{"uid":"cap_DqyeQf2JEOQsODkzSOMYP","slug":"cache-telemetry-record-quality-audit-string-normalisation-duplicate-458b8fcc","name":"Cache Telemetry — Record Quality Audit + String Normalisation + Duplicate Key Report","description":"Cache telemetry — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report for supplied cache telemetry records (hit_count, miss_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-software-06-192?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"rows":{"type":"array","items":{"type":"object","required":["row_id","component","date","hit_count","miss_count"],"properties":{"date":{"type":"string","default":"","pattern":"^\\d{4}-\\d{2}-\\d{2}$","maxLength":10},"row_id":{"type":"string","default":"","maxLength":80,"minLength":1},"component":{"type":"string","default":"","maxLength":80},"hit_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000},"miss_count":{"type":["number","null"],"maximum":1000000000000,"minimum":-1000000000000}},"additionalProperties":false},"default":[{"date":"2026-10-01","row_id":"row-1","component":"group-a","hit_count":10,"miss_count":1},{"date":"2026-10-02","row_id":"row-2","component":"group-b","hit_count":20,"miss_count":2},{"date":"2026-10-03","row_id":"row-3","component":"group-a","hit_count":15,"miss_count":3},{"date":"2026-10-04","row_id":"row-4","component":"group-b","hit_count":30,"miss_count":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_L32R3f2DUq8iM9TKJJb6p","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":"Audits, normalises, and deduplicates up to 200 cache telemetry records (hit_count, miss_count) producing three independent analytical reports using local engines.","exampleAgentPrompt":"Can you audit my cache telemetry data for quality issues, normalise the component strings, and flag any duplicate row IDs? I have about 50 rows with fields like row_id, component, date, hit_count, and miss_count.","exampleUseCases":[{"title":"Cache performance data quality check","prompt":"I have 120 rows of cache telemetry with hit_count and miss_count values collected over the last month — can you run a record quality audit on them and tell me which rows have issues?"},{"title":"Deduplicating cache telemetry pipeline output","prompt":"Our cache monitoring pipeline sometimes emits duplicate row_ids in the telemetry export. Can you scan these 80 records and give me a duplicate key report so I know which rows to drop?"},{"title":"Normalising component labels in cache data","prompt":"The component field in our cache telemetry has inconsistent capitalisation and spacing across about 60 rows — can you normalise those strings and show me what changed?"}],"resultDescription":"Three independent reports returned together: (1) a record quality audit flagging missing, null, or out-of-range values in the supplied rows; (2) a string normalisation report showing cleaned/standardised versions of string fields like component; (3) a duplicate key report identifying rows sharing the same row_id. All processing is performed locally with no external lookups or predictions.","failureModes":["Exceeding 200 rows returns a validation error","Missing required fields (row_id, component, date, hit_count, miss_count) in any row causes rejection","Invalid date format (not YYYY-MM-DD) triggers schema validation failure","Numeric values outside ±1,000,000,000,000 range are rejected","Empty rows array returns an error"],"whenToPreferThis":"Choose this endpoint when you need simultaneous data quality auditing, string normalisation, and duplicate detection on cache telemetry records (hit_count/miss_count) in a single low-cost call. It is ideal for pipelines that collect raw cache performance logs and need to validate and clean them before downstream analysis, without requiring any external data lookups or live system integrations.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-24T12:56:57.623Z","isFirstParty":false,"canonicalSlug":"cache-telemetry-record-quality-audit-string-normalisation-duplicate-458b8fcc"}