{"uid":"cap_YqkXyY7tVV0XA22YdRbYL","slug":"newsletter-observations-record-quality-audit-numeric-interval-filter-3c433bec","name":"Newsletter Observations — Record Quality Audit + Numeric Interval Filter","description":"Newsletter observations — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied newsletter observations records (delivered_messages, open_count). 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-news-08-008?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","delivered_messages","open_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"open_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"channel_group":{"type":"string","default":"","maxLength":80},"delivered_messages":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","open_count":1,"channel_group":"group-a","delivered_messages":10},{"date":"2026-10-02","row_id":"row-2","open_count":2,"channel_group":"group-b","delivered_messages":20},{"date":"2026-10-03","row_id":"row-3","open_count":3,"channel_group":"group-a","delivered_messages":15},{"date":"2026-10-04","row_id":"row-4","open_count":4,"channel_group":"group-b","delivered_messages":30}],"maxItems":200,"minItems":1},"field":{"enum":["delivered_messages","open_count"],"type":"string","default":"delivered_messages"},"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_36es2aIRcczuydDQlJ-JS","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 on newsletter observation rows: a record quality audit and a numeric interval filter for delivered_messages or open_count fields.","exampleAgentPrompt":"Can you audit the quality of these newsletter records and filter the delivered_messages field to only show rows between 50 and 500? Here are up to 200 rows with row_id, channel_group, date, delivered_messages, and open_count.","exampleUseCases":[{"title":"Email campaign data quality check","prompt":"I have 80 rows of newsletter delivery data for October with channel groups and open counts — can you run a record quality audit on them and also filter delivered_messages to rows between 100 and 10000?"},{"title":"Anomaly detection in open counts","prompt":"Can you audit this set of newsletter observation records for quality issues and filter the open_count field to flag anything outside the range of 0 to 5000? I've got about 150 rows from different channel groups."},{"title":"Pre-reporting data validation","prompt":"Before I build my monthly newsletter report, can you check these 200 rows for record quality problems and filter out any delivered_messages values that fall outside 200 to 50000?"}],"resultDescription":"Two analytical reports: (1) a record quality audit identifying issues such as nulls, out-of-range values, or malformed records across the supplied newsletter rows, and (2) a numeric interval filter report listing which rows have the chosen field (delivered_messages or open_count) within the specified minimum–maximum range. Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row or more than 200 rows supplied returns a validation error","Missing required fields (row_id, channel_group, date, delivered_messages, open_count) cause row rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Minimum greater than maximum may produce empty filter results or an error","Payment not included or insufficient USDC results in 402 rejection"],"whenToPreferThis":"Use this endpoint when you need both a quality audit and a numeric range filter on newsletter observation data in a single call for up to 200 rows, without requiring external data lookups or predictions. It is cost-effective at $0.01 USDC for two reports simultaneously and is ideal for pre-processing or validating newsletter analytics data before reporting or downstream pipeline use.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:37:58.307Z","isFirstParty":false,"canonicalSlug":"newsletter-observations-record-quality-audit-numeric-interval-filter-3c433bec"}