{"uid":"cap_b8pha7zoEVXNBPviDinM8","slug":"sampling-observations-data-quality-suite-record-audit-string-f7e27fff","name":"Sampling Observations Data Quality Suite: Record Audit + String Normalisation + Exact Deduplication","description":"Sampling observations — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied sampling observations records (sample_value, sample_weight). 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-15-191?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}}},"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_YFfw0DKmqNbrUZIWIZEOW","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 three combined data-quality operations on up to 200 sampling observation rows: a record quality audit, string field normalisation, and exact row deduplication — all processed locally without external lookups.","exampleAgentPrompt":"Can you run a full data quality check on my sampling observations — I need a record quality audit, string normalisation, and exact row deduplication on these rows: row-1 (2026-10-01, group-a, value=10, weight=1), row-2 (2026-10-02, group-b, value=20, weight=2), row-3 (2026-10-01, group-a, value=10, weight=1) — I want to spot duplicates and any messy string or quality issues.","exampleUseCases":[{"title":"Pre-analysis survey data cleanup","prompt":"Before I run my weighted analysis, can you audit these 50 survey sampling rows for quality issues, normalise any inconsistent string labels in dataset_group, and flag any exact duplicate rows? Here are the records with sample_value and sample_weight fields."},{"title":"Deduplication check on merged observation exports","prompt":"I merged two observation exports and I'm worried there are duplicate rows — can you run an exact deduplication check plus a record quality audit on these 120 rows? Each row has a row_id, date, dataset_group, sample_value, and sample_weight."},{"title":"Routine QA on weekly sampling batch","prompt":"Run the weekly QA routine on this batch of sampling observations — I need the record quality audit, string normalisation, and exact row deduplication reports for these 80 rows covering group-a and group-b from October 2026."}],"resultDescription":"Returns three independent analytical reports for the submitted sampling observation rows: (1) a record quality audit identifying missing values, out-of-range figures, or malformed fields; (2) a string normalisation report standardising text fields like dataset_group; and (3) an exact row deduplication report identifying identical records. All processing is local — no external lookups or predictions are included.","failureModes":["Submitting more than 200 rows returns a validation error","Rows missing required fields (row_id, date, sample_value, sample_weight, dataset_group) are rejected","Dates not matching YYYY-MM-DD pattern cause schema validation failure","Numeric values outside ±1,000,000,000,000 are rejected","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need a bundled, cost-effective data quality pass over sampling observation records (with sample_value and sample_weight fields) and want all three reports — quality audit, string normalisation, and exact deduplication — in a single call for up to 200 rows. It is ideal for pre-analysis data cleaning pipelines where no external data enrichment or live prediction is needed and the dataset fits within the 200-row limit.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:54.765Z","isFirstParty":false,"canonicalSlug":"sampling-observations-data-quality-suite-record-audit-string-f7e27fff"}