{"uid":"cap_FEKJvqDztoGQgSp9vwFed","slug":"feature-availability-analytics-record-quality-audit-exact-row-e952ca27","name":"Feature Availability Analytics — Record Quality Audit + Exact Row Deduplication + Daily Sum Series","description":"Feature availability — Record quality audit + Exact row deduplication + Daily sum series: Record quality audit + Exact row deduplication + Daily sum series 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-10-215?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_pU7kby0W0GHtnWoDAc81p","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 (record quality audit, exact row deduplication, and daily sum series) on up to 200 feature availability records containing populated_features and expected_features fields.","exampleAgentPrompt":"Can you run a record quality audit, exact row deduplication, and daily sum series on my feature availability data? Here are up to 200 rows with row_id, dataset_group, date, populated_features, and expected_features — I want all three reports for the populated_features field.","exampleUseCases":[{"title":"Feature coverage completeness audit","prompt":"I have a batch of feature availability records with populated_features and expected_features by date and dataset group — can you run a quality audit, deduplicate exact rows, and show me daily sums so I can see where coverage is dropping?"},{"title":"Deduplication check on ingested feature logs","prompt":"We ingested feature availability logs from two pipelines and I suspect there are duplicate rows. Can you run exact row deduplication plus a record quality audit on these 150 rows and tell me what's redundant or bad quality?"},{"title":"Daily aggregation of expected vs populated features","prompt":"I need a daily sum series for the expected_features column across these feature availability records grouped by date — also run a quality audit and deduplicate while you're at it, here are the rows."}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging null values, format issues, and completeness problems; (2) an exact row deduplication report identifying fully duplicate records; and (3) a daily sum series aggregating the selected field (populated_features or expected_features) by date — all computed locally without external lookups.","failureModes":["Submitting more than 200 rows returns a validation error","Missing required fields (row_id, date, populated_features, expected_features) causes row-level rejection","Malformed date strings not matching YYYY-MM-DD pattern cause parse failures","Null values in both numeric fields may produce incomplete sum series","Empty rows array rejected due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously audit data quality, remove exact duplicate records, and compute daily aggregated sums on feature availability data in a single low-cost call. It is ideal for small-to-medium batches (up to 200 rows) where you want three complementary reports without setting up a full analytics pipeline. Prefer alternatives if you need predictive modeling, live data lookups, outlier detection, or more than 200 rows processed at once.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-03T06:41:44.244Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-record-quality-audit-exact-row-e952ca27"}