{"uid":"cap_tnIiDWfhA3_W6GpWkqr1I","slug":"video-engagement-record-quality-audit-string-normalisation-numeric-4c58bd42","name":"Video Engagement Record Quality Audit + String Normalisation + Numeric Row Ordering","description":"Video engagement — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied video engagement records (view_count, watch_minutes). 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-10-196?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","view_count","watch_minutes"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"view_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"channel_group":{"type":"string","default":"","maxLength":80},"watch_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","view_count":10,"channel_group":"group-a","watch_minutes":1},{"date":"2026-10-02","row_id":"row-2","view_count":20,"channel_group":"group-b","watch_minutes":2},{"date":"2026-10-03","row_id":"row-3","view_count":15,"channel_group":"group-a","watch_minutes":3},{"date":"2026-10-04","row_id":"row-4","view_count":30,"channel_group":"group-b","watch_minutes":4}],"maxItems":200,"minItems":1},"field":{"enum":["view_count","watch_minutes"],"type":"string","default":"view_count"}}},"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_jz11VfMriQ_8kVe-Keqq_","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":"Audits quality, normalises strings, and orders rows numerically for up to 200 video engagement records (view_count, watch_minutes) across 3 independent local analytical reports.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and numeric row ordering on my video engagement data — here are 4 rows with row IDs row-1 through row-4, channel groups group-a and group-b, dates from 2026-10-01 to 2026-10-04, view counts 10/20/15/30, and watch minutes 1/2/3/4 — and sort everything by view_count?","exampleUseCases":[{"title":"Pre-publish video data cleanup","prompt":"I have 150 rows of video engagement data with channel groups, dates, view counts and watch minutes — can you audit them for quality issues, normalise the channel group strings, and order the rows by view_count so I can review before uploading to our dashboard?"},{"title":"Watch-time ranking for content team","prompt":"Our content team exported 80 video engagement records with row IDs, dates, channel groups, and watch_minutes — please run the quality audit and sort everything numerically by watch_minutes so they can see which videos are performing best."},{"title":"Channel group data normalisation check","prompt":"I need to clean up a batch of 60 video engagement rows — the channel_group field has inconsistent casing and spacing, view counts and watch minutes are mixed in. Can you normalise the strings and flag any quality issues across all 3 reports?"}],"resultDescription":"Returns 3 independent analytical reports: (1) a record quality audit identifying issues in the supplied video engagement rows, (2) a string normalisation report for fields like channel_group, and (3) a numeric row ordering report sorting rows by the selected metric (view_count or watch_minutes). All processing is local with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, channel_group, date, view_count, watch_minutes) causes row rejection","Invalid date format (not YYYY-MM-DD) fails pattern validation","Numeric values outside ±1,000,000,000,000 boundary are rejected","Empty rows array returns an error","Invalid field enum value (not view_count or watch_minutes) causes request failure"],"whenToPreferThis":"Choose this endpoint when you need a combined quality audit, string normalisation, and numeric ordering for video engagement data (view_count, watch_minutes) in a single low-cost call. Ideal for batch preprocessing up to 200 rows before ingesting into dashboards or reports, without needing external lookups or predictions. Best suited for offline analytical pipelines where data cleanliness and ordering are the primary concern.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-25T12:31:37.890Z","isFirstParty":false,"canonicalSlug":"video-engagement-record-quality-audit-string-normalisation-numeric-4c58bd42"}