{"uid":"cap_XV06mIBEy8s9MoRt1-WUn","slug":"sampling-observations-analyzer-record-quality-audit-string-27cc7ba9","name":"Sampling Observations Analyzer — Record Quality Audit + String Normalisation + Category Frequencies","description":"Sampling observations — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies 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-15-195?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_Tq9aYyMce8s2I059F9BeT","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 (record quality audit, string normalisation, and category frequencies) on up to 200 sampling observation rows with sample_value and sample_weight fields.","exampleAgentPrompt":"Can you audit and analyze my sampling observations dataset — I have 150 rows with row IDs, dates in YYYY-MM-DD format, dataset groups, sample values, and sample weights — and give me a record quality audit, string normalisation, and category frequency report all at once?","exampleUseCases":[{"title":"Survey data quality check","prompt":"I have a batch of 120 survey sampling records with row IDs, dates, group labels, sample values, and sample weights. Can you run a full quality audit on them, normalise the group name strings, and tell me the frequency of each category?"},{"title":"Weighted sample category analysis","prompt":"I've collected 80 weighted sampling observations across different dataset groups and I need to know the category frequency breakdown, catch any string inconsistencies in the group labels, and flag any quality issues in the records."},{"title":"Pre-analysis dataset cleanup","prompt":"Before I run my statistical model, can you audit these 200 sampling observation rows for record quality issues, normalise the string fields in the dataset_group column, and give me a count of how frequently each category appears?"}],"resultDescription":"Three independent analytical reports: (1) a record quality audit flagging missing, malformed, or out-of-range values; (2) a string normalisation report standardising text fields like dataset_group; and (3) a category frequency report counting occurrences of each distinct category value across the supplied rows.","failureModes":["More than 200 rows submitted — request rejected due to row limit","Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) cause validation errors","Dates not matching YYYY-MM-DD pattern are rejected","sample_value or sample_weight outside the allowed numeric range causes errors","Empty rows array (minItems: 1 not met) results in validation failure"],"whenToPreferThis":"Choose this endpoint when you need all three of record quality auditing, string normalisation, and category frequency analysis run together on sampling observation data (sample_value, sample_weight) in a single low-cost call. Ideal for datasets up to 200 rows where you want offline, local analytical reports without any external lookups, live predictions, or professional assessments.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:38:51.906Z","isFirstParty":false,"canonicalSlug":"sampling-observations-analyzer-record-quality-audit-string-27cc7ba9"}