{"uid":"cap_dzUjwS4Zbgzx2rg74l3PZ","slug":"null-coverage-analytics-numeric-distribution-interval-filter-73505830","name":"Null Coverage Analytics: Numeric Distribution + Interval Filter","description":"Null coverage — Numeric distribution + Numeric interval filter: Numeric distribution + Numeric interval filter for supplied null coverage records (missing_values, total_values). 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-03-074?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","missing_values","total_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"missing_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_values":1,"dataset_group":"group-a","missing_values":10},{"date":"2026-10-02","row_id":"row-2","total_values":2,"dataset_group":"group-b","missing_values":20},{"date":"2026-10-03","row_id":"row-3","total_values":3,"dataset_group":"group-a","missing_values":15},{"date":"2026-10-04","row_id":"row-4","total_values":4,"dataset_group":"group-b","missing_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["missing_values","total_values"],"type":"string","default":"missing_values"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_yMms73ZOyOzHWigvbHhJh","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 and an interval-filtered report for null coverage data (missing_values, total_values) across up to 200 rows, returning 2 independent analytical reports.","exampleAgentPrompt":"Analyze the distribution of missing_values in my null coverage data and filter to rows where missing_values is between 0 and 50 — here are my rows: row-1 (group-a, 2024-01-01, 10 missing out of 100), row-2 (group-b, 2024-01-02, 5 missing out of 80), row-3 (group-a, 2024-01-03, 45 missing out of 200).","exampleUseCases":[{"title":"Data quality audit across dataset groups","prompt":"I have 150 rows of null coverage records across dataset groups A, B, and C — can you give me a numeric distribution of missing_values and show me only the rows where missing_values falls between 10 and 100?"},{"title":"Monitoring total values in a specific range","prompt":"Run a distribution analysis on total_values for my dataset records, and filter to only rows where total_values is between 500 and 10000 — I'll paste in the 80 rows with row IDs, dates, and group names."},{"title":"Identifying high-null date ranges","prompt":"I want to understand the spread of missing_values across my records from October 2026 — here are 40 rows with row_id, dataset_group, date, missing_values, and total_values. Give me the numeric distribution and filter to missing_values between 15 and 60."}],"resultDescription":"Returns 2 independent analytical reports: (1) a numeric distribution summarizing the spread of the selected field (missing_values or total_values) across up to 200 input rows, and (2) an interval-filtered report showing only the rows where the selected field falls within the specified minimum–maximum range.","failureModes":["Missing required row fields (row_id, date, missing_values, total_values) causes validation failure","Exceeding 200 rows in the input array returns an error","Date values not matching YYYY-MM-DD pattern are rejected","minimum greater than maximum causes undefined filter behavior","Null values in the selected field may be excluded from distribution calculations"],"whenToPreferThis":"Choose this endpoint when you have up to 200 null coverage records (with missing_values and total_values) and need both a distribution breakdown and an interval-filtered subset in a single low-cost call. Ideal for data quality pipelines, completeness audits, and monitoring workflows that need quick local analytics without external lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T06:55:18.445Z","isFirstParty":false,"canonicalSlug":"null-coverage-analytics-numeric-distribution-interval-filter-73505830"}