{"uid":"cap_9sQI6HLQgghN7PZIxoCUN","slug":"queue-consumers-analytics-string-normalisation-secondary-measure-aa1bd12e","name":"Queue Consumers Analytics — String Normalisation + Secondary-Measure Weighted Mean","description":"Queue consumers — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied queue consumers records (queue_depth, processed_messages). 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-software-07-034?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","component","date","queue_depth","processed_messages"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"component":{"type":"string","default":"","maxLength":80},"queue_depth":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processed_messages":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","component":"group-a","queue_depth":10,"processed_messages":1},{"date":"2026-10-02","row_id":"row-2","component":"group-b","queue_depth":20,"processed_messages":2},{"date":"2026-10-03","row_id":"row-3","component":"group-a","queue_depth":15,"processed_messages":3},{"date":"2026-10-04","row_id":"row-4","component":"group-b","queue_depth":30,"processed_messages":4}],"maxItems":200,"minItems":1},"field":{"enum":["queue_depth","processed_messages"],"type":"string","default":"queue_depth"}}},"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_HAvyD_2dnvFDpS6xgTS1K","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 string normalisation and secondary-measure weighted mean calculations on up to 200 queue consumer records (queue_depth, processed_messages) and returns 2 independent analytical reports.","exampleAgentPrompt":"Can you run string normalisation and a secondary-measure weighted mean on these queue consumer records — I have 4 rows with queue_depth and processed_messages for components group-a and group-b across dates 2026-10-01 to 2026-10-04, and I want the analysis focused on queue_depth?","exampleUseCases":[{"title":"Queue depth normalisation for microservices","prompt":"I have 50 rows of queue consumer data from my microservices — each row has a component name, date, queue_depth, and processed_messages. Can you normalise the string fields and compute a weighted mean on queue_depth so I can compare components fairly?"},{"title":"Processed messages weighted mean analysis","prompt":"Run string normalisation and a secondary-measure weighted mean on my queue consumer dataset — 120 rows covering various components from 2026-09-01 to 2026-09-30, and focus the weighted mean calculation on processed_messages."},{"title":"Daily queue monitoring report generation","prompt":"I need two analytical reports on my queue consumer logs: string normalisation for the component names and a weighted mean for queue_depth. Here are 80 rows with row_id, component, date, queue_depth, and processed_messages — can you process them?"}],"resultDescription":"Returns 2 independent analytical reports: (1) a string normalisation report cleaning and standardising string fields across the supplied queue consumer rows, and (2) a secondary-measure weighted mean report computing weighted averages over the specified numeric field (queue_depth or processed_messages), all computed locally without external lookups.","failureModes":["More than 200 rows submitted — payload rejected due to maxItems constraint","Missing required fields (row_id, component, date, queue_depth, or processed_messages) — validation error","Invalid date format (not YYYY-MM-DD) — pattern validation failure","Numeric values outside allowed range (±1,000,000,000,000) — schema rejection","Empty rows array — minItems violation","Invalid field enum value (not queue_depth or processed_messages) — schema error"],"whenToPreferThis":"Choose this endpoint when you have tabular queue consumer data (up to 200 rows) and need both string normalisation of component/label fields AND a weighted mean computation on a secondary numeric measure in a single $0.01 call. Ideal for offline/batch analytical processing of queue monitoring data where no live lookup, prediction, or external data enrichment is required.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:46:10.077Z","isFirstParty":false,"canonicalSlug":"queue-consumers-analytics-string-normalisation-secondary-measure-aa1bd12e"}