| name | golang-samber-hot |
| description | In-memory caching in Golang using samber/hot — eviction algorithms (LRU, LFU, TinyLFU, W-TinyLFU, S3FIFO, ARC, TwoQueue, SIEVE, FIFO), TTL, cache loaders, sharding, stale-while-revalidate, missing key caching, and Prometheus metrics. Apply when using or adopting samber/hot, when the codebase imports github.com/samber/hot, or when the project repeatedly loads the same medium-to-low cardinality resources at high frequency and needs to reduce latency or backend pressure. |
| 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 WebFetch mcp__context7__resolve-library-id mcp__context7__query-docs AskUserQuestion |
Persona: You are a Go engineer who treats caching as a system design decision. You choose eviction algorithms based on measured access patterns, size caches from working-set data, and always plan for expiration, loader failures, and monitoring.
Using samber/hot for In-Memory Caching in Go
Generic, type-safe in-memory caching library for Go 1.22+ with 9 eviction algorithms, TTL, loader chains with singleflight deduplication, sharding, stale-while-revalidate, and Prometheus metrics.
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.
go get -u github.com/samber/hot
Algorithm Selection
Pick based on your access pattern — the wrong algorithm wastes memory or tanks hit rate.
| Algorithm | Constant | Best for | Avoid when |
|---|
| W-TinyLFU | hot.WTinyLFU | General-purpose, mixed workloads (default) | You need simplicity for debugging |
| LRU | hot.LRU | Recency-dominated (sessions, recent queries) | Frequency matters (scan pollution evicts hot items) |
| LFU | hot.LFU | Frequency-dominated (popular products, DNS) | Access patterns shift (stale popular items never evict) |
| TinyLFU | hot.TinyLFU | Read-heavy with frequency bias | Write-heavy (admission filter overhead) |
| S3FIFO | hot.S3FIFO | High throughput, scan-resistant | Small caches (<1000 items) |
| ARC | hot.ARC | Self-tuning, unknown patterns | Memory-constrained (2x tracking overhead) |
| TwoQueue | hot.TwoQueue | Mixed with hot/cold split |
