{"uid":"cap_MJcoWrlY80BB-43-ZYl2E","slug":"meeting-load-string-normalisation-numeric-interval-filter-d8512983","name":"Meeting Load String Normalisation + Numeric Interval Filter","description":"Meeting load — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter for supplied meeting load records (meeting_minutes, participant_count). 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-operations-03-026?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","team_group","date","meeting_minutes","participant_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"team_group":{"type":"string","default":"","maxLength":80},"meeting_minutes":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"participant_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","team_group":"group-a","meeting_minutes":10,"participant_count":1},{"date":"2026-10-02","row_id":"row-2","team_group":"group-b","meeting_minutes":20,"participant_count":2},{"date":"2026-10-03","row_id":"row-3","team_group":"group-a","meeting_minutes":15,"participant_count":3},{"date":"2026-10-04","row_id":"row-4","team_group":"group-b","meeting_minutes":30,"participant_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["meeting_minutes","participant_count"],"type":"string","default":"meeting_minutes"},"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_WP4qI6oY3WTt5x7MoKKmN","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":"Normalises string fields and filters meeting load records (meeting_minutes, participant_count) by a numeric interval, returning two analytical reports for up to 200 rows.","exampleAgentPrompt":"I have 4 rows of meeting data for groups A and B across October 2026 — can you normalise the string fields and filter to only keep records where meeting_minutes is between 0 and 100? Use the default sample rows.","exampleUseCases":[{"title":"Filter meetings by duration range","prompt":"I have a list of up to 50 team meeting records with columns row_id, team_group, date, meeting_minutes, and participant_count. Can you normalise the string fields and keep only the rows where meeting_minutes falls between 15 and 60? I want two reports back."},{"title":"Validate participant counts within bounds","prompt":"Here are 30 meeting log entries across several team groups. Please normalise the text fields and filter the records so I only see rows where participant_count is between 3 and 20. Give me the two analytical reports."},{"title":"Clean and segment meeting data by interval","prompt":"I've got 120 rows of meeting load data with dates, team groups, and numeric fields. Run string normalisation on the text columns and filter by meeting_minutes between 10 and 90. I need both reports from your local analytical engines."}],"resultDescription":"Two independent analytical reports covering string-normalised meeting load records and the subset of those records whose selected numeric field (meeting_minutes or participant_count) falls within the specified minimum–maximum interval, produced locally without external lookups or predictions, for up to 200 input rows.","failureModes":["More than 200 rows submitted — request rejected or truncated","Missing required fields (row_id, date, team_group, meeting_minutes, participant_count) — validation error","Invalid date format (not YYYY-MM-DD) — schema validation failure","minimum greater than maximum — potentially empty result set with no error","Numeric values outside allowed range (±1 trillion) — schema rejection"],"whenToPreferThis":"Choose this endpoint when you have meeting load data (meeting minutes and/or participant counts) that needs string field normalisation combined with numeric range filtering in a single low-cost call, and you require two structured analytical reports without any external data enrichment, live lookup, or prediction. It is ideal for offline batch cleaning and segmentation of meeting logs at up to 200 rows for $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:52:58.488Z","isFirstParty":false,"canonicalSlug":"meeting-load-string-normalisation-numeric-interval-filter-d8512983"}