{"uid":"cap_yy6S2dIfUFxT-0vg6isRk","slug":"join-coverage-analytics-string-normalisation-base-100-series-7d5f7dc4","name":"Join Coverage Analytics — String Normalisation + Base-100 Series","description":"Join coverage — String normalisation + Base-100 series: String normalisation + Base-100 series for supplied join coverage records (matched_rows, source_rows). 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-09-030?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","dataset_group","date","matched_rows","source_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"source_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"matched_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"dataset_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","source_rows":1,"matched_rows":10,"dataset_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","source_rows":2,"matched_rows":20,"dataset_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","source_rows":3,"matched_rows":15,"dataset_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","source_rows":4,"matched_rows":30,"dataset_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["matched_rows","source_rows"],"type":"string","default":"matched_rows"},"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_a57LfuUsgyhAuvZuuhX-u","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 string normalisation and Base-100 index series for join coverage metrics (matched_rows, source_rows) across up to 200 supplied data rows, returning two independent analytical reports.","exampleAgentPrompt":"Run string normalisation and a Base-100 series on my join coverage data — I have 4 rows across group-a and group-b from October 2026, with matched_rows values of 10, 20, 15, and 30, and source_rows of 1, 2, 3, 4. Use matched_rows as the field and base index 0.","exampleUseCases":[{"title":"ETL pipeline join quality audit","prompt":"I have daily join coverage records for two dataset groups across the past week — matched_rows and source_rows for each day. Can you run string normalisation and a Base-100 index series on the matched_rows field, starting from base index 0, so I can see how join quality has trended?"},{"title":"Cross-group coverage benchmarking","prompt":"I want to benchmark join coverage across my group-a and group-b datasets. I have about 50 rows with date, matched_rows, and source_rows. Run the string normalisation and Base-100 series on source_rows with base index 0 and give me the two reports."},{"title":"Data pipeline regression detection","prompt":"After a schema change last month, I suspect our join coverage dropped. I have 120 rows of matched_rows and source_rows data by date and dataset group. Can you compute the string normalisation and Base-100 indexed series on matched_rows starting at index 0 so I can spot where the regression happened?"}],"resultDescription":"Returns two independent analytical reports per call: (1) string-normalised values for the selected field (matched_rows or source_rows) across all supplied rows, and (2) a Base-100 index series anchored at the specified base_index row. Reports are computed locally from supplied data only — no external lookups or predictions are performed.","failureModes":["Rows array empty or missing — minimum 1 row required","More than 200 rows submitted — maxItems limit exceeded","Invalid date format (must match YYYY-MM-DD pattern)","row_id missing or empty string — required field","matched_rows or source_rows out of allowed numeric range (±1,000,000,000,000)","base_index out of range (0–199) or exceeds actual row count","field enum value not one of matched_rows or source_rows — validation error"],"whenToPreferThis":"Choose this endpoint when you have tabular join coverage data (matched_rows, source_rows) keyed by date and dataset group and need both string normalisation and a Base-100 time-indexed series in a single low-cost call. It is ideal for data engineers auditing ETL pipeline join quality, comparing coverage across groups, or detecting regressions over time — especially when you want offline, supplied-data-only computation with no external dependencies. At $0.01 USDC for two reports on up to 200 rows, it is cost-effective for batch analytical passes over moderate-sized datasets.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T18:54:28.216Z","isFirstParty":false,"canonicalSlug":"join-coverage-analytics-string-normalisation-base-100-series-7d5f7dc4"}