{"uid":"cap_FcsXAj0siiFLDMZn0pvPb","slug":"schema-conformity-string-normalisation-base-100-series-ad6badc2","name":"Schema Conformity — String Normalisation + Base-100 Series","description":"Schema conformity — String normalisation + Base-100 series: String normalisation + Base-100 series for supplied schema conformity records (valid_records, checked_records). 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-02-030?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","valid_records","checked_records"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"valid_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"checked_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","valid_records":10,"checked_records":1},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","valid_records":20,"checked_records":2},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","valid_records":15,"checked_records":3},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","valid_records":30,"checked_records":4}],"maxItems":200,"minItems":1},"field":{"enum":["valid_records","checked_records"],"type":"string","default":"valid_records"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_1DMbIB17YqzuaDSYWlz_U","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 local analytical reports on schema conformity data: string normalisation and base-100 indexing for valid_records and checked_records fields across up to 200 rows.","exampleAgentPrompt":"Run the string normalisation and base-100 series reports on my schema conformity data — I have 4 rows for group-a and group-b dated 2026-10-01 through 2026-10-04 with valid_records values of 10, 20, 15, 30 and checked_records of 1, 2, 3, 4; use valid_records as the field and set the base index to row 0.","exampleUseCases":[{"title":"Indexing data quality metrics over time","prompt":"I have a month of daily schema conformity readings — 30 rows with valid_records and checked_records for two dataset groups. Can you index the valid_records field to a base of 100 starting from the first row so I can see how data quality has trended?"},{"title":"Normalising checked_records for cross-group comparison","prompt":"Normalise the checked_records values across my schema conformity dataset — I've got 50 rows split across three dataset groups, and I want string-normalised output alongside the base-100 series so I can compare groups fairly."},{"title":"Automated schema conformity reporting pipeline","prompt":"Every week I get a batch of up to 200 schema conformity rows. Can you run both the string normalisation and base-100 index reports on this week's batch using the checked_records field, with the base index set to 0?"}],"resultDescription":"Returns two independent analytical reports for the supplied schema conformity rows: (1) a string normalisation report standardising the selected field values across all rows, and (2) a base-100 index series anchored at the specified base_index row, both computed locally without external lookups. Up to 200 rows processed per call.","failureModes":["Fewer than 1 or more than 200 rows submitted — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Field value out of allowed numeric range (±1,000,000,000,000) — rejected","base_index out of range (0–199 or exceeding row count) — error","Missing required fields (row_id, date, valid_records, checked_records) — schema rejection","Extra properties in row objects — rejected due to additionalProperties:false"],"whenToPreferThis":"Choose this endpoint when you need two simultaneous local analytical reports — string normalisation and base-100 indexing — on schema conformity data (valid_records/checked_records) for up to 200 rows in a single low-cost call ($0.01 USDC). Prefer it over general-purpose analytics when your data already conforms to the required schema (row_id, dataset_group, date, valid_records, checked_records) and you want both normalisation and indexing in one shot without any external data enrichment or prediction.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T00:37:26.917Z","isFirstParty":false,"canonicalSlug":"schema-conformity-string-normalisation-base-100-series-ad6badc2"}