zhukang 1c7abd81d1 All 310 Manus skill-hub community skills as a Kortix marketplace registry

- 310 registry:skill items, 1528 files, 7 categories (hub tags)
- registry.json generated by @kortix/registry buildRegistry
- nested SKILL.md in sn-da-* renamed SUBSKILL.md (no phantom skills)
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2026-09-15 13:37:20 +08:00

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title

impact

Choose the right enrichment path: JOIN, dictionary, denormalization, or precomputed enrichment

Principle

Not every dimension lookup should remain a runtime JOIN. The right design depends on dimension volatility, cardinality, and the cost profile of repeated enrichment.

Decision framework

Condition	Recommendation	Category
Small, slowly changing lookup table used in many queries	Dictionary	official
Dimension is naturally embedded and storage duplication is acceptable	Denormalize	derived
Join logic is complex and refreshed on a schedule	Refreshable MV	official
Query is exploratory or infrequent and dimensions change often	Runtime JOIN	official

Guidance

Recommendation: dictionaries for repeated low-latency lookups

Why Dictionaries are often the best fit for repeated key-based enrichment when the lookup data is relatively static.

Official sources

https://clickhouse.com/docs/en/sql-reference/dictionaries
query-join-consider-alternatives

Recommendation: denormalize when operationally simple

Why If the dimension is stable and queried constantly, denormalization may outperform repeated joins.

Category derived

Official context

https://clickhouse.com/docs/best-practices/minimize-optimize-joins

Recommendation: use refreshable or incremental MVs for structured enrichment

Why Precomputed enrichment is often better than expensive runtime joins for recurring production queries.