golang-samber-hot
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.
93
93%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that is highly specific, comprehensive, and distinctive. It names the exact library, lists concrete features and algorithms, provides the import path as a trigger, and includes a clear 'Apply when' clause covering both direct library usage and broader use-case scenarios. The third-person voice is used correctly throughout.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete capabilities: eviction algorithms (with named variants), TTL, cache loaders, sharding, stale-while-revalidate, missing key caching, and Prometheus metrics. Highly detailed and actionable. | 3 / 3 |
Completeness | Clearly answers both 'what' (in-memory caching with specific features) and 'when' with explicit triggers ('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...'). | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'caching', 'Golang', 'samber/hot', 'LRU', 'LFU', 'TTL', 'sharding', 'Prometheus metrics', 'reduce latency', 'backend pressure', and the full import path 'github.com/samber/hot'. Excellent coverage of both library-specific and general caching terms. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive — scoped to a specific Go library (samber/hot) with named eviction algorithms and a specific import path. Very unlikely to conflict with generic caching skills or other language-specific caching tools. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a high-quality skill that efficiently covers algorithm selection, core usage patterns, capacity sizing, common pitfalls, and best practices for samber/hot. Its strengths are excellent conciseness, actionable code examples, and well-structured progressive disclosure. The main weakness is the lack of an explicit end-to-end workflow with validation/feedback loops for adopting and tuning the cache in production.
Suggestions
Add a brief end-to-end adoption workflow (e.g., 1. Choose algorithm → 2. Size cache → 3. Configure with TTL/jitter/janitor → 4. Deploy → 5. Monitor hit rate via Prometheus → 6. If hit rate < SLO, adjust capacity or algorithm → repeat) with explicit validation checkpoints.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is lean and efficient throughout. It assumes Claude knows Go, caching concepts, and library conventions. No unnecessary explanations of what caching is or how Go generics work. Every section delivers actionable information without padding. | 3 / 3 |
Actionability | Provides fully executable Go code for basic cache setup, loader pattern, and TTL configuration. The algorithm selection table gives concrete constants to use. Capacity sizing includes a worked numeric example. Common mistakes list specific failure modes (panics, OOM) with exact causes. | 3 / 3 |
Workflow Clarity | The capacity sizing section has a clear 3-step process, and the common mistakes section serves as implicit validation checkpoints. However, there's no explicit workflow for the overall cache adoption process (measure → choose algorithm → size → configure → monitor → tune), and no feedback loop for validating that the cache is working correctly after setup (e.g., check hit rate → adjust capacity → re-check). | 2 / 3 |
Progressive Disclosure | Excellent structure with a concise overview in the main file and clear one-level-deep references to algorithm-guide.md, production-patterns.md, and api-reference.md. Cross-references to related skills are well-organized. Content is appropriately split between the overview and referenced files. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_field | 'metadata' should map string keys to string values | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
- Repository
- samber/cc-skills-golang
- Commit
b88f91d
- Reviewed
Table of Contents
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