{"uid":"cap_BtNkrCMetLItXVj-gQftK","slug":"join-coverage-string-normalisation-trailing-mean-series-ac37020c","name":"Join Coverage — String Normalisation + Trailing Mean Series","description":"Join coverage — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied join coverage records (matched_rows, source_rows). 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-09-028?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"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_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_rows"},"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__KPNdCIxXgRoKcMNRu8vi","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 analytical reports (string normalisation and trailing mean series) on user-supplied join coverage data (matched_rows, source_rows) for up to 200 rows.","exampleAgentPrompt":"Can you run string normalisation and a trailing mean series on my join coverage records? I have 4 rows from 2026-10-01 to 2026-10-04 with matched_rows and source_rows values across group-a and group-b, using the matched_rows field and a window of 2.","exampleUseCases":[{"title":"Monitor join quality trends over time","prompt":"I have daily join coverage data for two dataset groups over the past week — can you normalize the string fields and compute a trailing mean with window 2 on the matched_rows column so I can see the trend?"},{"title":"Audit ETL pipeline match rates","prompt":"Run both the string normalisation and trailing mean series reports on these 50 rows of ETL join results, using source_rows as the field and a window of 5, so I can audit our pipeline's match rates."},{"title":"Compare coverage across dataset groups","prompt":"I want to compare join coverage across my dataset groups — please normalise the string columns and compute a trailing 3-period mean on matched_rows for my 100 records dated between 2026-09-01 and 2026-09-30."}],"resultDescription":"Returns two analytical reports for the supplied rows: (1) a string normalisation report covering text fields such as row_id and dataset_group, and (2) a trailing mean series computed over the chosen numeric field (matched_rows or source_rows) using the specified rolling window. No external lookups or predictions are made; all analysis is performed locally on the supplied data.","failureModes":["Fewer than 1 row or more than 200 rows supplied — validation error","Invalid date format (not YYYY-MM-DD) — schema rejection","window value outside range 2–200 — validation error","Null or missing required fields (row_id, dataset_group, date) — error","Numeric values outside ±1,000,000,000,000 — schema rejection","Payment failure or insufficient USDC balance — 402 response"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and a trailing mean time series computed together on join coverage data (matched_rows/source_rows) in a single $0.01 call. Prefer it over single-report endpoints when you want both analytical outputs simultaneously without separate requests. It is purely local — no external enrichment, prediction, or live data lookup — making it suitable for offline or sandboxed data pipelines.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:41.051Z","isFirstParty":false,"canonicalSlug":"join-coverage-string-normalisation-trailing-mean-series-ac37020c"}