{"uid":"cap_vMGP-L2_KCGN6RY3LOGpl","slug":"fact-check-workflow-string-normalisation-daily-sum-series-54e3253c","name":"Fact Check Workflow — String Normalisation + Daily Sum Series","description":"Fact check workflow — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied fact check workflow records (claims_reviewed, references_collected). 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-news-18-027?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","claims_reviewed","references_collected"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"channel_group":{"type":"string","default":"","maxLength":80},"claims_reviewed":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"references_collected":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","channel_group":"group-a","claims_reviewed":10,"references_collected":1},{"date":"2026-10-02","row_id":"row-2","channel_group":"group-b","claims_reviewed":20,"references_collected":2},{"date":"2026-10-03","row_id":"row-3","channel_group":"group-a","claims_reviewed":15,"references_collected":3},{"date":"2026-10-04","row_id":"row-4","channel_group":"group-b","claims_reviewed":30,"references_collected":4}],"maxItems":200,"minItems":1},"field":{"enum":["claims_reviewed","references_collected"],"type":"string","default":"claims_reviewed"}}},"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_x6kHEmcNdV-tC_COh8x7Q","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 fact-check workflow data: string normalisation of channel groups and a daily sum time series for claims_reviewed or references_collected, for up to 200 rows.","exampleAgentPrompt":"I have up to 200 rows of fact-check workflow data with dates, channel groups, claims_reviewed, and references_collected — can you run string normalisation on the channel groups and generate a daily sum series for claims_reviewed?","exampleUseCases":[{"title":"Daily claims reviewed trend report","prompt":"Here are 150 rows of our fact-checking workflow records with dates and channel groups — please normalize the channel group strings and give me a daily sum series for claims_reviewed so I can see how our verification volume changed day by day."},{"title":"References collected aggregation by date","prompt":"I've got fact-check workflow data across two channel groups over the past month — run the string normalization and daily sum series reports on references_collected so I can see daily totals across the dataset."},{"title":"Multi-channel fact-check data cleanup","prompt":"Our editorial team has 80 rows of fact-check records with inconsistent channel group labels — can you normalize those strings and also compute the daily sum series for claims_reviewed to help us spot any gaps in coverage?"}],"resultDescription":"Two analytical reports: (1) a string normalisation report standardising the channel_group field values, and (2) a daily sum time series aggregating the selected numeric field (claims_reviewed or references_collected) by date — both derived from the supplied rows without any external lookups.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, channel_group, date, claims_reviewed, references_collected) causes rejection","Invalid date format (non-YYYY-MM-DD) triggers schema validation failure","Null values in numeric fields may be excluded from daily sum calculations","Values outside the allowed numeric range cause input rejection","Payment failure (insufficient USDC) blocks the request"],"whenToPreferThis":"Choose this endpoint when you need both string normalization of categorical labels and a daily sum time series in a single low-cost call ($0.01 USDC) on structured fact-check workflow data up to 200 rows, without requiring any external data lookups, live APIs, or professional assessments.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T18:37:39.906Z","isFirstParty":false,"canonicalSlug":"fact-check-workflow-string-normalisation-daily-sum-series-54e3253c"}