{"uid":"cap_3CVrRezhLtMt38mU6XDkV","slug":"data-pipeline-runs-string-normalisation-d7f68678","name":"Data Pipeline Runs – String Normalisation","description":"Data pipeline runs - String normalisation: String normalisation for Data pipeline 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-pipeline-runs-normalise?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","pipeline","date","processed_rows","rejected_rows"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"pipeline":{"type":"string","default":"","maxLength":80},"rejected_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"processed_rows":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","pipeline":"group-a","rejected_rows":1,"processed_rows":10},{"date":"2026-10-02","row_id":"row-2","pipeline":"group-b","rejected_rows":2,"processed_rows":20},{"date":"2026-10-03","row_id":"row-3","pipeline":"group-a","rejected_rows":3,"processed_rows":15},{"date":"2026-10-04","row_id":"row-4","pipeline":"group-b","rejected_rows":4,"processed_rows":30}],"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_vJg60tJdAS5NUr5EqElrB","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 in up to 200 data pipeline run records and returns a local descriptive analytics report on the normalised data.","exampleAgentPrompt":"Can you normalise the string fields in my pipeline run records? I have about 50 rows with pipeline names like 'group-a' and 'group-b', dates in YYYY-MM-DD format, and processed/rejected row counts — I want a clean descriptive analytics report back.","exampleUseCases":[{"title":"Cleaning ETL job log exports","prompt":"I've exported 120 rows of ETL job logs with pipeline names, run dates, and processed/rejected row counts, but the string fields are inconsistent — can you normalise them and give me a descriptive analytics summary?"},{"title":"Pre-analysis pipeline data standardisation","prompt":"Before I run my dashboard queries, I need the pipeline name strings in my 80 run records standardised — can you normalise them and return the cleaned analytics report?"},{"title":"Quality check on rejected rows data","prompt":"I have 40 data pipeline run records with messy string fields including pipeline labels and dates — please normalise the strings and give me the descriptive analytics breakdown of processed and rejected rows."}],"resultDescription":"A bounded string normalisation report containing descriptive analytics (local, no enrichment or forecasting) derived from the submitted pipeline run records, with normalised string fields across pipeline names, dates, and row counts.","failureModes":["Empty rows array or missing required fields (row_id, pipeline, date, processed_rows, rejected_rows) causes validation error","More than 200 items in the rows array exceeds the maxItems limit","Date strings not matching YYYY-MM-DD pattern fail schema validation","Numeric fields outside the allowed range cause rejection","Payment not fulfilled via x402 protocol results in 402 response"],"whenToPreferThis":"Choose this endpoint when you have up to 200 data pipeline run records and need string normalisation with local descriptive analytics at low cost ($0.01 USDC). It is ideal for cleaning pipeline name strings and standardising run record data before downstream analysis, without needing external enrichment or forecasting.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-16T18:48:37.011Z","isFirstParty":false,"canonicalSlug":"data-pipeline-runs-string-normalisation-d7f68678"}