{"uid":"cap_9dU2fK4Vuwp0yGdhlSbLQ","slug":"schema-conformity-analytics-string-normalisation-category-frequencies-c7b0d7a6","name":"Schema Conformity Analytics — String Normalisation + Category Frequencies","description":"Schema conformity — String normalisation + Category frequencies: String normalisation + Category frequencies 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-02-024?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}}},"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_veQPQJkVOfReHldwbSjr7","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":"Analyzes schema conformity records (valid_records, checked_records) to produce two analytical reports: string normalization and category frequency breakdowns, for up to 200 rows.","exampleAgentPrompt":"I have 4 schema conformity records — row-1 on 2026-10-01 in group-a with 10 valid out of 1 checked, row-2 on 2026-10-02 in group-b with 20 valid out of 2 checked, row-3 on 2026-10-03 in group-a with 15 valid out of 3 checked, and row-4 on 2026-10-04 in group-b with 30 valid out of 4 checked — can you run string normalization and category frequency analysis on these?","exampleUseCases":[{"title":"Data pipeline quality audit","prompt":"I've got 50 schema conformity rows from our nightly pipeline run, each tagged with a dataset_group, date, and counts of valid_records vs checked_records — can you run string normalization and category frequencies on all of them so I can see which groups are underperforming?"},{"title":"Monthly validation summary by group","prompt":"Here are 120 schema conformity records from last month across three dataset groups. Can you compute the category frequency breakdown and normalize the string fields so I can compare group-a, group-b, and group-c side by side?"},{"title":"Ad hoc conformity spot check","prompt":"I just pulled 10 records from our staging environment with valid_records and checked_records counts — run string normalization and category frequency reports on them so I can quickly spot any anomalies before we promote to production."}],"resultDescription":"Two analytical reports: (1) a string normalization report that standardizes and cleans text values across the submitted rows, and (2) a category frequency report showing count distributions across dataset_group values and other categorical fields — both computed locally without any external lookups, covering up to 200 submitted rows.","failureModes":["Empty or missing rows array returns an error","More than 200 rows submitted exceeds the maxItems limit and will be rejected","Rows missing required fields (row_id, dataset_group, date, valid_records, checked_records) fail schema validation","Date strings not matching YYYY-MM-DD pattern are rejected","Payment of 0.01 USDC not included or declined results in 402 response","Numeric values outside the ±1,000,000,000,000 range are rejected"],"whenToPreferThis":"Choose this endpoint when you need two fast, offline analytical reports — string normalization and category frequency distribution — on schema conformity data containing valid_records and checked_records fields, for batches of up to 200 rows, at a low flat cost of $0.01 USDC. It is ideal when you do not need external lookups, predictions, or ML inference, just deterministic local computation on your own conformity records.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T12:48:40.125Z","isFirstParty":false,"canonicalSlug":"schema-conformity-analytics-string-normalisation-category-frequencies-c7b0d7a6"}