{"uid":"cap_e3Ki1NP5emy_f7EXUiynZ","slug":"market-survey-observations-record-quality-audit-adjacent-row-changes-d0c5a3da","name":"Market Survey Observations — Record Quality Audit + Adjacent Row Changes","description":"Market survey observations — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes 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-06-011?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_MaT-U0ohVD4Taz05OmRbO","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 adjacent row change detection for respondent_count or sample_weight fields.","exampleAgentPrompt":"Can you run a record quality audit and adjacent row changes report on my market survey data — I have rows for group-a and group-b across a few dates in October 2026, each with respondent_count and sample_weight, and I want to check the respondent_count field?","exampleUseCases":[{"title":"Survey data quality check before reporting","prompt":"I've got 50 rows of market survey observations from our quarterly study — each row has a company group, date, respondent count, and sample weight. Can you run a record quality audit and flag any adjacent row changes in the respondent_count field before I hand this off to the client?"},{"title":"Detecting sample weight jumps across dates","prompt":"I need to spot any sudden jumps or drops in sample_weight between consecutive dates in my survey dataset — it covers two company groups over the past month. Can you run the adjacent row changes report and also audit the records for quality issues?"},{"title":"Pre-analysis data validation for survey panel","prompt":"Before we analyze our panel survey results, can you check these 120 observation rows for record quality problems and also show me where the respondent_count changes between adjacent rows for group-a and group-b?"}],"resultDescription":"Returns two independent reports: (1) a record quality audit flagging issues in the supplied survey observation rows (e.g. nulls, out-of-range values, formatting problems), and (2) an adjacent row changes report showing differences between consecutive rows for the selected field (respondent_count or sample_weight). Both reports are computed locally on the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected due to maxItems limit","Missing required fields (row_id, company_group, date, respondent_count, sample_weight) cause validation errors","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Invalid field enum value (not respondent_count or sample_weight) causes rejection","Empty rows array (minItems: 1 not met) causes failure","Numeric values outside allowed range trigger validation errors"],"whenToPreferThis":"Choose this endpoint when you have market survey observation data (up to 200 rows) with respondent_count and sample_weight fields and need both a data quality audit and adjacent row change detection in a single low-cost call. It is ideal for pre-analysis validation of survey panel data where you want to catch quality issues and detect temporal jumps without any external data lookups or predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T06:43:27.153Z","isFirstParty":false,"canonicalSlug":"market-survey-observations-record-quality-audit-adjacent-row-changes-d0c5a3da"}