{"uid":"cap_2t4yWDw7Ug7cfD7UEh7cJ","slug":"point-clouds-data-quality-audit-string-normalisation-numeric-row-3a2404c1","name":"Point Clouds Data Quality Audit, String Normalisation & Numeric Row Ordering","description":"Point clouds — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied point clouds records (point_count, file_mb). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.","url":"https://market.datapackvibe.com/x402/assistant-ib26-creative-22-196?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","asset_group","date","point_count","file_mb"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"file_mb":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"asset_group":{"type":"string","default":"","maxLength":80},"point_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","file_mb":1,"asset_group":"group-a","point_count":10},{"date":"2026-10-02","row_id":"row-2","file_mb":2,"asset_group":"group-b","point_count":20},{"date":"2026-10-03","row_id":"row-3","file_mb":3,"asset_group":"group-a","point_count":15},{"date":"2026-10-04","row_id":"row-4","file_mb":4,"asset_group":"group-b","point_count":30}],"maxItems":200,"minItems":1},"field":{"enum":["point_count","file_mb"],"type":"string","default":"point_count"}}},"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_U2w4zMFDi8BAE7tAFaEEf","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":"Runs three independent analytical reports on point cloud records: a record quality audit, string normalisation, and numeric row ordering for up to 200 rows of point_count and file_mb data.","exampleAgentPrompt":"Can you audit the data quality, normalise the asset group strings, and sort by point_count for these point cloud records: [{\"row_id\":\"r1\",\"asset_group\":\"Site A\",\"date\":\"2025-01-15\",\"point_count\":500000,\"file_mb\":120.5},{\"row_id\":\"r2\",\"asset_group\":\"site a\",\"date\":\"2025-01-16\",\"point_count\":null,\"file_mb\":85.2}]? I want all three reports.","exampleUseCases":[{"title":"LiDAR survey file inventory audit","prompt":"I have a list of 50 LiDAR point cloud files with row IDs, asset groups, dates, point counts, and file sizes in MB. Can you run a full quality audit, normalise the asset group names, and order them by file_mb so I can spot any bad records and get a clean sorted list?"},{"title":"3D scan data normalisation for pipeline ingestion","prompt":"Before I ingest these 3D scan records into our processing pipeline, can you check them for quality issues, standardise the asset_group strings, and sort by point_count? Here are the rows: [{\"row_id\":\"scan-01\",\"asset_group\":\"Building B\",\"date\":\"2024-11-01\",\"point_count\":1200000,\"file_mb\":340},{\"row_id\":\"scan-02\",\"asset_group\":\"building b\",\"date\":\"2024-11-02\",\"point_count\":980000,\"file_mb\":null}]."},{"title":"Point cloud batch QA for project handover","prompt":"We're handing over a project and need to validate the quality of our point cloud dataset records, normalise the group labels, and sort everything by point_count descending. Can you run those three reports on these 30 rows I'm sending?"}],"resultDescription":"Returns three independent analytical reports: (1) a record quality audit flagging missing, null, or malformed values across rows; (2) string normalisation results for the asset_group field; and (3) rows reordered numerically by the chosen field (point_count or file_mb). All processing is performed locally with no external lookups.","failureModes":["Empty rows array returns an error (minItems: 1)","More than 200 rows submitted exceeds maxItems limit","Invalid date format (not YYYY-MM-DD) fails pattern validation","Invalid field enum value (not point_count or file_mb) rejected","row_id missing or empty string fails minLength validation","Numeric fields outside allowed range rejected"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously audit data quality, normalise string fields, and sort by a numeric column on point cloud records (point_count, file_mb) in a single low-cost call. It is ideal for batch pre-processing of LiDAR or 3D scan metadata before ingestion into a pipeline, and when you want three bundled analytical reports without any external API calls or live data lookups.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-23T12:49:52.921Z","isFirstParty":false,"canonicalSlug":"point-clouds-data-quality-audit-string-normalisation-numeric-row-3a2404c1"}