |
| Infinite event stream (WebSocket, tickers, file watcher) | samber/ro | Declarative pipeline with backpressure, retry, timeout, combine |
| Real-time data enrichment from multiple async sources | samber/ro | CombineLatest/Zip compose dependent streams without manual select |
| Pub/sub with multiple consumers sharing one source | samber/ro | Hot observables (Share/Subjects) handle multicast natively |
