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Cache Observations Base-100 Series Analytics
x402
Cache Observations Base-100 Series Analytics is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).
Computes a base-100 indexed series for cache hit or miss observations across up to 200 dated records, enabling normalized trend comparison anchored to a chosen baseline row.
Price / call$0.01
Success—
StatusUnknown
How this service works
Cache observations - Base-100 series: Base-100 series for Cache observations. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded base-100 series report.
Output
Returns a base-100 indexed series report for the selected field (hits or misses) across all supplied cache observation rows, normalized so the chosen base_index row equals 100. Includes local descriptive analytics (no external enrichment or forecasting). Each row in the output reflects its value as a percentage of the baseline row's value.
Example use cases
Normalize cache hit trends over a month
“I have daily cache hit counts for two cache groups across October — can you build a base-100 index series for hits, anchored to the first day (row index 0), so I can compare how each group's performance has changed relative to that starting point?”
Benchmark cache miss rates across groups
“Here are 30 days of cache miss data for caches named 'cdn-east' and 'cdn-west' — generate a base-100 series for misses, using row 0 as the baseline, so I can see which cache's miss rate grew faster.”
Detect cache performance regression from a reference date
“I want to check if our cache hit rate degraded after a deploy — I have daily hit and miss data for 'prod-cache' from the past two weeks. Can you index the hits as a base-100 series starting from row 0 so I can see the relative change since that reference date?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-cache-observations-index?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a simple, fast, local base-100 normalization of cache hit or miss time-series data without external dependencies, enrichment, or forecasting. It is ideal for comparing relative performance trends across multiple cache groups anchored to a reference observation, at very low cost ($0.01 USDC). Prefer alternatives if you also need correlation analysis, forecasting, or enrichment alongside the index.
Side effects
- Fewer than 1 row supplied — minimum of 1 row required
- More than 200 rows supplied — maximum of 200 rows enforced
- base_index references a row index out of bounds for the supplied array
- base_index row has a zero or null value for the selected field, causing division-by-zero in normalization
- Missing required fields (row_id, cache, date, hits, misses) on any row
- Invalid date format — must match YYYY-MM-DD pattern
- Numeric values outside the allowed range (±1,000,000,000,000)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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