{"uid":"cap_k0zNb7PooKXz2TcKOTCFu","slug":"training-assessments-data-quality-suite-record-audit-string-7ee13dd4","name":"Training Assessments Data Quality Suite (Record Audit + String Normalisation + IQR Outlier Flags)","description":"Training assessments — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags for supplied training assessments records (pre_score, post_score). 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-education-11-203?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","pre_score","post_score"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"pre_score":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"post_score":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"course_group":{"type":"string","default":"","maxLength":80}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","pre_score":10,"post_score":1,"course_group":"group-a"},{"date":"2026-10-02","row_id":"row-2","pre_score":20,"post_score":2,"course_group":"group-b"},{"date":"2026-10-03","row_id":"row-3","pre_score":15,"post_score":3,"course_group":"group-a"},{"date":"2026-10-04","row_id":"row-4","pre_score":30,"post_score":4,"course_group":"group-b"}],"maxItems":200,"minItems":1},"field":{"enum":["pre_score","post_score"],"type":"string","default":"pre_score"}}},"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_OdjP-tnCyiDAfxQNtHO4O","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 combined analytical reports on training assessment records — record quality audit, string normalisation, and IQR outlier detection — for up to 200 rows of pre_score/post_score data.","exampleAgentPrompt":"Can you run the full quality audit, string normalisation, and IQR outlier check on my training assessment records — I have up to 50 rows with row_id, course_group, date, pre_score, and post_score fields — and flag the outliers on the pre_score field?","exampleUseCases":[{"title":"Pre-training data quality gate","prompt":"Before I analyse my learner results, can you audit these 80 training assessment rows for record quality issues, normalise the course_group strings, and flag any IQR outliers in the post_score field so I know which records to clean up?"},{"title":"Post-course score anomaly detection","prompt":"I've got results from a recent corporate training rollout — 120 rows with pre and post scores across several course groups. Can you run the IQR outlier detection on pre_score plus the full record quality audit so I can spot any suspicious entries before reporting?"},{"title":"Quarterly assessment dataset validation","prompt":"We're preparing our quarterly training effectiveness report and need to validate the dataset first — please run the record quality audit, string normalisation, and IQR outlier flags on these 200 assessment records, checking the post_score field for outliers."}],"resultDescription":"Returns three independent analytical reports for the submitted rows: (1) a record quality audit identifying missing, malformed, or invalid fields; (2) a string normalisation report for text fields like course_group; and (3) IQR-based outlier flags for the selected numeric score field (pre_score or post_score), all computed locally without external lookups or predictions.","failureModes":["Submitting more than 200 rows will be rejected (maxItems constraint)","Missing required fields (row_id, course_group, date, pre_score, post_score) will cause validation failure","Invalid date format (not YYYY-MM-DD) will fail schema validation","field enum must be exactly 'pre_score' or 'post_score'; other values rejected","Empty rows array (minItems: 1) will fail validation","Payment of 0.01 USDC must be included via x402 protocol or request will be rejected"],"whenToPreferThis":"Choose this endpoint when you need three complementary data quality checks — record auditing, string normalisation, and statistical outlier detection — bundled in a single low-cost call for training assessment data. Ideal when you have up to 200 rows of pre/post score data and want a cost-efficient ($0.01 USDC for all three reports) pre-analysis validation step before downstream modelling or reporting, without requiring any external data lookups or live predictions.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T18:52:17.414Z","isFirstParty":false,"canonicalSlug":"training-assessments-data-quality-suite-record-audit-string-7ee13dd4"}