{"uid":"cap_lxx6lFixz0J-RZpmV8UeT","slug":"content-length-observations-adjacent-row-changes-explicit-missing-b1d3104b","name":"Content Length Observations — Adjacent Row Changes + Explicit Missing-Value Fill","description":"Content length observations — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied content length observations records (word_count, heading_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-web-19-162?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","site_group","date","word_count","heading_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"site_group":{"type":"string","default":"","maxLength":80},"word_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"heading_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","site_group":"group-a","word_count":10,"heading_count":1},{"date":"2026-10-02","row_id":"row-2","site_group":"group-b","word_count":20,"heading_count":2},{"date":"2026-10-03","row_id":"row-3","site_group":"group-a","word_count":15,"heading_count":3},{"date":"2026-10-04","row_id":"row-4","site_group":"group-b","word_count":30,"heading_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["word_count","heading_count"],"type":"string","default":"word_count"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_EI4n6J7RDYWSoSjNO5v1m","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":"Analyzes up to 200 rows of content length data (word_count, heading_count) by computing adjacent row changes and filling missing values using zero, mean, or median strategies.","exampleAgentPrompt":"I have 150 rows of dated content observations for two site groups with some null word_count values — can you run the adjacent row changes report and fill the missing word_count values using median imputation?","exampleUseCases":[{"title":"Impute missing word counts for content audit","prompt":"I've got a dataset of 80 content pages across two site groups with dates from January, and some word_count entries are null — fill those missing word_count values using median and also show me the row-by-row changes."},{"title":"Track heading count drift across site groups","prompt":"Can you analyze adjacent row changes in heading_count for my 120-row content dataset grouped by site group and date, and fill any missing heading_count entries with zero?"},{"title":"Clean content length data before reporting","prompt":"Before I run my weekly content report, I need to fill missing word_count values using mean imputation and compute the adjacent row deltas — I have about 200 rows of content observations with site_group and date fields."}],"resultDescription":"Two analytical reports: (1) a row-by-row adjacent change analysis showing deltas between consecutive records for the selected field, and (2) an explicit missing-value fill report replacing null entries in the chosen field using the specified strategy (zero, mean, or median). Both reports are computed locally with no external lookups.","failureModes":["Exceeding 200 rows returns an error or truncation","Invalid date format (not YYYY-MM-DD) causes schema rejection","Missing required fields (row_id, date, site_group) cause validation failure","Unsupported method enum value outside zero/mean/median causes rejection","Empty rows array returns an error due to minItems:1 constraint"],"whenToPreferThis":"Choose this endpoint when you need offline, deterministic analysis of content length time series — specifically adjacent row delta computation and structured missing-value imputation — on datasets of up to 200 rows. Ideal when no live data lookup, prediction, or external API call is needed, and when the cost of a quick local analytical pass ($0.01 USDC for two reports) is acceptable.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:49:28.586Z","isFirstParty":false,"canonicalSlug":"content-length-observations-adjacent-row-changes-explicit-missing-b1d3104b"}