{"uid":"cap_dgbSPbQ1d1AMWbHfr83wx","slug":"market-survey-observations-record-quality-audit-numeric-row-ordering-f12d808e","name":"Market Survey Observations — Record Quality Audit + Numeric Row Ordering","description":"Market survey observations — Record quality audit + Numeric row ordering: Record quality audit + Numeric row ordering for supplied market survey observations records (respondent_count, 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-company-06-007?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","respondent_count","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},"company_group":{"type":"string","default":"","maxLength":80},"sample_weight":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"respondent_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","sample_weight":1,"respondent_count":10},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","sample_weight":2,"respondent_count":20},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","sample_weight":3,"respondent_count":15},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","sample_weight":4,"respondent_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["respondent_count","sample_weight"],"type":"string","default":"respondent_count"}}},"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_VtN3hJA0TcBiNvinzLrNH","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 two analytical reports on market survey observation rows: a record quality audit and a numeric row ordering, for up to 200 rows with respondent_count or sample_weight fields.","exampleAgentPrompt":"Can you run a record quality audit and numeric row ordering on my market survey data? I have 4 rows with respondent counts and sample weights for group-a and group-b across October 2026 dates, and I want the analysis done on the respondent_count field.","exampleUseCases":[{"title":"Survey data quality check before analysis","prompt":"I have a batch of 50 market survey observation records with respondent counts and sample weights across several company groups — can you run a record quality audit on them and also order them by respondent_count so I can spot any anomalies before I do my analysis?"},{"title":"Sample weight validation for weighted survey results","prompt":"Before I compute weighted averages from my survey, I need to audit the quality of my sample_weight values and get the rows ordered numerically by sample_weight — I have about 120 rows with row IDs, company groups, and dates from Q3 2025."},{"title":"Identifying bad records in multi-group survey dataset","prompt":"Can you check my market survey dataset for record quality issues and rank all rows by respondent_count? There are 80 rows covering different company groups and dates in 2024, and I want to catch any nulls or suspect values before reporting."}],"resultDescription":"Returns two reports: (1) a record quality audit flagging issues such as nulls, out-of-range values, or malformed fields across the supplied rows, and (2) a numeric row ordering ranking rows by the selected field (respondent_count or sample_weight). No external lookups or predictions are made — all analysis is performed locally on the supplied data.","failureModes":["More than 200 rows submitted — exceeds maxItems limit","Missing required fields (row_id, date, respondent_count, sample_weight) causes validation error","Invalid date format (not YYYY-MM-DD) rejected by pattern constraint","Invalid field enum value (anything other than respondent_count or sample_weight) causes error","Empty rows array (minItems:1 not satisfied) returns error","Payment not provided or insufficient — x402 payment required at $0.01 USDC"],"whenToPreferThis":"Choose this endpoint when you have market survey observation data (up to 200 rows) and need both a data quality audit and a numeric ordering report in a single low-cost call. It is ideal for pre-analysis data validation workflows where you want to identify record issues and rank rows by respondent_count or sample_weight without any external data lookups or model predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-03T06:38:05.811Z","isFirstParty":false,"canonicalSlug":"market-survey-observations-record-quality-audit-numeric-row-ordering-f12d808e"}