{"uid":"cap_yVMAtSFUERPXF4BcVEM7o","slug":"feature-availability-analytics-category-frequencies-daily-sum-series-adb48b5d","name":"Feature Availability Analytics — Category Frequencies & Daily Sum Series","description":"Feature availability — Category frequencies + Daily sum series: Category frequencies + Daily sum series 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-10-102?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_cfFKXKXsX-tV3eykqK_w0","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":"Computes two analytical reports (category frequencies and daily sum series) for up to 200 feature availability records defined by populated_features and expected_features fields.","exampleAgentPrompt":"Analyze my feature availability data — I have up to 50 rows with date, dataset_group, populated_features, and expected_features — and give me both the category frequency breakdown and the daily sum series for the populated_features field.","exampleUseCases":[{"title":"Data completeness audit by group","prompt":"I have a dataset with daily feature availability records for two groups, 'group-a' and 'group-b', across October 2026 — can you run the category frequency and daily sum reports on the populated_features column so I can see which groups are filling in their data?"},{"title":"Expected vs populated feature trend","prompt":"Run analytics on my 120 feature availability records for Q3 — I want the category frequencies and daily sum series for the expected_features field so I can spot which days had unusually low expected feature counts."},{"title":"Pipeline feature coverage monitoring","prompt":"I'm monitoring a data pipeline and have 200 rows of feature availability logs with dates and dataset groups — generate the category frequency distribution and the daily sum series for populated_features so I can check for gaps or anomalies in coverage."}],"resultDescription":"Returns two independent analytical reports for the submitted rows: (1) a category frequency table showing how feature availability values are distributed across categories, and (2) a daily sum series aggregating the selected field (populated_features or expected_features) by date — both computed locally without external lookups.","failureModes":["More than 200 rows submitted — exceeds max row limit","Missing required fields (row_id, date, populated_features, expected_features) on any row — validation error","Invalid date format (must match YYYY-MM-DD pattern) — schema rejection","Numeric values outside allowed range (±1,000,000,000,000) — validation error","Empty rows array — minItems constraint violation","Invalid field enum value (must be 'populated_features' or 'expected_features') — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have structured feature availability records (with populated and expected feature counts per date and dataset group) and need both a category frequency summary and a daily aggregation series in a single low-cost call. Ideal for data quality audits, pipeline monitoring, and completeness reporting on up to 200 rows without needing live lookups or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:46:40.485Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-category-frequencies-daily-sum-series-adb48b5d"}