{"uid":"cap_0F2SQVAYnKMmUciNSRWBF","slug":"third-party-reviews-record-quality-audit-string-normalisation-daily-e65e67dd","name":"Third Party Reviews — Record Quality Audit + String Normalisation + Daily Sum Series","description":"Third party reviews — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series for supplied third party reviews records (vendors_reviewed, outstanding_actions). 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-security-24-198?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","control_group","date","vendors_reviewed","outstanding_actions"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"control_group":{"type":"string","default":"","maxLength":80},"vendors_reviewed":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"outstanding_actions":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","control_group":"group-a","vendors_reviewed":10,"outstanding_actions":1},{"date":"2026-10-02","row_id":"row-2","control_group":"group-b","vendors_reviewed":20,"outstanding_actions":2},{"date":"2026-10-03","row_id":"row-3","control_group":"group-a","vendors_reviewed":15,"outstanding_actions":3},{"date":"2026-10-04","row_id":"row-4","control_group":"group-b","vendors_reviewed":30,"outstanding_actions":4}],"maxItems":200,"minItems":1},"field":{"enum":["vendors_reviewed","outstanding_actions"],"type":"string","default":"vendors_reviewed"}}},"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_pDwVA5HuUC7Rz-U9nDRAg","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 local analytical reports on third-party review data: a record quality audit, string normalisation, and a daily sum time series, for up to 200 rows of vendors_reviewed and outstanding_actions data.","exampleAgentPrompt":"Can you run a record quality audit, string normalisation, and daily sum series on my third-party review data? I have rows with dates from 2026-10-01 to 2026-10-04, covering vendors_reviewed and outstanding_actions across group-a and group-b — I want the vendors_reviewed field analysed.","exampleUseCases":[{"title":"Vendor review data quality check","prompt":"I've got a batch of third-party review records with vendors_reviewed and outstanding_actions columns — can you audit them for quality issues, normalise the strings, and give me a daily sum series for the vendors_reviewed field? There are about 150 rows spanning October 2026."},{"title":"Daily outstanding actions trend","prompt":"Run a daily sum series plus a record quality audit on my outstanding_actions data from our vendor review logs — I have around 80 rows with dates and control groups, and I want the outstanding_actions field summarised by day."},{"title":"Multi-group vendor review analytics","prompt":"I have third-party review records split across two control groups, group-a and group-b, with vendors_reviewed and outstanding_actions per day. Can you do a quality audit, string normalise the records, and produce a daily sum series on the vendors_reviewed field for all 200 rows?"}],"resultDescription":"Three independent analytical reports produced from the supplied rows: (1) a record quality audit flagging missing values, format errors, and anomalies; (2) a string normalisation report standardising text fields; and (3) a daily sum series aggregating the selected numeric field (vendors_reviewed or outstanding_actions) by date. No external lookups or live data — all analysis is local.","failureModes":["Rows array empty or missing — minimum 1 row required","More than 200 rows supplied — request will be rejected","Invalid date format (not YYYY-MM-DD) on any row","Field selector not one of 'vendors_reviewed' or 'outstanding_actions'","Numeric values outside allowed range (±1,000,000,000,000)","Missing required fields (row_id, date, vendors_reviewed, outstanding_actions) on any row"],"whenToPreferThis":"Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and daily sum aggregation — on a small-to-medium dataset of third-party review records (up to 200 rows) in a single low-cost call ($0.01 USDC). It is ideal for offline/local analysis where no live lookup, prediction, or external data enrichment is needed.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:51:15.829Z","isFirstParty":false,"canonicalSlug":"third-party-reviews-record-quality-audit-string-normalisation-daily-e65e67dd"}