Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add alexastrum/skl --skill golang-samber-hotgit clone --depth 1 https://github.com/alexastrum/sklWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alexastrum/skl/golang-samber-hot)<a href="https://agentmods.dev/skills/alexastrum/skl/golang-samber-hot"><img src="https://agentmods.dev/badge/skills/alexastrum/skl/golang-samber-hot/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alexastrum/skl/golang-samber-hot"><img src="https://agentmods.dev/badge/skills/alexastrum/skl/golang-samber-hot.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00122 | $0.01861 |
| Opus 5.5 | $0.00049 | $0.00744 |
| Sonnet 5.5 | $0.00024 | $0.00372 |
| Haiku 4.5 | $0.00012 | $0.00186 |
Grade A, and why
golang-samber-hot scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
86% identical to golang-samber-hot — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 | 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) |
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 136 lines · 122 tokens per session scan A 76e10be2c732
golang-samber-hot is a skill published in the GitHub repository alexastrum/skl (10 stars, last pushed 4mo ago), licensed MIT. It adds 122 tokens to every session and 1,861 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 86% identical to golang-samber-hot, differing in 14 lines, and is treated as a copy.
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