{"uid":"cap_wdcit2EwCeDqbMTwdi_7-","slug":"data-collection-completeness-numeric-interval-filter-adjacent-row-e2844766","name":"Data Collection Completeness — Numeric Interval Filter + Adjacent Row Changes","description":"Data collection completeness — Numeric interval filter + Adjacent row changes: Numeric interval filter + Adjacent row changes for supplied data collection completeness records (observed_values, expected_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-education-22-127?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","observed_values","expected_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"course_group":{"type":"string","default":"","maxLength":80},"expected_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"observed_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","course_group":"group-a","expected_values":1,"observed_values":10},{"date":"2026-10-02","row_id":"row-2","course_group":"group-b","expected_values":2,"observed_values":20},{"date":"2026-10-03","row_id":"row-3","course_group":"group-a","expected_values":3,"observed_values":15},{"date":"2026-10-04","row_id":"row-4","course_group":"group-b","expected_values":4,"observed_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["observed_values","expected_values"],"type":"string","default":"observed_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_8QV6sLcp9bwKPXfzTcYKZ","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 completeness data: filters rows by a numeric interval and computes adjacent row changes for observed/expected values.","exampleAgentPrompt":"I have 50 rows of education data collection completeness records with observed_values and expected_values by course group and date — can you run two reports: filter rows where observed_values fall between 0 and 100, and compute adjacent row changes on observed_values?","exampleUseCases":[{"title":"Course completeness gap detection","prompt":"I've got daily data collection completeness records for two course groups over the past month — can you filter the observed_values between 5 and 80 and show me the adjacent row changes so I can spot where data dropped off suddenly?"},{"title":"Expected values interval audit","prompt":"Run a completeness analysis on my education dataset: filter expected_values between 0 and 500 and compute the row-to-row changes so I can see where expectations shifted dramatically across dates."},{"title":"Comparing observed vs expected submission rates","prompt":"I have 120 rows of course completion records with observed and expected submission counts — filter the observed_values between 10 and 200 and give me the adjacent row deltas to find unusual spikes or drops."}],"resultDescription":"Returns two analytical reports for up to 200 rows: (1) a numeric interval filter identifying rows where the selected field (observed_values or expected_values) falls within the specified minimum/maximum range, and (2) an adjacent row changes report showing value differences between consecutive rows for the selected field.","failureModes":["More than 200 rows submitted — request will be rejected or truncated","Invalid date format (not YYYY-MM-DD) causes row-level validation errors","Missing required fields (row_id, observed_values, expected_values) causes schema rejection","Minimum value greater than maximum value produces empty interval filter results","Non-numeric observed_values or expected_values causes type validation failure"],"whenToPreferThis":"Choose this endpoint when you need simultaneous interval filtering and adjacent-row change detection on completeness data (observed vs expected values) for education or data pipeline monitoring use cases, without any need for external lookups or predictions. Ideal for batch analytical workflows on up to 200 rows at low cost ($0.01 USDC for both reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:49:27.958Z","isFirstParty":false,"canonicalSlug":"data-collection-completeness-numeric-interval-filter-adjacent-row-e2844766"}