{"uid":"cap_kN_wSy1iTUQMsp8TFPymG","slug":"feature-availability-analytics-exact-row-deduplication-adjacent-row-e08639f6","name":"Feature Availability Analytics: Exact Row Deduplication + Adjacent Row Changes","description":"Feature availability — Exact row deduplication + Adjacent row changes: Exact row deduplication + Adjacent row changes for supplied feature availability records (populated_features, expected_features). 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-10-046?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_Ng8AD1bKMMun7tk9yd7Y-","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":"Performs exact row deduplication and adjacent row change detection on feature availability records (populated_features, expected_features) for up to 200 rows, returning two independent analytical reports.","exampleAgentPrompt":"Can you run exact row deduplication and adjacent row change detection on my feature availability data? I have 4 rows with columns row_id, dataset_group, date, populated_features, and expected_features — use populated_features as the field and check rows from 2026-10-01 to 2026-10-04 across group-a and group-b.","exampleUseCases":[{"title":"Deduplication audit for ML feature pipeline","prompt":"I have a batch of 50 feature availability records tagged by date and dataset group — can you run exact row deduplication on them using populated_features as the field so I can clean up my ML pipeline before training?"},{"title":"Detecting feature count drift between consecutive dates","prompt":"I need to find where expected_features changed between consecutive rows in my dataset — run the adjacent row changes report on these 120 records grouped by dataset_group and date."},{"title":"Data quality check on populated vs expected features","prompt":"Can you check my feature availability log for both duplicate rows and day-over-day changes? I have records for 3 groups over the past month and I want both the deduplication and adjacent change reports for populated_features."}],"resultDescription":"Two independent analytical reports: (1) an exact row deduplication report identifying which of the supplied rows are exact duplicates, and (2) an adjacent row changes report showing where consecutive rows differ in the selected field (populated_features or expected_features). Both reports are computed locally from the supplied data with no external lookups.","failureModes":["More than 200 rows submitted — request rejected with maxItems validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","Missing required fields (row_id, dataset_group, date, populated_features, expected_features) — request rejected","field enum value not in ['populated_features','expected_features'] — validation error","Numeric values outside allowed range (±1,000,000,000,000) — validation error","Empty rows array (minItems:1 not met) — request rejected"],"whenToPreferThis":"Choose this endpoint when you need both exact row deduplication and adjacent row change detection on feature availability records in a single low-cost call ($0.01 USDC for both reports). It is best suited for datasets up to 200 rows where all data is supplied directly (no live lookups needed). Prefer this over general-purpose analytics tools when your data specifically tracks populated_features and expected_features by date and dataset_group, and you want structured, reproducible local analysis without sending data to an external prediction or ML service.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T07:19:40.256Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-exact-row-deduplication-adjacent-row-e08639f6"}