{"uid":"cap_pAHwzkEcBeZhlyOwR_C5o","slug":"news-archive-completeness-string-normalisation-daily-sum-series-f09cb2e5","name":"News Archive Completeness — String Normalisation + Daily Sum Series","description":"News archive completeness — String normalisation + Daily sum series: String normalisation + Daily sum series for supplied news archive completeness records (indexed_items, expected_items). 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-23-027?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","channel_group","date","indexed_items","expected_items"],"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},"indexed_items":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"expected_items":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","channel_group":"group-a","indexed_items":10,"expected_items":1},{"date":"2026-10-02","row_id":"row-2","channel_group":"group-b","indexed_items":20,"expected_items":2},{"date":"2026-10-03","row_id":"row-3","channel_group":"group-a","indexed_items":15,"expected_items":3},{"date":"2026-10-04","row_id":"row-4","channel_group":"group-b","indexed_items":30,"expected_items":4}],"maxItems":200,"minItems":1},"field":{"enum":["indexed_items","expected_items"],"type":"string","default":"indexed_items"}}},"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_Donneh0M6cjGqLoPQhuPk","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 string normalisation and daily sum series analysis on up to 200 news archive completeness records (indexed_items, expected_items), returning two analytical reports per call.","exampleAgentPrompt":"I have 150 rows of daily news archive completeness data with channel groups like 'politics' and 'sports', each row having a date, indexed_items, and expected_items — can you run string normalisation plus a daily sum series on the indexed_items field and give me back two reports?","exampleUseCases":[{"title":"Daily indexing gap trend analysis","prompt":"I've got 90 days of news archive records across three channel groups — 'breaking-news', 'sports', and 'entertainment' — with indexed_items and expected_items per day. Can you compute a daily sum series on indexed_items so I can see how total indexing volume trends over time?"},{"title":"Channel group label normalisation","prompt":"My news archive completeness dataset has messy channel_group strings like 'Sports ', 'SPORTS', and 'sports' across 120 rows. Can you run string normalisation on those labels so I can group them consistently, alongside a daily sum on expected_items?"},{"title":"Expected vs indexed coverage audit","prompt":"Here are 200 rows of daily archive records for our news crawler — each has a date, a channel group, an indexed count, and an expected count. Run the string normalisation and daily sum series on expected_items so I can audit where our coverage is falling short."}],"resultDescription":"Two analytical reports: (1) a string normalisation report for the selected field across all supplied rows, and (2) a daily sum series aggregating the chosen numeric field (indexed_items or expected_items) by date — all computed locally from supplied data, with no external lookups or predictions.","failureModes":["Rows array empty or missing — validation error returned","More than 200 rows submitted — request rejected or truncated","Invalid date format (not YYYY-MM-DD) — row rejected or error","Null values in indexed_items/expected_items — may affect sum series output","Invalid field enum value (not 'indexed_items' or 'expected_items') — error response","Missing required fields (row_id, channel_group, date) — schema validation failure"],"whenToPreferThis":"Choose this endpoint when you need both string normalisation and daily sum series analysis on news archive completeness data in a single low-cost call, without requiring any external data sources, live lookups, or predictions. Ideal for pipelines that batch-process up to 200 archive records and need reproducible, locally-computed analytics on indexed vs expected item counts across channel groups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:53:08.264Z","isFirstParty":false,"canonicalSlug":"news-archive-completeness-string-normalisation-daily-sum-series-f09cb2e5"}