{"uid":"cap_UiKzjqst_RW58rkyZ_9Hs","slug":"sampling-observations-string-normalisation-adjacent-row-changes-632141c8","name":"Sampling Observations — String Normalisation + Adjacent Row Changes","description":"Sampling observations — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied sampling observations records (sample_value, 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-analytics-15-029?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},"field":{"enum":["sample_value","sample_weight"],"type":"string","default":"sample_value"}}},"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_cXnyZPJ2zXh8WaWpAT5cL","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":"Normalises string fields and detects adjacent row changes in sampling observation records (sample_value, sample_weight) for up to 200 rows, returning two analytical reports.","exampleAgentPrompt":"Can you normalize the string fields and detect adjacent row changes in my sampling observations? I have 4 rows: row-1 on 2026-10-01 with sample_value 10 and sample_weight 1 in group-a, row-2 on 2026-10-02 with sample_value 20 and sample_weight 2 in group-b, row-3 on 2026-10-03 with sample_value 15 and sample_weight 1 in group-a, and row-4 on 2026-10-04 with sample_value 30 and sample_weight 4 in group-b — run the analysis on the sample_value field.","exampleUseCases":[{"title":"Survey data string cleanup and change detection","prompt":"I have 50 rows of survey sampling observations with messy dataset_group labels and I need to normalize those strings and also flag wherever the sample_value changes between adjacent rows — dates run from 2025-01-01 to 2025-02-19, field is sample_value. Can you run both reports?"},{"title":"Lab sample weight shift monitoring","prompt":"I've got 120 lab sampling records from 2024-06-01 through 2024-10-28 across two groups, control and treatment, and I need to normalize the group name strings and identify any adjacent row changes in sample_weight. Please run both analytical reports on the sample_weight field."},{"title":"Retail inventory sample QA before ingestion","prompt":"Before I ingest my retail sampling observations into our pipeline, can you normalize all the string fields and detect adjacent row changes in sample_value? I'll send you up to 80 rows with row IDs, dates, dataset_group names, sample_value, and sample_weight."}],"resultDescription":"Returns two analytical reports: one covering string normalisation of text fields (e.g. dataset_group) across the submitted rows, and one identifying adjacent row-to-row changes in the specified numeric field (sample_value or sample_weight). Both reports are computed locally from the supplied data with no external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) causes rejection","Dates not matching YYYY-MM-DD pattern fail schema validation","row_id exceeding 80 characters is rejected","Numeric values outside ±1,000,000,000,000 fail schema constraints","Empty rows array (minItems:1 not met) returns an error"],"whenToPreferThis":"Use this endpoint when you need both string normalisation and adjacent row change detection on sampling observation records in a single call for up to 200 rows. Prefer it over general-purpose analytics when your data specifically carries sample_value and sample_weight fields and you want two focused reports without external lookups or live data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-15T12:37:49.209Z","isFirstParty":false,"canonicalSlug":"sampling-observations-string-normalisation-adjacent-row-changes-632141c8"}