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Cache Observations Record Quality Audit
x402
Cache Observations Record Quality Audit is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Audits the data quality of up to 200 cache observation records (hits, misses, date, cache group) and returns a local descriptive analytics report.
Price / call$0.01
Success—
StatusUnknown
How this service works
Cache observations - Record quality audit: Record quality audit 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 record quality audit report.
Output
A bounded record quality audit report containing descriptive analytics about the submitted cache observation records, including assessments of data completeness, validity of field values (dates, numeric ranges), and any detected quality issues — no enrichment or forecasting is included.
Example use cases
Pre-pipeline cache data validation
“Before I load my cache metrics into the data warehouse, can you audit the quality of these 50 cache observation records — check for missing values, invalid dates, or out-of-range hit/miss counts across group-a and group-b entries?”
Debugging anomalous cache hit rates
“I'm seeing weird numbers in my cache dashboard. Can you run a quality audit on these 30 cache observation rows for my CDN caches from October 2026 so I can figure out if it's a data problem before I dig into the actual performance issue?”
Routine data quality check for ops reporting
“Every week I need to verify our cache observation logs are clean before the ops report goes out — can you audit this batch of 100 records covering our primary and fallback cache groups and tell me if anything looks off?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-cache-observations-quality?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, cheap ($0.01 USDC) data quality check specifically on cache observation records (hits, misses, date, cache group) before downstream processing or reporting. It is ideal for validating small-to-medium batches (up to 200 rows) of cache performance data locally without requiring enrichment or forecasting. Prefer alternatives if you need cache performance forecasting, anomaly detection, or enrichment with external data sources.
Side effects
- Empty rows array (minItems:1 violation) returns a validation error
- Rows exceeding 200 items (maxItems:200) are rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, cache, date, hits, misses) triggers an error
- Non-numeric values in hits or misses fields cause type validation failure
- Duplicate row_id values may cause ambiguous audit results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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