{"uid":"cap_EogYniddFpnl4O0lrqqwh","slug":"transformation-throughput-analytics-numeric-distribution-adjacent-row-a3b08141","name":"Transformation Throughput Analytics: Numeric Distribution + Adjacent Row Changes","description":"Transformation throughput — Numeric distribution + Adjacent row changes: Numeric distribution + Adjacent row changes for supplied transformation throughput records (processed_rows, duration_seconds). 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.","url":"https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-077?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","processed_rows","duration_seconds"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"duration_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","processed_rows":10,"duration_seconds":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","processed_rows":20,"duration_seconds":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","processed_rows":15,"duration_seconds":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","processed_rows":30,"duration_seconds":4}],"maxItems":200,"minItems":1},"field":{"enum":["processed_rows","duration_seconds"],"type":"string","default":"processed_rows"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_xNx3cpHYNO4nFAwB1WKda","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes transformation throughput records to produce a numeric distribution report and an adjacent row changes report for processed_rows or duration_seconds fields.","exampleAgentPrompt":"Analyze the distribution of processed_rows and the adjacent row changes for my pipeline records — I have 4 rows: row-1 on 2026-10-01 in group-a with 10 processed_rows and 1 duration_second, row-2 on 2026-10-02 in group-b with 20 processed_rows and 2 seconds, row-3 on 2026-10-03 in group-a with 15 processed_rows and 3 seconds, row-4 on 2026-10-04 in group-b with 30 processed_rows and 4 seconds; use processed_rows as the field.","exampleUseCases":[{"title":"ETL pipeline throughput distribution review","prompt":"I have 50 daily ETL run records with processed_rows and duration_seconds — can you give me a numeric distribution of processed_rows and show me how the counts changed between consecutive runs across my dataset groups?"},{"title":"Duration anomaly detection across batch jobs","prompt":"Here are 80 transformation records for our batch jobs with dates, dataset groups, and duration_seconds values — run the numeric distribution and adjacent row changes reports on duration_seconds so I can spot any unusually long or spiking runs."},{"title":"Pipeline performance comparison by group","prompt":"I want to understand the spread and step-by-step changes in processed_rows for my group-a and group-b pipeline records from last month — I'll supply up to 150 rows with row IDs, dates, processed_rows, and duration_seconds; please use processed_rows as the field to analyze."}],"resultDescription":"Returns two analytical reports: (1) a numeric distribution report summarizing the statistical spread (e.g. min, max, mean, percentiles, frequency buckets) of the chosen field (processed_rows or duration_seconds), and (2) an adjacent row changes report showing the delta between consecutive rows for the same field — all computed locally from supplied data with no external lookups.","failureModes":["Rows array is empty or missing — minimum 1 row required","More than 200 rows supplied — exceeds maxItems limit","Missing required row fields (row_id, dataset_group, date, processed_rows, duration_seconds) — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","Field selector not one of 'processed_rows' or 'duration_seconds' — enum validation error","Null values in processed_rows or duration_seconds may reduce report completeness","Payment of 0.01 USDC not provided or rejected — 402 Payment Required"],"whenToPreferThis":"Choose this endpoint when you need both a statistical distribution view and a consecutive-record delta view of ETL or data pipeline throughput metrics (processed_rows or duration_seconds) from your own supplied data, without requiring any external data source, prediction, or real-time lookup. It is especially useful for pipeline performance audits, batch job monitoring, and identifying throughput anomalies in up to 200 records for a flat $0.01 USDC fee covering both reports.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-28T19:41:47.887Z","isFirstParty":false,"canonicalSlug":"transformation-throughput-analytics-numeric-distribution-adjacent-row-a3b08141"}