{"uid":"cap_h6BaC48bw6Nb6eGar62Dr","slug":"dataset-reconciliation-031e1f24","name":"Dataset Reconciliation","description":"Reconcile two datasets you supply and get one answer plus every disagreement. Reports keys present on only one side, keys duplicated on either side, whether the join is really 1:1 or silently N:M, and field-level differences with the row number on each side. Numbers compare exactly on their decimal text, never through floating point, so 42.50 and 42.5 agree while 9007199254740992 and 9007199254740993 do not. A repeated key is compared as an unordered multiset. Nothing is fetched.","url":"https://api.zfinia.com/x402/v1/dataset-reconciliation?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"key":{"type":"array","items":{"oneOf":[{"type":"string"},{"type":"object","required":["left","right"],"properties":{"left":{"type":"string"},"right":{"type":"string"}},"additionalProperties":false}]},"maxItems":4,"minItems":1},"left":{"type":"object","required":["csv"],"properties":{"csv":{"type":"string","maxLength":262144},"name":{"type":"string","maxLength":64}},"additionalProperties":false},"right":{"type":"object","required":["csv"],"properties":{"csv":{"type":"string","maxLength":262144},"name":{"type":"string","maxLength":64}},"additionalProperties":false},"compare":{"type":"array","items":{"oneOf":[{"type":"string"},{"type":"object","required":["left","right"],"properties":{"left":{"type":"string"},"right":{"type":"string"}},"additionalProperties":false}]}},"delimiter":{"type":"string","maxLength":1,"minLength":1},"numeric_tolerance":{"oneOf":[{"type":"number","minimum":0},{"type":"string"}]}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.2","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":"$0.2/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.2","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.2","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_JoZgydAFDkoKsdjK5Dicp","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.2","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Reconciles two CSV datasets by key, reporting missing keys, duplicates, cardinality issues, and field-level differences using exact decimal comparison.","exampleAgentPrompt":"Can you reconcile these two CSVs for me — join them on the 'order_id' column and compare the 'amount' and 'status' fields, then tell me every row that disagrees, any keys only on one side, and whether the join is truly 1:1?","exampleUseCases":[{"title":"Post-migration data validation","prompt":"I just migrated our orders table to a new database. Can you reconcile the before and after CSVs joined on 'order_id', compare the 'total', 'status', and 'customer_id' fields, and flag every disagreement plus any rows that went missing?"},{"title":"Finance month-end close reconciliation","prompt":"I have two CSV exports — one from our billing system and one from the bank — both with a 'transaction_ref' key. Can you reconcile them, compare the 'amount' column exactly without floating-point rounding, and tell me every discrepancy and any transactions present on only one side?"},{"title":"Vendor data feed audit","prompt":"Our vendor sent us an updated product catalog CSV and I want to compare it against our internal catalog — join on 'sku', compare 'price' and 'stock_qty', and let me know if any SKUs are duplicated or missing on either side and what values changed."}],"resultDescription":"Returns a structured report with: keys present only in the left or right dataset, keys duplicated on either side, whether the join cardinality is 1:1 or N:M, and field-level value differences with row numbers from each side. Numeric comparisons are performed on exact decimal text (e.g. 42.50 vs 42.5 agree; high-precision integers are distinguished correctly).","failureModes":["CSV too large (exceeds 256KB per side)","Key column not found in one or both CSVs","Delimiter mismatch causing parse failures","More than 4 join keys specified","Malformed CSV input (unescaped quotes, inconsistent columns)","Numeric tolerance value invalid"],"whenToPreferThis":"Choose this endpoint when you need exact, auditable reconciliation of two tabular datasets joined by key — especially for financial, migration, or compliance use cases where floating-point imprecision would be unacceptable. Prefer it over general diff tools when you need cardinality analysis, duplicate detection, and row-level provenance all in one call. It is self-contained (fetches nothing externally) and deterministic.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T18:35:19.587Z","isFirstParty":false,"canonicalSlug":"dataset-reconciliation-031e1f24"}