{"uid":"cap_MGp-hdphYRYuF2xbnWsjX","slug":"aggregation-checks-string-normalisation-trailing-mean-series-204f7a0d","name":"Aggregation Checks — String Normalisation + Trailing Mean Series","description":"Aggregation checks — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied aggregation checks records (source_sum, aggregate_sum). 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-17-028?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","source_sum","aggregate_sum"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_sum":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"aggregate_sum":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_sum":10,"aggregate_sum":1,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_sum":20,"aggregate_sum":2,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_sum":15,"aggregate_sum":3,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_sum":30,"aggregate_sum":4,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["source_sum","aggregate_sum"],"type":"string","default":"source_sum"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2}}},"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_QKB3IsGrpve24OECdoXzj","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":"Runs two local analytical reports on supplied aggregation check records: string normalisation and trailing mean series computation, for up to 200 rows.","exampleAgentPrompt":"Run the string normalisation and trailing mean series reports on my aggregation check records — here are 4 rows with source_sum and aggregate_sum values across groups A and B from October 2026, using field source_sum and a window of 3.","exampleUseCases":[{"title":"Reconciliation drift detection for finance team","prompt":"I have 50 daily aggregation records with source_sum and aggregate_sum from January 2025 — can you run the string normalisation and trailing mean series reports on them using a window of 7 and field aggregate_sum so I can spot where the totals start drifting?"},{"title":"Data quality check on ETL pipeline output","prompt":"Our ETL pipeline outputs dataset_group labels that may have casing inconsistencies, and we need a trailing mean over source_sum with a window of 5 — can you run both the normalisation and rolling mean reports on these 120 rows?"},{"title":"Rolling average trend for monthly aggregation audit","prompt":"I'm auditing monthly aggregation checks across two dataset groups for Q3 2024, 30 rows total — please compute the string normalisation report and a trailing mean series on source_sum with a window of 4."}],"resultDescription":"Two independent analytical reports: (1) a string normalisation report on the dataset_group labels and row identifiers, and (2) a trailing mean series computed over the specified numeric field (source_sum or aggregate_sum) using the given rolling window size — all derived locally from the supplied rows with no external lookups.","failureModes":["Fewer than 1 row or more than 200 rows submitted — request rejected","Window size larger than the number of rows — trailing mean series may be incomplete or invalid","Missing required fields (row_id, date, dataset_group, source_sum, aggregate_sum) — validation error","Date values not matching YYYY-MM-DD pattern — schema validation failure","Numeric values outside ±1,000,000,000,000 range — rejected","Payment not attached or insufficient — x402 payment required error"],"whenToPreferThis":"Choose this endpoint when you need two bundled local analytical operations — string normalisation and trailing mean series — on a small-to-medium set of aggregation check records (up to 200 rows) in a single low-cost call. Ideal for reconciliation workflows where you want to clean group labels and compute rolling averages on source or aggregate sums simultaneously without external API dependencies or live data lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:53:22.196Z","isFirstParty":false,"canonicalSlug":"aggregation-checks-string-normalisation-trailing-mean-series-204f7a0d"}