{"uid":"cap_b7GI9CB57z3PXdAnux_Pz","slug":"null-coverage-duplicate-key-report-base-100-series-analyzer-2d107a8e","name":"Null Coverage Duplicate Key Report + Base-100 Series Analyzer","description":"Null coverage — Duplicate key report + Base-100 series: Duplicate key report + Base-100 series for supplied null coverage records (missing_values, total_values). 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-03-063?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","missing_values","total_values"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"total_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80},"missing_values":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","total_values":1,"dataset_group":"group-a","missing_values":10},{"date":"2026-10-02","row_id":"row-2","total_values":2,"dataset_group":"group-b","missing_values":20},{"date":"2026-10-03","row_id":"row-3","total_values":3,"dataset_group":"group-a","missing_values":15},{"date":"2026-10-04","row_id":"row-4","total_values":4,"dataset_group":"group-b","missing_values":30}],"maxItems":200,"minItems":1},"field":{"enum":["missing_values","total_values"],"type":"string","default":"missing_values"},"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_3f9QoosTsEDbQNlBzk-Ga","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":"Generates two local analytical reports — a duplicate key report and a base-100 indexed series — for user-supplied null coverage records containing missing and total value counts.","exampleAgentPrompt":"Run both a duplicate key report and a base-100 series on my null coverage data — here are 4 rows: row-1 on 2026-10-01 in group-a with 10 missing out of 1 total, row-2 on 2026-10-02 in group-b with 20 missing out of 2 total, row-3 on 2026-10-03 in group-a with 15 missing out of 3 total, and row-4 on 2026-10-04 in group-b with 30 missing out of 4 total. Use missing_values as the field and start the base-100 index at row 0.","exampleUseCases":[{"title":"Data pipeline duplicate key audit","prompt":"I have a batch of null coverage records from our ETL pipeline and I need to know if any row IDs are duplicated — can you run a duplicate key report on these rows: row-A on 2025-01-10 in group-sales with 5 missing out of 100 total, row-B on 2025-01-11 in group-sales with 5 missing out of 100 total, row-A on 2025-01-12 in group-ops with 8 missing out of 50 total? Use missing_values as the field and start the index at 0."},{"title":"Monthly completeness trend indexing","prompt":"Can you generate a base-100 series for my monthly data completeness records so I can see how total_values have changed relative to the first month? Here are the rows: jan on 2025-01-01 in group-finance with 200 missing out of 5000 total, feb on 2025-02-01 in group-finance with 180 missing out of 5200 total, mar on 2025-03-01 in group-finance with 150 missing out of 5100 total. Field should be total_values, base index at 0."},{"title":"Multi-group null coverage QA check","prompt":"I'm doing a quality audit across two dataset groups and need both a duplicate key check and a normalized index series — please analyze these 5 records: r1 on 2024-06-01 group-alpha 12 missing 300 total, r2 on 2024-06-02 group-beta 7 missing 280 total, r3 on 2024-06-03 group-alpha 15 missing 310 total, r1 on 2024-06-04 group-beta 9 missing 290 total, r5 on 2024-06-05 group-alpha 11 missing 305 total. Use missing_values, starting the base-100 index at position 0."}],"resultDescription":"Returns two independent analytical reports: (1) a duplicate key report identifying any repeated row_id values across the supplied rows, and (2) a base-100 indexed series for the selected numeric field (missing_values or total_values) anchored at the specified base_index row. Both reports are computed locally from the supplied data with no external lookups. Up to 200 rows are supported per call.","failureModes":["Missing required fields (row_id, date, missing_values, total_values) causes validation failure","Submitting more than 200 rows exceeds the maxItems limit and is rejected","Invalid date format (not YYYY-MM-DD) causes a pattern validation error","base_index out of range (>= number of submitted rows) may produce undefined indexing behavior","Null or negative values for total_values or missing_values are accepted but may produce unexpected base-100 results","Empty rows array (minItems:1 violated) returns an error"],"whenToPreferThis":"Choose this endpoint when you need both a duplicate key audit and a base-100 normalization series on null coverage data in a single cheap call ($0.01 USDC). It is ideal for data quality workflows where you want to verify row uniqueness and trend-index completeness metrics simultaneously, without any external data fetching or prediction. Best suited for batches of up to 200 rows of time-series null coverage records organized by dataset group.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-14T00:37:13.198Z","isFirstParty":false,"canonicalSlug":"null-coverage-duplicate-key-report-base-100-series-analyzer-2d107a8e"}