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Metadata Completeness — Duplicate Key Report + Base-100 Series
x402
Metadata Completeness — Duplicate Key Report + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Analyzes metadata completeness records to produce a duplicate key report and a base-100 index series for up to 200 rows of present_fields/expected_fields data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Metadata completeness — Duplicate key report + Base-100 series: Duplicate key report + Base-100 series for supplied metadata completeness records (present_fields, expected_fields). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two reports: (1) a duplicate key report identifying rows with repeated key combinations (row_id, site_group, date), and (2) a base-100 index series for the selected field (present_fields or expected_fields) anchored to the specified base_index row, computed locally without any external lookups.
Example use cases
Audit metadata pipeline for duplicate keys
“I've got 150 rows from our metadata pipeline with site groups and dates — can you check them for duplicate keys and also give me a base-100 series on present_fields starting from index 0?”
Index field coverage across content groups
“I have completeness records for two site groups over the past quarter — run a base-100 index series on expected_fields starting at row 0 and flag any duplicate row IDs in there.”
QA metadata records before reporting
“Before I publish our metadata quality report, can you run a duplicate key check and a base-100 completeness index on these 80 rows of present_fields and expected_fields data across our site groups?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-web-05-063?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need two complementary offline analytical reports — duplicate key detection and base-100 normalization — on metadata completeness data in a single low-cost call. It is ideal for data quality audits of metadata pipelines where you want to identify repeated keys and index field coverage ratios without any external API calls or predictions.
Side effects
- Missing required fields (row_id, site_group, date, present_fields, expected_fields) cause validation errors
- More than 200 rows submitted — exceeds maximum and will be rejected
- Invalid date format (must match YYYY-MM-DD pattern) causes schema validation failure
- base_index out of range (must be 0–199) returns an error
- Null numeric values for present_fields or expected_fields may produce incomplete index calculations
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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