{"uid":"cap_xkf5Y2hMNk_SuVYCFg3F4","slug":"market-survey-observations-quality-audit-string-normalisation-numeric-a1686cdb","name":"Market Survey Observations — Quality Audit, String Normalisation & Numeric Row Ordering","description":"Market survey observations — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied market survey observations records (respondent_count, 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-company-06-196?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_uScWq-i8OMBXeFRw-5noq","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 on market survey observation records: a record quality audit, string normalisation, and numeric row ordering for respondent_count or sample_weight fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and numeric row ordering on my market survey data — here are up to 200 rows with row_id, company_group, date, respondent_count, and sample_weight — and focus the numeric ordering on the respondent_count field?","exampleUseCases":[{"title":"Survey data quality check before reporting","prompt":"I have 150 market survey observation rows with respondent counts and sample weights for two company groups over the past quarter — can you audit the record quality, normalise the company_group strings, and sort the rows by respondent_count so I can spot anomalies before I write my report?"},{"title":"Sample weight ordering for weighted analysis","prompt":"Before I run my weighted analysis, can you validate my survey records for quality issues, normalise the group labels, and order the rows numerically by sample_weight? I'll send you the full dataset with row IDs, company groups, dates, respondent counts, and sample weights."},{"title":"Market research data cleaning pipeline","prompt":"I need to clean up my market survey dataset of about 80 rows — run the record quality audit, string normalisation on company_group, and numeric ordering on respondent_count so I can hand off clean data to the research team."}],"resultDescription":"Three separate analytical reports: (1) a record quality audit identifying issues such as missing values or invalid formats in the supplied rows, (2) a string normalisation report standardising company_group and other text fields, and (3) a numeric row ordering report sorting rows by the selected field (respondent_count or sample_weight). All analysis is performed locally with no external lookups.","failureModes":["Exceeding 200 rows causes rejection","Missing required fields (row_id, company_group, date, respondent_count, sample_weight) returns validation error","Invalid date format (not YYYY-MM-DD) causes schema rejection","Unsupported field enum value causes error","Payment failure (insufficient USDC balance) blocks the request"],"whenToPreferThis":"Choose this endpoint when you need three bundled data-quality operations — audit, string normalisation, and numeric ordering — on market survey observation records in a single low-cost call. It is ideal for lightweight, offline data hygiene on datasets up to 200 rows without needing external lookups, predictions, or live data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T06:43:14.156Z","isFirstParty":false,"canonicalSlug":"market-survey-observations-quality-audit-string-normalisation-numeric-a1686cdb"}