{"uid":"cap_tY09NDxfXO5hKOONY3xGW","slug":"feature-availability-analytics-record-quality-audit-string-3908bf23","name":"Feature Availability Analytics — Record Quality Audit, String Normalisation & Adjacent Row Changes","description":"Feature availability — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied feature availability records (populated_features, expected_features). 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-analytics-10-200?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","populated_features","expected_features"],"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},"expected_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"populated_features":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","expected_features":1,"populated_features":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","expected_features":2,"populated_features":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","expected_features":3,"populated_features":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","expected_features":4,"populated_features":30}],"maxItems":200,"minItems":1},"field":{"enum":["populated_features","expected_features"],"type":"string","default":"populated_features"}}},"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_UACP2vMQmkUQPcd1DMnaz","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 independent analytical reports (record quality audit, string normalisation, and adjacent row change detection) on up to 200 feature availability records containing populated_features and expected_features fields.","exampleAgentPrompt":"Can you run the three-part quality check on my feature availability records — audit record quality, normalise strings, and flag adjacent row changes — for this batch of up to 200 rows with populated_features and expected_features fields across my dataset groups?","exampleUseCases":[{"title":"ML feature store completeness audit","prompt":"I have a batch of 150 feature availability records from our ML pipeline with populated_features and expected_features counts per date and dataset group — can you audit their record quality, normalise any string fields, and flag where adjacent rows show unexpected changes?"},{"title":"Daily data pipeline quality check","prompt":"Run the record quality audit, string normalisation, and adjacent row change detection on these 80 feature availability rows from our daily ETL run — I need to spot any gaps between what's populated versus what was expected."},{"title":"Dataset group feature coverage review","prompt":"I've got feature availability records across three dataset groups covering October 2026 — please check them for quality issues, normalise the strings, and tell me where there are notable changes between consecutive rows in the populated_features field."}],"resultDescription":"Three independent analytical reports returned together: (1) a record quality audit highlighting issues such as nulls, out-of-range values, or missing fields in the feature availability rows; (2) a string normalisation report identifying and standardising inconsistent string representations; (3) an adjacent row change report detecting significant differences between consecutive rows in the chosen numeric field (populated_features or expected_features). All reports are computed locally with no external lookups.","failureModes":["Submitting more than 200 rows will be rejected (maxItems constraint)","Missing required fields (row_id, date, populated_features, expected_features) will cause validation errors","Malformed date strings not matching YYYY-MM-DD pattern will fail schema validation","Numeric values outside the allowed range (-1e12 to 1e12) will be rejected","Payment failure or insufficient USDC balance will prevent the call from completing"],"whenToPreferThis":"Choose this endpoint when you need three bundled data quality reports — record quality audit, string normalisation, and adjacent row change detection — on feature availability data (populated vs expected feature counts) in a single low-cost call. It is best suited for batch sizes up to 200 rows and situations where no live lookup, external enrichment, or predictive modelling is required. It is more cost-efficient than calling separate audit, normalisation, and change-detection services individually.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:46:57.978Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-record-quality-audit-string-3908bf23"}