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File Ingestion Duplicate Key Report
x402
File Ingestion 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 2026-10-20).
Analyzes up to 200 file ingestion records and returns a duplicate key report identifying repeated row IDs across the dataset.
Price / call$0.01
Success—
StatusUnknown
How this service works
File ingestion - Duplicate key report: Duplicate key report for File ingestion. 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 duplicate key report report.
Output
A bounded descriptive analytics report identifying which row_id values appear more than once across the submitted ingestion records, along with occurrence details such as counts and associated source/date groupings. No enrichment, forecasting, or external lookups are performed.
Example use cases
ETL pipeline key collision audit
“I just ran a file ingestion batch and I'm worried some row IDs got duplicated — can you check these 80 ingestion records and give me a report of any duplicate row_id values across my sources?”
Daily data load quality check
“Here are today's 120 file ingestion rows from our data pipeline, each with a row_id, source, date, loaded_bytes, and parse_errors — can you run a duplicate key check and tell me which row IDs show up more than once?”
Multi-source ingestion deduplication review
“We're merging file loads from two sources, group-a and group-b, and I need to know if any row IDs collide — can you analyze these 50 ingestion records and produce a duplicate key report?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ar-analytics-file-ingestion-key-duplicates?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a bounded batch of up to 200 file ingestion records and need a fast, local duplicate key report without any external enrichment or forecasting. It is ideal for data quality checks in ETL pipelines where you want to confirm row ID uniqueness before downstream processing. Prefer this over general-purpose deduplication tools when your data already conforms to the file ingestion schema (row_id, source, date, loaded_bytes, parse_errors).
Side effects
- Empty rows array or fewer than 1 item returns a validation error
- More than 200 rows submitted exceeds the maxItems limit and will be rejected
- Missing required fields (row_id, source, date, loaded_bytes, parse_errors) on any record causes a schema validation failure
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- row_id values exceeding 80 characters are rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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