{"uid":"cap_lUrktnwpGLAYPsu8f49OT","slug":"join-coverage-analytics-numeric-distribution-grouped-numeric-summary-390c9862","name":"Join Coverage Analytics: Numeric Distribution + Grouped Numeric Summary","description":"Join coverage — Numeric distribution + Grouped numeric summary: Numeric distribution + Grouped numeric summary 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-09-071?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"}}},"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_TjCM0WG97HFQErc7TJxsN","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":"Computes a numeric distribution report and a grouped numeric summary for join coverage metrics (matched_rows, source_rows) across up to 200 supplied records.","exampleAgentPrompt":"Analyze the numeric distribution and grouped summary of matched_rows for my join coverage dataset — here are 4 records: row-1 on 2026-10-01 in group-a with source_rows=1 and matched_rows=10, row-2 on 2026-10-02 in group-b with source_rows=2 and matched_rows=20, row-3 on 2026-10-03 in group-a with source_rows=3 and matched_rows=15, row-4 on 2026-10-04 in group-b with source_rows=4 and matched_rows=30.","exampleUseCases":[{"title":"ETL pipeline join audit","prompt":"I've got 50 rows of join coverage data from my nightly ETL run — each row has a date, a dataset group like 'orders' or 'inventory', and both source_rows and matched_rows counts. Can you give me the numeric distribution and grouped summary for matched_rows so I can see where coverage is low?"},{"title":"Data quality review by team","prompt":"We have join coverage records from three teams — 'finance', 'marketing', and 'ops' — across the past month. Run the numeric distribution and grouped numeric summary on source_rows so I can compare how each team's datasets are performing."},{"title":"Pre-merge coverage check","prompt":"Before we merge these two datasets, I want to understand the spread and group-level summary of matched_rows across our 120 join coverage records. Can you run both the numeric distribution and grouped summary reports on the matched_rows field?"}],"resultDescription":"Returns two independent analytical reports: (1) a numeric distribution breakdown of the selected field (matched_rows or source_rows), including spread, frequency, and range statistics; and (2) a grouped numeric summary aggregating that field by dataset_group, showing group-level stats. Both reports are computed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) causes row rejection","Field selector not one of 'matched_rows' or 'source_rows' causes enum validation error","Null values in the selected numeric field may affect distribution computations","Empty rows array (minItems:1 violated) returns an error"],"whenToPreferThis":"Choose this endpoint when you need both a numeric distribution and a grouped summary for join coverage metrics (matched_rows or source_rows) in a single low-cost call. It is ideal for data engineers auditing ETL pipeline join quality, where you want statistical spread and group-level breakdowns without writing custom analytics code. Prefer it over generic analytics tools when your data already conforms to the row_id/dataset_group/date/matched_rows/source_rows schema and you want two reports for $0.01 USDC with no external data leaving your payload.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:50:52.989Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-numeric-distribution-grouped-numeric-summary-390c9862"}