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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.
Passed 21 of 22 test cases with the skill, and 12 of 22 without it.
and 10 more in the full report
9 fixed13 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
When initializing a `samber/hot` cache with background expired entry cleanup via `.WithJanitor()`, what cleanup method must be deferred immediately after `.Build()` to ensure background resources are freed when the cache is no longer needed?
| Checked | Without skill | With skill |
|---|---|---|
| Calls defer cache.StopJanitor() | Missed | Passed |
The instructions your model reads when the skill loads.
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.
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 — refer to library documentation and code examples for more information:
samber/cc-skills-golang@golang-pkg-go-dev skill (godig), preferred over Context7 for Go package facts.samber/cc-skills-golang@golang-gopls skill (gopls).go get -u github.com/samber/hot
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 | Tuning complexity is unacceptable |
| SIEVE | hot.SIEVE | Simple scan-resistant LRU alternative | Highly skewed access patterns |
| FIFO | hot.FIFO | Simple, predictable eviction order | Hit rate matters (no frequency/recency awareness) |
Decision shortcut: Start with hot.WTinyLFU. Switch only when profiling shows the miss rate is too high for your SLO.
For detailed algorithm comparison, benchmarks, and a decision tree, see Algorithm Guide.
test cases passed, vs 12 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.