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Energy Readings Duplicate Key Report
x402
Energy Readings Duplicate Key Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Identifies duplicate composite keys (meter + date combinations) across a batch of up to 200 energy reading records
Price / call$0.01
Success—
StatusUnknown
How this service works
Energy readings - Duplicate key report: Duplicate key report for Energy readings. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded duplicate key report deliverable.
Output
A report identifying which records share duplicate composite keys (meter + date), including the affected row IDs and the conflicting key values, enabling the caller to locate and resolve data collisions within the submitted batch of up to 200 energy reading records.
Example use cases
Audit uploaded meter data before ingestion
“Before I load these 150 energy meter readings into our database, can you scan them for any duplicate meter-and-date combinations so I can fix conflicts first? Here are the records with row IDs, meter names, dates, kWh, and costs.”
Detect ETL pipeline duplicates
“Our ETL job processed energy readings from two sources and I think some rows got duplicated — can you run a duplicate key check on this batch of 80 records to tell me which meter-date pairs appear more than once?”
Validate energy billing data quality
“I'm preparing monthly billing data for 120 meters and need to make sure no meter has two readings logged on the same date — can you identify any duplicate meter-date keys in this dataset?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-analytics-energy-readings-key-duplicates?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, local duplicate-key detection on energy meter reading records (meter + date composite key) without sending data to external enrichment services. It is ideal for pre-ingestion data quality checks, ETL pipeline validation, and billing data audits where privacy or latency matters. Prefer alternatives if you need forecasting, anomaly detection, or enrichment beyond key-collision reporting.
Side effects
- Batch exceeds 200 items — request rejected with validation error
- row_id missing or empty — record fails schema validation
- date not in YYYY-MM-DD format — schema pattern validation error
- No duplicates found — report returns empty duplicate list (not an error)
- Numeric fields (kwh, cost) out of allowed range — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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