{"uid":"cap_dYMPRUVQsCK51duNZgRO_","slug":"foundry-csv-cross-file-key-integrity-validator-58835a0e","name":"Foundry CSV Cross-File Key Integrity Validator","description":"Pay-per-request evidence and data tools: CSV validation and reconciliation, DNS/email configuration evidence, and bounded official weather, earthquake, vehicle, company and study records. Exact USDC prices, explicit JSON contracts and source provenance. No mailbox, ownership, medical or safety guarantees.","url":"https://foundry-par007-machine-revenue-mainnet.inference-chip-index.workers.dev/v2/data/csv-cross-file-key-integrity","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"child_csv":{"type":"string","maxLength":12000,"minLength":1},"child_key":{"type":"string","maxLength":100,"minLength":1},"trim_keys":{"type":"boolean","default":false},"parent_csv":{"type":"string","maxLength":12000,"minLength":1},"parent_key":{"type":"string","maxLength":100,"minLength":1},"blank_child_keys":{"enum":["reject","ignore"],"type":"string","default":"reject"}}},"responseSchema":{"type":"json","example":{"route":"csv-cross-file-key-integrity","result":{"status":"PASS","child_rows":2,"limitations":["Synthetic example hashes."],"parent_rows":2,"child_sha256":"0000000000000000000000000000000000000000000000000000000000000000","orphan_count":0,"parent_sha256":"0000000000000000000000000000000000000000000000000000000000000000","blank_child_rows":[],"blank_child_count":0,"blank_parent_rows":[],"orphan_child_rows":[],"blank_parent_count":0,"evidence_truncated":false,"matched_child_rows":2,"duplicate_parent_rows":[],"duplicate_parent_count":0},"observed_at":"2026-09-06T00:00:00Z"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.012","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":"$0.012/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.012","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.012","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_Z6yh7U4x0Pt-FOb3cytIE","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.012","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Validates referential integrity between two CSV files by checking whether all keys in a child CSV exist in a parent CSV, returning match/orphan/blank counts and SHA-256 hashes as evidence.","exampleAgentPrompt":"Check whether every `order_id` in my child CSV exists in the parent CSV (which uses `id` as its key column) — reject any blank child keys — and give me the orphan rows, match count, and SHA-256 hashes as evidence.","exampleUseCases":[{"title":"Pre-import database integrity check","prompt":"Before I load these two CSVs into Postgres, can you verify that every `customer_id` value in the transactions CSV actually exists in the customers CSV? Use `id` as the parent key and reject any blank transaction customer_ids. Show me which rows are orphans."},{"title":"Compliance audit trail for data reconciliation","prompt":"I need a tamper-evident check showing that all `invoice_number` entries in my payments CSV match records in the master invoices CSV — use `invoice_no` as the parent key, trim whitespace from both keys, and give me the SHA-256 hashes and orphan list for our compliance records."},{"title":"ETL pipeline data quality gate","prompt":"Run a referential integrity check on these two CSVs: the child file has a column called `product_sku` and the parent catalog uses `sku`. Ignore any blank SKUs in the child file and tell me how many rows passed, how many are orphans, and whether any parent SKUs appear more than once."}],"resultDescription":"A JSON object containing: a PASS or FAIL status; counts and row-level details of orphaned child rows (keys not found in parent), blank child/parent rows, and duplicate parent keys; the count of successfully matched child rows; SHA-256 hashes of both input CSVs for audit provenance; an observed_at timestamp; an evidence_truncated flag if row lists were capped; and a limitations array noting any caveats about the result.","failureModes":["CSV exceeds 12,000 character limit — request rejected","blank_child_keys set to 'reject' and blank keys present — FAIL status returned with blank_child_rows populated","child_key or parent_key column name not found in respective CSV — error or unexpected FAIL","Malformed CSV (unbalanced quotes, inconsistent columns) — parsing error","Payment of $0.012 USDC not received — HTTP 402 returned before processing"],"whenToPreferThis":"Choose this endpoint when you need verifiable, evidence-grade referential integrity checking between two CSV datasets with cryptographic provenance (SHA-256 hashes) and explicit per-row orphan/duplicate reporting — especially for compliance, audit, or pre-import ETL validation workflows. Prefer it over ad-hoc scripting when you need a pay-per-call, stateless check with no infrastructure setup and a machine-readable JSON contract.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T00:53:24.797Z","isFirstParty":false}