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From temporal-data
Implements incremental sync and cache validation using system_from/system_to temporal columns. Covers global watermarks, predicate watermarks, and item-level conditional requests.
How this skill is triggered — by the user, by Claude, or both
Slash command
/temporal-data:temporal-cachingThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
System-time versioned tables give you a built-in cache validator: `system_from` changes whenever a record is updated. This eliminates the need for separate version columns, ETags tables, or change-tracking infrastructure.
System-time versioned tables give you a built-in cache validator: system_from changes whenever a record is updated. This eliminates the need for separate version columns, ETags tables, or change-tracking infrastructure.
Three patterns leverage this at different granularities:
Client stores the maximum system_from seen across an entire collection. On each poll, asks "give me everything newer than X." Empty result means nothing changed — no data transfer needed.
Best for: feeds, dashboards, lists sorted by recency where you need to detect any change across a large collection.
The "one" side of a one-to-many relationship stores the maximum system_from of its children as a denormalized column. Clients can check this single value before deciding whether to fetch the entire child collection.
Best for: parent-child relationships where fetching all children is expensive but checking the parent is cheap.
Client sends the last-known system_from for a specific item in the request header. Server returns HTTP 304 if the item hasn't changed. Maps directly to standard HTTP conditional request semantics (ETags).
Best for: individual resource endpoints where clients repeatedly fetch the same item.
| Scenario | Pattern | Why |
|---|---|---|
| "Show me what's new since I last checked" | Global watermark | One query covers the whole collection |
| "Have any of this user's blueprints changed?" | Predicate watermark | Avoids fetching all blueprints to find out |
| "Give me blueprint X if it changed" | Item watermark | Standard HTTP caching for single resources |
| Feed page with detail drill-down | Global + Item | Global for the list, item for individual views |
npx claudepluginhub motlin/claude-code-plugins --plugin temporal-dataProvides patterns for implementing system-time versioned tables: schema design with system_from/system_to columns, primary key conventions, deduplication, and contiguous timeline logic.
Models valid-time, transaction-time, and bitemporal data in SQL, using range types and exclusion constraints for history tracking and audit queries.
Provides caching strategies (Cache-Aside, Read-Through, Write-Through, Write-Behind), invalidation approaches, multi-level caching, and Redis data structures for audits and generation.