{"uid":"cap_BiJgFkfy27xQ1BOiPsq1X","slug":"sampling-observations-record-quality-audit-iqr-outlier-flags-bfc2aa06","name":"Sampling Observations — Record Quality Audit + IQR Outlier Flags","description":"Sampling observations — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied sampling observations records (sample_value, sample_weight). 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-15-014?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","sample_value","sample_weight"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"sample_value":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"sample_weight":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","sample_value":10,"dataset_group":"group-a","sample_weight":1},{"date":"2026-10-02","row_id":"row-2","sample_value":20,"dataset_group":"group-b","sample_weight":2},{"date":"2026-10-03","row_id":"row-3","sample_value":15,"dataset_group":"group-a","sample_weight":3},{"date":"2026-10-04","row_id":"row-4","sample_value":30,"dataset_group":"group-b","sample_weight":4}],"maxItems":200,"minItems":1},"field":{"enum":["sample_value","sample_weight"],"type":"string","default":"sample_value"}}},"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_s171duYvFk52n6ygoAdnR","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 a record quality audit and IQR-based outlier detection on up to 200 rows of sampling observation data (sample_value, sample_weight), returning two independent analytical reports.","exampleAgentPrompt":"Can you run a record quality audit and IQR outlier check on my sampling observations? Here are up to 200 rows with row_id, dataset_group, date, sample_value, and sample_weight fields — flag any quality issues and statistical outliers in the sample_value column.","exampleUseCases":[{"title":"Pre-analysis QC on survey samples","prompt":"I have 150 rows of survey sampling data with sample values and weights collected across two groups in October 2026 — can you audit the record quality and flag any IQR outliers in the sample_value field before I run my analysis?"},{"title":"Detecting bad weights in lab samples","prompt":"Run an IQR outlier check on the sample_weight column for my lab sampling observations — I have about 80 rows with row IDs, dates, and group labels, and I need to know which rows have anomalous weights."},{"title":"Data validation before pipeline ingestion","prompt":"Before I ingest this batch of 200 sampling records into our pipeline, can you run a full record quality audit and outlier flag report on the sample_value column so I can catch any bad data first?"}],"resultDescription":"Two independent analytical reports: (1) a record quality audit identifying malformed, missing, or invalid rows among the supplied sampling observations, and (2) IQR-based outlier flags indicating which rows contain statistically extreme values in the selected field (sample_value or sample_weight). No external lookups or predictions are made — analysis is performed entirely on the supplied data.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) cause row-level validation errors","Invalid date format (not YYYY-MM-DD) may cause parsing failures","Null values in the selected analysis field may affect IQR calculation","Insufficient data rows for meaningful IQR computation (e.g. only 1-2 rows)","Payment not processed — 402 response if USDC payment is not attached"],"whenToPreferThis":"Choose this endpoint when you need both a structural record quality check and IQR-based statistical outlier detection on sampling observation data in a single call. It is well-suited for pre-processing validation steps before downstream analysis, reporting, or pipeline ingestion. Prefer it over single-purpose validators when you want two independent reports (quality audit + outlier flags) on the same dataset without making separate API calls. It is purely local/analytical — no external data sources or live lookups are involved.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:52.758Z","isFirstParty":false,"canonicalSlug":"sampling-observations-record-quality-audit-iqr-outlier-flags-bfc2aa06"}