{"uid":"cap_4yosO3dhQv0NkHfJ26i8k","slug":"metadata-completeness-string-normalisation-missing-value-fill-2910d28a","name":"Metadata Completeness — String Normalisation + Missing-Value Fill","description":"Metadata completeness — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied metadata completeness records (present_fields, expected_fields). 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-web-05-037?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","site_group","date","present_fields","expected_fields"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"site_group":{"type":"string","default":"","maxLength":80},"present_fields":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"expected_fields":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","site_group":"group-a","present_fields":10,"expected_fields":1},{"date":"2026-10-02","row_id":"row-2","site_group":"group-b","present_fields":20,"expected_fields":2},{"date":"2026-10-03","row_id":"row-3","site_group":"group-a","present_fields":15,"expected_fields":3},{"date":"2026-10-04","row_id":"row-4","site_group":"group-b","present_fields":30,"expected_fields":4}],"maxItems":200,"minItems":1},"field":{"enum":["present_fields","expected_fields"],"type":"string","default":"present_fields"},"method":{"enum":["zero","mean","median"],"type":"string","default":"median"}}},"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_X4JQMn73FEAbyy_d6DLOX","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 strings and fills missing values in metadata completeness records (present_fields, expected_fields) for up to 200 rows, producing 2 analytical reports.","exampleAgentPrompt":"Take my metadata completeness records — I have 4 rows with site groups group-a and group-b, dates from 2026-10-01 to 2026-10-04, and some null present_fields values — normalise the strings and fill those missing values using median imputation, then give me 2 analytical reports.","exampleUseCases":[{"title":"Imputing missing completeness counts","prompt":"I have 150 rows of metadata completeness data with site groups and dates, but about 20 of them have null present_fields values. Can you fill those nulls using median imputation and normalise the string fields so everything is consistent?"},{"title":"Zero-filling expected fields for reporting","prompt":"My metadata completeness dataset has some missing expected_fields entries. Fill them with zero and normalise the site_group strings, then produce the two standard completeness reports for me — I have about 80 rows total."},{"title":"Pre-pipeline data quality cleanup","prompt":"Before I load my metadata completeness records into the warehouse, I need the strings normalised and any missing present_fields values filled using mean — here are 200 rows with row IDs, site groups, and dates. Can you run both reports?"}],"resultDescription":"Two analytical reports covering the supplied metadata completeness rows: one applying string normalisation to site_group and other string fields, and one with explicit missing-value fill (zero, mean, or median) applied to the chosen field (present_fields or expected_fields). Reports are generated locally without external lookups.","failureModes":["Rows array empty or exceeds 200 items — validation error","Invalid date format (not YYYY-MM-DD) — schema rejection","present_fields or expected_fields outside allowed numeric range — validation error","Invalid method enum value (not zero/mean/median) — rejection","Invalid field enum value — rejection","Missing required fields (row_id, site_group, date) — schema error"],"whenToPreferThis":"Choose this endpoint when you need lightweight, local string normalisation and missing-value imputation on metadata completeness records (present_fields / expected_fields) without any external lookups or ML predictions. It is ideal for pre-pipeline data quality cleanup on small-to-medium batches (up to 200 rows) where cost matters and you want two bundled analytical reports for $0.01 USDC.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-29T12:52:52.414Z","isFirstParty":false,"canonicalSlug":"metadata-completeness-string-normalisation-missing-value-fill-2910d28a"}