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Remove Duplicates → Text Match → Sort Numbers Descending
x402
Remove Duplicates → Text Match → Sort Numbers Descending is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Processes tabular records by sequentially removing duplicate rows, filtering rows where a text column matches a query, and sorting the results by a numeric column in descending order.
Price / call$0.01
Success—
StatusUnknown
How this service works
Remove duplicate rows → Match text in a column → Sort numbers descending: Process customer-supplied records: Remove duplicate rows → Match text in a column → Sort numbers descending. Returns the processed output and row counts per step. No external data lookup. 0.01 USDC includes up to 300 flat records.
Output
Returns the fully processed records array after all three sequential steps (deduplication, text match filter, numeric sort descending), along with row counts at each stage so you can see how many rows were removed or kept at each step.
Example use cases
Deduplicate and rank product listings
“I have a list of product records with duplicates — can you remove the dupes, keep only rows where the 'type' field contains 'widget', and sort the results by 'revenue' from highest to lowest?”
Filter customer survey responses by keyword
“Here are my survey responses. Remove any duplicate entries, filter down to rows where the 'answer' column matches 'satisfied', then sort them by 'score' descending so I see the highest scores first.”
Clean and prioritize support tickets
“Can you process these support ticket records — strip out duplicate rows, keep only tickets where the 'status' field matches 'open', and order the result by 'priority_score' from highest to lowest?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-cap-72a93bfc8cb8b26e2d26?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fixed three-step pipeline (deduplicate → text-match filter → numeric descending sort) applied to up to 300 flat records in a single call for a flat $0.01 USDC. Ideal for lightweight ETL preprocessing, data cleaning tasks, or quick report generation where you don't want to maintain your own transformation logic. Not suitable if you need a different operation order, more than 300 records, external data lookups, or custom aggregation beyond these three steps.
Side effects
- Empty records array or fewer than 1 item returns a validation error
- Records array exceeding 300 items is rejected
- Field name not matching pattern ^[a-zA-Z][a-zA-Z0-9_]{0,39}$ returns schema error
- Query string shorter than 1 character or longer than 100 characters is rejected
- Non-object items in records array cause schema validation failure
- No rows surviving deduplication or text-match filter returns empty result set with zero rows
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| field | string | |
| query | string | |
| records | array |
Tags
x402
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