{"uid":"cap_fvzW4TrLyjXU7QRYVp3S_","slug":"record-routing-quality-audit-string-normalisation-iqr-outlier-flags-99e57c9f","name":"Record Routing Quality Audit: String Normalisation + IQR Outlier Flags","description":"Record routing — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags for supplied record routing records (accepted_records, rejected_records). 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-analytics-19-203?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","accepted_records","rejected_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},"accepted_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"rejected_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","accepted_records":10,"rejected_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","accepted_records":20,"rejected_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","accepted_records":15,"rejected_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","accepted_records":30,"rejected_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["accepted_records","rejected_records"],"type":"string","default":"accepted_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_3gRV_lWhb2uFwASmIdCnF","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 record routing data — a quality audit, string normalisation, and IQR-based outlier detection — for up to 200 rows of accepted/rejected record counts.","exampleAgentPrompt":"Can you audit the quality of my record routing data, normalise the string fields, and flag any IQR outliers in the accepted_records column? I have 4 rows across two dataset groups (group-a and group-b) with dates from 2026-10-01 to 2026-10-04.","exampleUseCases":[{"title":"ETL pipeline data quality check","prompt":"I just pulled a batch of 50 rows from our record routing pipeline — can you run a quality audit, normalise the string fields like dataset_group, and flag any IQR outliers in the rejected_records column so I know which rows to investigate?"},{"title":"Detecting anomalous rejection spikes","prompt":"We have daily routing records across several dataset groups for October 2026 — can you identify which rows have unusually high rejected_records values using IQR outlier detection and give me a full quality report?"},{"title":"Pre-ingestion data validation for analytics","prompt":"Before I load these record routing rows into our data warehouse, can you run a string normalisation pass on the dataset_group names and do a quality audit plus IQR outlier check on the accepted_records field across all 120 rows?"}],"resultDescription":"Returns three independent reports for up to 200 supplied rows: (1) a record quality audit highlighting missing, malformed, or inconsistent values; (2) a string normalisation report cleaning dataset_group and other text fields; and (3) IQR-based outlier flags identifying statistically anomalous rows in the chosen numeric field (accepted_records or rejected_records). All analysis is performed locally with no external lookups.","failureModes":["Fewer than 1 row supplied — request rejected","More than 200 rows supplied — exceeds batch limit","Invalid date format (not YYYY-MM-DD) — schema validation error","Missing required fields (row_id, date, accepted_records, rejected_records) — validation failure","Numeric values outside allowed range (±1,000,000,000,000) — schema rejection","Invalid field enum value — must be 'accepted_records' or 'rejected_records'"],"whenToPreferThis":"Choose this endpoint when you need a fast, self-contained, three-in-one analytical pass on record routing data — covering quality auditing, string normalisation, and IQR outlier detection — without any external API calls or live data lookups. Ideal for pre-ingestion validation, pipeline monitoring, or ad-hoc data quality checks on batches up to 200 rows at very low cost ($0.01 USDC for all three reports).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T06:40:06.504Z","isFirstParty":false,"canonicalSlug":"record-routing-quality-audit-string-normalisation-iqr-outlier-flags-99e57c9f"}