{"uid":"cap_EGPY2_lzycH9SGsMb7QVI","slug":"fact-check-workflow-string-normalisation-base-100-series-ca0b6da5","name":"Fact Check Workflow — String Normalisation + Base-100 Series","description":"Fact check workflow — String normalisation + Base-100 series: String normalisation + Base-100 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-18-030?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"},"base_index":{"type":"integer","default":0,"maximum":199,"minimum":0}}},"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_MG8yMj596QuzlZgBSPD-x","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 base-100 index series computation on fact-check workflow records (claims reviewed, references collected) for up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Can you run string normalisation and a base-100 series on my fact-check workflow data — I have 4 rows with channel groups 'group-a' and 'group-b', claims_reviewed values of 10, 20, 15, and 30 for dates 2026-10-01 through 2026-10-04, using claims_reviewed as the field and row index 0 as the base?","exampleUseCases":[{"title":"Newsroom claims volume trend analysis","prompt":"I have weekly fact-check data across two editorial channels with claims_reviewed counts for the last 6 months — can you normalise the labels and build a base-100 index series starting from week 1 so I can compare growth trends across channel groups?"},{"title":"References collected baseline comparison","prompt":"Run a base-100 series on my references_collected field across these 50 fact-check workflow rows, using row index 0 as the baseline, and normalise the channel_group strings — I want two reports back."},{"title":"Multi-channel fact-check audit","prompt":"I need to audit our fact-check workflow records for Q3 — can you normalise the channel group names and index the claims_reviewed numbers against our starting week so I can see how each group has scaled relative to the baseline?"}],"resultDescription":"Returns 2 analytical reports: one covering string normalisation of text fields (e.g. channel_group) and one providing a base-100 index series for the selected numeric field (claims_reviewed or references_collected) anchored to the specified base row. All analysis is performed locally on the supplied data with no external lookups.","failureModes":["Input array below minItems:1 — request rejected","date field does not match YYYY-MM-DD pattern — validation error","row_id missing or empty string — schema validation failure","base_index out of range (0–199) or exceeds actual row count — index error","Numeric field values outside ±1,000,000,000,000 range — rejection","More than 200 rows submitted — maxItems exceeded error"],"whenToPreferThis":"Choose this endpoint when you need offline, local analytical processing of fact-check workflow records specifically requiring both string normalisation and base-100 index series computation in a single call. It is well-suited for newsroom or editorial analytics pipelines where no live data lookup or external action is needed and cost must be kept low ($0.01 for 2 reports). Prefer it over general-purpose analytics APIs when your data is already collected and you need deterministic, reproducible index series anchored to a specific baseline row.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-30T12:37:40.154Z","isFirstParty":false,"canonicalSlug":"fact-check-workflow-string-normalisation-base-100-series-ca0b6da5"}