{"uid":"cap_mTxIEwDaObpkHSj4cDs4n","slug":"tutorial-completion-record-quality-audit-and-string-normalisation-a2515d6c","name":"Tutorial Completion Record Quality Audit and String Normalisation","description":"Tutorial completion — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied tutorial completion records (starts, completions). 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-game-20-001?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","game_area","date","starts","completions"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"starts":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"game_area":{"type":"string","default":"","maxLength":80},"completions":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","starts":10,"game_area":"group-a","completions":1},{"date":"2026-10-02","row_id":"row-2","starts":20,"game_area":"group-b","completions":2},{"date":"2026-10-03","row_id":"row-3","starts":15,"game_area":"group-a","completions":3},{"date":"2026-10-04","row_id":"row-4","starts":30,"game_area":"group-b","completions":4}],"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_OMESxMzjGT7KnoTajlgBf","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 two independent analytical reports on supplied tutorial completion records — a record quality audit and string normalisation — for up to 200 rows, using local engines with no external lookups.","exampleAgentPrompt":"Can you audit the quality of these tutorial completion records and normalise the game_area strings? I have rows with row_id, game_area, date, starts, and completions — up to 200 rows — and I want two reports: one for record quality issues and one for normalised strings.","exampleUseCases":[{"title":"Pre-analysis data quality check","prompt":"Before I run my funnel analysis, can you audit these 150 tutorial completion rows for data quality issues and normalise the game_area labels? The rows have row_id, date, game_area, starts, and completions fields."},{"title":"Cleaning inconsistent game area labels","prompt":"My tutorial tracking dataset has messy game_area strings — things like 'Group A', 'group-a', and 'GROUP A' mixed together. Can you normalise them and flag any record quality problems across these 80 rows?"},{"title":"Weekly tutorial data validation","prompt":"I've exported this week's tutorial starts and completions data — about 60 rows — can you run a record quality audit and string normalisation report so I can spot any bad data before sending it to the dashboard?"}],"resultDescription":"Two independent analytical reports: (1) a record quality audit identifying issues such as missing values, out-of-range numbers, duplicate row IDs, or malformed dates across the supplied rows; and (2) a string normalisation report showing cleaned and standardised versions of string fields like game_area. No external data sources are used — analysis is performed locally on the supplied rows only.","failureModes":["Rows array is empty or missing — returns validation error","More than 200 rows supplied — rejected with maxItems error","row_id field missing or blank — schema validation failure","date field does not match YYYY-MM-DD pattern — rejected","starts or completions values outside allowed numeric range — schema rejection","Malformed JSON payload — parse error returned"],"whenToPreferThis":"Choose this endpoint when you have raw tutorial completion records (starts, completions by game area and date) that need pre-analysis data hygiene — specifically a quality audit and string normalisation — in a single low-cost call. It is ideal for batch offline validation of up to 200 rows without needing live data lookups, predictions, or external enrichment. Prefer it over general-purpose data cleaning tools when your data model matches the game/tutorial engagement schema (row_id, game_area, date, starts, completions).","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-26T12:31:58.530Z","isFirstParty":false,"canonicalSlug":"tutorial-completion-record-quality-audit-and-string-normalisation-a2515d6c"}