{"uid":"cap_ZXLotEbejg4qduElyace9","slug":"schema-conformity-record-quality-audit-with-iqr-outlier-flags-79e9191e","name":"Schema Conformity Record Quality Audit with IQR Outlier Flags","description":"Schema conformity — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied schema conformity records (valid_records, checked_records). 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-analytics-02-014?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_records","checked_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"valid_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","valid_records":10,"checked_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","valid_records":20,"checked_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","valid_records":15,"checked_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","valid_records":30,"checked_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_records","checked_records"],"type":"string","default":"valid_records"}}},"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_RdOgqN2HvfcqLD5e7Cv1o","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":"Performs a two-report quality audit on schema conformity records (valid_records, checked_records), including record quality analysis and IQR-based outlier detection, for up to 200 supplied rows.","exampleAgentPrompt":"Run a record quality audit and IQR outlier check on my schema conformity data — here are my rows with valid_records and checked_records by date and group, and I want to analyze the valid_records field.","exampleUseCases":[{"title":"Data pipeline conformity review","prompt":"I have up to 200 rows of schema conformity data from my ETL pipeline, each with a date, group name, valid_records, and checked_records — can you run a quality audit and flag any IQR outliers in the valid_records field?"},{"title":"Detect anomalous checked record counts","prompt":"Here's my dataset of checked_records and valid_records grouped by dataset group and date — I want a record quality report plus any rows flagged as outliers based on IQR, analyzing the checked_records field specifically."},{"title":"Weekly data quality health check","prompt":"Every week I track how many records pass schema validation across my groups. Can you audit this batch of up to 150 rows for record quality issues and highlight any valid_records values that look like outliers using IQR analysis?"}],"resultDescription":"Returns two independent analytical reports: (1) a record quality audit summarizing the health and completeness of the supplied schema conformity rows, and (2) IQR-based outlier flags identifying rows where the selected field (valid_records or checked_records) deviates significantly from the interquartile range. No external lookups or predictions are performed — all analysis is based solely on the supplied data.","failureModes":["Fewer than 1 row supplied — minimum row count not met","More than 200 rows submitted — exceeds maximum batch size","Missing required fields (row_id, date, valid_records, checked_records) on any row","Date field not matching YYYY-MM-DD pattern","Field selector not one of 'valid_records' or 'checked_records'","Null values in both numeric fields making IQR computation impossible","Insufficient data variance for meaningful IQR outlier detection (all values identical)"],"whenToPreferThis":"Choose this endpoint when you have a batch of up to 200 schema conformity records and need both a holistic data quality audit and statistical outlier detection (IQR-based) in a single low-cost call. Prefer this over generic analytics APIs when your data specifically tracks valid_records and checked_records by date and group, and you want two structured reports without any external data enrichment or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-17T00:47:23.780Z","isFirstParty":false,"canonicalSlug":"schema-conformity-record-quality-audit-with-iqr-outlier-flags-79e9191e"}