{"uid":"cap_vvhbPjMOSUNtQWKJh9Zg9","slug":"newsletter-observations-analyzer-record-quality-audit-string-f8f54be4","name":"Newsletter Observations Analyzer — Record Quality Audit + String Normalisation + Trailing Mean Series","description":"Newsletter observations — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series for supplied newsletter observations records (delivered_messages, open_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-news-08-199?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"},"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_zkund15Waw33C5qSiBccG","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 three analytical reports (record quality audit, string normalisation, and trailing mean series) on newsletter observation data (delivered_messages, open_count) for up to 200 rows.","exampleAgentPrompt":"Can you run a quality audit, string normalization, and trailing mean analysis (window of 7) on my newsletter data — I have rows with row_id, channel_group, date, delivered_messages, and open_count — and focus the trailing mean on open_count?","exampleUseCases":[{"title":"Email campaign data quality check","prompt":"I've got 150 rows of newsletter send data with delivered_messages and open_count per channel group and date — can you run a record quality audit and flag any bad or missing values, normalize the channel group strings, and compute a 5-period trailing mean on delivered_messages?"},{"title":"Rolling open rate trend analysis","prompt":"Take my newsletter observation records for the past quarter — each row has a date, channel_group, delivered_messages, and open_count — and give me a trailing mean series with a window of 10 for open_count so I can see the smoothed trend over time."},{"title":"Multi-report newsletter data cleanup","prompt":"I need three reports on my newsletter dataset: a quality audit to catch bad records, string normalization on channel_group, and a rolling average with window size 4 on delivered_messages — there are about 80 rows total, each identified by row_id."}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging missing, null, or out-of-range values per row; (2) a string normalisation report with cleaned/standardized versions of string fields like channel_group; and (3) a trailing mean series showing rolling averages for the selected numeric field (delivered_messages or open_count) over the specified window. All computed locally without external lookups or predictions.","failureModes":["More than 200 rows submitted — request rejected or truncated","Invalid date format (not YYYY-MM-DD) causes row rejection","Numeric values outside ±1,000,000,000,000 range rejected","Missing required fields (row_id, channel_group, date, delivered_messages, open_count) cause row-level errors","Window size less than 2 or greater than 200 causes parameter validation failure","Empty rows array causes request failure","Payment of 0.01 USDC not provided or rejected causes 402 response"],"whenToPreferThis":"Choose this endpoint when you need all three of record quality auditing, string normalization, and trailing mean computation on newsletter data in a single low-cost call. It is ideal for preprocessing and QA of email campaign datasets before downstream analysis, especially when working with delivered_messages or open_count metrics grouped by channel and date. Prefer this over general-purpose data tools when you want bundled, purpose-built reports for newsletter observation schemas at a fixed $0.01 cost for up to 200 rows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-03T06:44:03.873Z","isFirstParty":false,"canonicalSlug":"newsletter-observations-analyzer-record-quality-audit-string-f8f54be4"}