{"uid":"cap_J7hTNHs5g4wI-eieIG996","slug":"business-location-inventories-numeric-distribution-daily-sum-series-8a1648b9","name":"Business Location Inventories — Numeric Distribution + Daily Sum Series","description":"Business location inventories — Numeric distribution + Daily sum series: Numeric distribution + Daily sum series for supplied business location inventories records (location_count, verified_locations). 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-company-05-075?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","company_group","date","location_count","verified_locations"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"company_group":{"type":"string","default":"","maxLength":80},"location_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"verified_locations":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","company_group":"group-a","location_count":10,"verified_locations":1},{"date":"2026-10-02","row_id":"row-2","company_group":"group-b","location_count":20,"verified_locations":2},{"date":"2026-10-03","row_id":"row-3","company_group":"group-a","location_count":15,"verified_locations":3},{"date":"2026-10-04","row_id":"row-4","company_group":"group-b","location_count":30,"verified_locations":4}],"maxItems":200,"minItems":1},"field":{"enum":["location_count","verified_locations"],"type":"string","default":"location_count"}}},"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_IfMvUYIjjqOe2581BZLiz","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 numeric distribution statistics and daily sum time series for location_count and verified_locations fields in supplied business location inventory records (up to 200 rows, 2 reports per call).","exampleAgentPrompt":"Analyze my business location inventory records — I have rows with company_group, date, location_count, and verified_locations — and give me a numeric distribution report plus a daily sum series for location_count.","exampleUseCases":[{"title":"Multi-group location spread analysis","prompt":"I have inventory data for two company groups over the past month with daily location_count and verified_locations entries. Can you run a numeric distribution and daily sum series on the location_count field so I can see how locations are spread and totaled day by day?"},{"title":"Verified locations daily trend report","prompt":"Here are our business location records for groups A and B across October — each row has a date, company_group, location_count, and verified_locations. Generate a daily sum series and numeric distribution for verified_locations so I can track trends over time."},{"title":"Inventory data QA before reporting","prompt":"Before I finalize our quarterly report, can you run a numeric distribution and daily sum series on these location inventory rows — about 150 records with location_count values — so I can spot any anomalies in how the counts are distributed and summed across dates?"}],"resultDescription":"Returns two analytical reports derived from the supplied rows: (1) a numeric distribution breakdown (e.g. percentiles, frequency buckets, spread statistics) for the selected field (location_count or verified_locations), and (2) a daily sum time series aggregating that field by date — all computed locally on the supplied data with no external lookup.","failureModes":["Exceeds 200-row limit — request will be rejected; split into smaller batches","Missing required fields (row_id, date, location_count, verified_locations) cause validation errors","Malformed date strings not matching YYYY-MM-DD pattern rejected by schema","Null values in numeric fields may affect distribution statistics or produce partial results","Empty rows array returns an error as minItems is 1"],"whenToPreferThis":"Choose this endpoint when you need both a numeric distribution report and a daily sum time series from business location inventory data (location_count and/or verified_locations) in a single low-cost call. It is ideal for offline/batch analytical use cases on up to 200 rows of pre-collected data where no live data lookup, prediction, or external enrichment is needed. At $0.01 USDC per call covering 2 reports, it is cost-efficient for exploratory data analysis, QA, or recurring summarization workflows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T06:45:40.866Z","isFirstParty":false,"canonicalSlug":"business-location-inventories-numeric-distribution-daily-sum-series-8a1648b9"}