{"uid":"cap_Gt7o_BrUOLw-vcR_IYKMR","slug":"label-review-record-quality-audit-base-100-series-5a22d668","name":"Label Review — Record Quality Audit + Base-100 Series","description":"Label review — Record quality audit + Base-100 series: Record quality audit + 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-12-012?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_AqpDaYVlWczUZmVd4aV51","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 analytical reports on label review data: a record quality audit and a Base-100 index series for reviewed_records or changed_labels across up to 200 rows.","exampleAgentPrompt":"Can you run a record quality audit and Base-100 index series on my label review data? I have 4 rows across two dataset groups (group-a and group-b) from 2026-10-01 to 2026-10-04, with reviewed_records counts of 10, 20, 15, 30 and changed_labels of 1, 2, 3, 4 — please index on reviewed_records starting from row index 0.","exampleUseCases":[{"title":"Annotation pipeline quality check","prompt":"I have a week's worth of label review records for two dataset groups — can you run a record quality audit and Base-100 index series on the reviewed_records field, using row index 0 as the base? Here are my 7 rows with dates, group names, reviewed_records, and changed_labels counts."},{"title":"Tracking label change rates over time","prompt":"Can you generate a Base-100 index series on changed_labels for my label review batch? I've got 15 rows spanning October, split across three dataset groups, and I want to use row index 0 as the base — plus a quality audit to flag any bad records."},{"title":"Comparing annotation throughput across groups","prompt":"Please audit data quality and compute a Base-100 series for reviewed_records across my annotation dataset groups — I have 50 rows from our QA pipeline with daily dates, group IDs, reviewed_records, and changed_labels, starting the index at position 0."}],"resultDescription":"Returns two independent analytical reports computed locally from supplied data: (1) a record quality audit flagging issues such as nulls, duplicates, or anomalies across the input rows, and (2) a Base-100 index series normalizing the chosen field (reviewed_records or changed_labels) relative to the specified base row index. No external data or live lookups are involved.","failureModes":["More than 200 rows submitted — request rejected due to maxItems constraint","Missing required fields (row_id, date, reviewed_records, changed_labels) — validation error","Date field does not match YYYY-MM-DD pattern — schema validation failure","base_index references a row index that does not exist in the submitted array","Numeric values outside allowed range (±1,000,000,000,000) — rejected by schema","Empty rows array submitted — minItems:1 constraint violated"],"whenToPreferThis":"Choose this endpoint when you have up to 200 rows of label review data and need both a data quality audit and a Base-100 normalization series in a single low-cost call ($0.01 USDC). It is ideal for ML annotation pipelines, QA teams monitoring label change rates, or analysts comparing dataset group throughput over time — without needing live lookups, predictions, or external data enrichment.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T00:54:16.231Z","isFirstParty":false,"canonicalSlug":"label-review-record-quality-audit-base-100-series-5a22d668"}