{"uid":"cap_ien4xrGkSa36c8T_Se9EB","slug":"database-query-runs-string-normalisation-07efb491","name":"Database Query Runs – String Normalisation","description":"Database query runs - String normalisation: String normalisation for Database query runs. Up to 200 supplied typed records. Local descriptive analytics; no enrichment or forecast. One of 25 new profiles across 20 shared operations in this industry. 0.01 USDC includes one bounded string normalisation report.","url":"https://market.datapackvibe.com/x402/assistant-ar-analytics-database-query-runs-normalise?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","database","date","execution_ms","rows_scanned"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"database":{"type":"string","default":"","maxLength":80},"execution_ms":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"rows_scanned":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","database":"group-a","execution_ms":10,"rows_scanned":1},{"date":"2026-10-02","row_id":"row-2","database":"group-b","execution_ms":20,"rows_scanned":2},{"date":"2026-10-03","row_id":"row-3","database":"group-a","execution_ms":15,"rows_scanned":3},{"date":"2026-10-04","row_id":"row-4","database":"group-b","execution_ms":30,"rows_scanned":4}],"maxItems":200,"minItems":1}}},"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_LKljFhkzi8RCTzjwl3QhI","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":"Normalises string fields (database name, row ID) across up to 200 database query run records and returns a local descriptive analytics report.","exampleAgentPrompt":"Can you normalise the string fields in my database query run records? I have 4 rows: row-1 ran on 2026-10-01 against database group-a taking 10ms scanning 1 row, row-2 on 2026-10-02 against group-b taking 20ms scanning 2 rows, row-3 on 2026-10-03 against group-a taking 15ms scanning 3 rows, and row-4 on 2026-10-04 against group-b taking 30ms scanning 4 rows.","exampleUseCases":[{"title":"Cleaning inconsistent database name labels","prompt":"I've collected query run logs from multiple teams and the database names are all over the place — some say 'Prod-DB', others 'prod_db', 'PROD DB', etc. Can you run string normalisation on these records so I get a consistent, clean report? I have about 50 rows with row IDs, dates, execution times in ms, and rows scanned."},{"title":"Pre-processing query logs before aggregation","prompt":"Before I aggregate my database query performance data for the month, I need to normalise the string fields — especially the database names and row IDs — to make sure grouping works correctly. Can you run the string normalisation report on my 120 query run records?"},{"title":"Auditing string quality in query run exports","prompt":"I exported 80 database query run records from our monitoring tool and I suspect the database name field has formatting inconsistencies. Can you run a string normalisation analysis on them so I can see what needs fixing before I import them into our data warehouse?"}],"resultDescription":"A bounded string normalisation report covering the submitted database query run records (up to 200 rows), including descriptive analytics on the string fields such as database name and row ID — highlighting inconsistencies, normalised forms, and local statistics. No external enrichment or forecasting is included.","failureModes":["Empty rows array returns validation error","More than 200 rows submitted exceeds maxItems limit","Missing required fields (row_id, database, date, execution_ms, rows_scanned) causes schema rejection","Invalid date format (not YYYY-MM-DD) fails pattern validation","Numeric fields out of allowed range cause rejection","Payment not provided or insufficient USDC balance blocks the request"],"whenToPreferThis":"Choose this endpoint when you need a quick, local string normalisation and descriptive analytics report specifically for database query run records (with fields like database name, row ID, date, execution_ms, rows_scanned) and do not need external enrichment, forecasting, or aggregation across other data types. It is ideal for data quality pre-processing steps before downstream aggregation or warehousing of query performance logs.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T02:02:11.996Z","isFirstParty":false,"canonicalSlug":"database-query-runs-string-normalisation-07efb491"}