{"uid":"cap_F2scUiOFeDqVZbLjyrqPI","slug":"label-review-adjacent-row-changes-base-100-series-c1111f70","name":"Label Review — Adjacent Row Changes + Base-100 Series","description":"Label review — Adjacent row changes + Base-100 series: Adjacent row changes + Base-100 series for supplied label review records (reviewed_records, changed_labels). 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-analytics-12-155?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","reviewed_records","changed_labels"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"dataset_group":{"type":"string","default":"","maxLength":80},"changed_labels":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"reviewed_records":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","dataset_group":"group-a","changed_labels":1,"reviewed_records":10},{"date":"2026-10-02","row_id":"row-2","dataset_group":"group-b","changed_labels":2,"reviewed_records":20},{"date":"2026-10-03","row_id":"row-3","dataset_group":"group-a","changed_labels":3,"reviewed_records":15},{"date":"2026-10-04","row_id":"row-4","dataset_group":"group-b","changed_labels":4,"reviewed_records":30}],"maxItems":200,"minItems":1},"field":{"enum":["reviewed_records","changed_labels"],"type":"string","default":"reviewed_records"},"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_XIRWWPZZavF1dpVwPpGUj","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 adjacent row changes and a base-100 index series for label review records (reviewed_records and changed_labels) across up to 200 rows.","exampleAgentPrompt":"Run adjacent row change analysis and a base-100 index series on my label review data — I have 4 rows with dates from 2026-10-01 to 2026-10-04, dataset groups group-a and group-b, and I want to analyze the reviewed_records field starting from base index 0.","exampleUseCases":[{"title":"Tracking label change velocity over time","prompt":"I have a week of daily label review records with reviewed_records and changed_labels counts per dataset group — can you compute the row-over-row changes and index them to a base of 100 starting from the first row, analyzing the changed_labels field?"},{"title":"Benchmarking annotation throughput by group","prompt":"Take my 20-row label review dataset with dates and group tags and give me both the adjacent row changes report and a base-100 series for reviewed_records, so I can see which groups are accelerating or slowing down relative to baseline."},{"title":"QA audit of labeling pipeline consistency","prompt":"I need to audit my labeling pipeline — can you run the adjacent row changes and base-100 index analysis on my 50-row dataset of reviewed_records values starting from base index 5, so I can spot any sudden spikes or drops?"}],"resultDescription":"Returns two analytical reports: (1) adjacent row changes showing the delta between consecutive rows for the selected field, and (2) a base-100 index series normalizing the selected field relative to the specified base row — both computed locally against the supplied label review data, with no external lookups or predictions.","failureModes":["Missing required fields (row_id, date, reviewed_records, changed_labels) cause validation errors","Date strings not matching YYYY-MM-DD pattern are rejected","More than 200 rows submitted exceeds the maxItems limit","base_index referencing a row out of range (>= row count) causes indexing failure","Null values in the selected field may produce incomplete series output","Non-numeric values in reviewed_records or changed_labels fail schema validation"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of label review records and need both sequential delta analysis (adjacent row changes) and relative trend visualization (base-100 indexing) in a single low-cost call. It is ideal for annotation pipelines, ML data quality audits, and labeling throughput monitoring where you want offline computation against your own supplied data without external dependencies.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:31.556Z","isFirstParty":false,"canonicalSlug":"label-review-adjacent-row-changes-base-100-series-c1111f70"}