{"uid":"cap_kysrjsvrPXlxfoC_Ccs9A","slug":"feature-availability-analytics-numeric-interval-filter-trailing-mean-3976da7d","name":"Feature Availability Analytics: Numeric Interval Filter + Trailing Mean Series","description":"Feature availability — Numeric interval filter + Trailing mean series: Numeric interval filter + Trailing mean 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-10-126?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"},"window":{"type":"integer","default":2,"maximum":200,"minimum":2},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_lbXa58NOvFyoKwIf-h3h7","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 two local analytical reports on feature availability records — a numeric interval filter and a trailing mean series — over up to 200 supplied rows.","exampleAgentPrompt":"Analyze my feature availability data for the 'catalog' dataset group using the populated_features field — filter to rows where values fall between 0 and 500, then compute a trailing mean with a window of 7, across these 50 rows I'll supply.","exampleUseCases":[{"title":"Dataset completeness trend smoothing","prompt":"I have daily records of how many features were populated vs expected across two dataset groups over the past 3 months. Can you compute a trailing mean with a window of 14 on the populated_features field to smooth out daily noise?"},{"title":"Interval filter for anomaly scoping","prompt":"Filter my feature availability rows to only those where expected_features is between 10 and 250, and also give me a trailing mean series with a window of 5 so I can see the rolling average trend within that range."},{"title":"Comparing feature population across groups","prompt":"I've got 120 rows of feature availability data split across group-a and group-b. Run both the numeric interval filter — keeping populated_features between 5 and 100 — and a trailing mean with a window of 3 so I can compare trends across groups."}],"resultDescription":"Returns two analytical reports for the supplied rows: (1) a numeric interval filter listing which rows fall within the specified min/max range for the chosen field, and (2) a trailing mean series showing the rolling average of the chosen field over the configured window size. Both reports are computed locally without external lookups.","failureModes":["Supplying fewer than 1 or more than 200 rows returns a validation error","Window size less than 2 or greater than 200 is rejected","Invalid date format (not YYYY-MM-DD) causes schema validation failure","Minimum value greater than maximum value may produce empty filter results","Null values in populated_features or expected_features may affect trailing mean computation","Missing required row fields (row_id, date) causes request rejection"],"whenToPreferThis":"Choose this endpoint when you have up to 200 feature availability records and need both a numeric range filter and a trailing mean series computed together in a single call at low cost ($0.01). Ideal for data quality monitoring pipelines where you want to isolate records within a feature-count band and simultaneously smooth the time series. Not suitable for live data lookups, predictions, datasets exceeding 200 rows, or operations needing external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-20T06:52:06.565Z","isFirstParty":false,"canonicalSlug":"feature-availability-analytics-numeric-interval-filter-trailing-mean-3976da7d"}