{"uid":"cap_LG9tp1WQ1i6UdZ991vFau","slug":"experiment-run-timing-record-quality-audit-string-normalisation-c491bb94","name":"Experiment Run Timing — Record Quality Audit + String Normalisation + Numeric Interval Filter","description":"Experiment run timing — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied experiment run timing records (run_seconds, sample_count). 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-13-197?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","course_group","date","run_seconds","sample_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"run_seconds":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"course_group":{"type":"string","default":"","maxLength":80},"sample_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","run_seconds":10,"course_group":"group-a","sample_count":1},{"date":"2026-10-02","row_id":"row-2","run_seconds":20,"course_group":"group-b","sample_count":2},{"date":"2026-10-03","row_id":"row-3","run_seconds":15,"course_group":"group-a","sample_count":3},{"date":"2026-10-04","row_id":"row-4","run_seconds":30,"course_group":"group-b","sample_count":4}],"maxItems":200,"minItems":1},"field":{"enum":["run_seconds","sample_count"],"type":"string","default":"run_seconds"},"maximum":{"type":"number","default":100,"maximum":1000000000000,"minimum":-1000000000000},"minimum":{"type":"number","default":0,"maximum":1000000000000,"minimum":-1000000000000}}},"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_vD2fiQliQ645fc2oSzB-j","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 local analytical reports on experiment run timing data: a record quality audit, string normalisation, and numeric interval filter for run_seconds or sample_count fields.","exampleAgentPrompt":"Can you run a quality audit, string normalisation, and numeric interval filter on these experiment run timing records — I've got up to 50 rows with row_id, course_group, date, run_seconds, and sample_count — filter on run_seconds between 0 and 300?","exampleUseCases":[{"title":"Pre-analysis data quality check","prompt":"I have 120 experiment run timing rows from our education study — can you audit them for quality issues, normalise the course_group strings, and filter out any run_seconds values outside the 5 to 600 range?"},{"title":"Cleaning course group labels","prompt":"Our experiment dataset has inconsistent course_group strings across 80 rows. Can you run string normalisation on them alongside a quality audit, using run_seconds as the filter field with a minimum of 0 and maximum of 500?"},{"title":"Validating sample counts before reporting","prompt":"Before I send this experiment data to the team, can you audit these 200 timing records for quality, normalise the strings, and filter sample_count values to only those between 1 and 1000?"}],"resultDescription":"Three independent analytical reports returned together: (1) a record quality audit flagging missing, null, or malformed values; (2) a string normalisation report for fields like course_group; and (3) a numeric interval filter report identifying rows where the chosen numeric field (run_seconds or sample_count) falls inside or outside the specified minimum–maximum range. All reports are computed locally from the supplied data with no external lookups.","failureModes":["Fewer than 1 row submitted — request rejected","More than 200 rows submitted — exceeds row limit","Invalid date format (not YYYY-MM-DD) — schema validation error","Field enum value not 'run_seconds' or 'sample_count' — rejected","Minimum greater than maximum — may produce empty interval filter results","Missing required fields (row_id) — row rejected or error returned","Payment not provided or insufficient USDC — 402 response"],"whenToPreferThis":"Choose this endpoint when you need to simultaneously quality-audit, normalise strings, and apply a numeric range filter to experiment run timing records (run_seconds, sample_count) in a single paid call. It is best when your dataset has up to 200 rows and you want all three reports bundled for $0.01 USDC rather than making separate calls. Prefer it over generic data cleaning tools when your data matches the experiment timing schema (course_group, date, run_seconds, sample_count).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-11-02T12:36:35.006Z","isFirstParty":false,"canonicalSlug":"experiment-run-timing-record-quality-audit-string-normalisation-c491bb94"}