{"uid":"cap_zJ6PqZfrZBgSM9pq3i0Ro","slug":"hermes-data-repair-plan-api-3ee9b7f1","name":"Hermes Data Repair Plan API","description":"Agent utilities for company research, package maintenance intelligence, dependency vulnerability checks, counterparty availability, SEC company snapshots, OFAC sanctions screening, and deterministic JSON/CSV data-quality work. Company domain intelligence includes a free preview before the paid enrichment call.","url":"https://hermes-counterparty-api.onrender.com/v1/repair-plan","method":"POST","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input"],"properties":{"input":{"type":"object","required":["type","method","bodyType","body"],"properties":{"body":{"oneOf":[{"type":"object","required":["format","records"],"properties":{"format":{"type":"string","const":"json"},"records":{"type":"array","items":{"type":"object"}}}},{"type":"object","required":["format","data"],"properties":{"data":{"type":"string"},"format":{"type":"string","const":"csv"}}}]},"type":{"type":"string","const":"http"},"method":{"enum":["POST"],"type":"string"},"bodyType":{"enum":["json","form-data","text"],"type":"string"}},"additionalProperties":false},"output":{"type":"object","required":["type"],"properties":{"type":{"type":"string"},"example":{"type":"object"}}}}},"responseSchema":{"type":"json","example":{"issues":{"duplicate_rows":1,"missing_values":0,"constant_fields":["id"],"mixed_type_fields":[],"identifier_integrity_fields":[]},"actions":[{"code":"DEDUPLICATE_ROWS","priority":1,"affected_count":1,"recommendation":"Remove or reconcile exact duplicate rows before downstream use."}],"quality_score":90,"schema_version":"1.0","schema_fingerprint":"sha256:example"}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.02","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":"$0.02/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.02","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_GqIs-lrQV61TKBIAI0-Sl","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.02","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Analyzes a JSON or CSV dataset and returns a prioritized repair plan identifying data-quality issues like duplicates, missing values, mixed types, and constant fields.","exampleAgentPrompt":"Can you analyze this JSON records array for data quality issues and give me a prioritized repair plan? I want to know about duplicate rows, missing values, constant fields, and mixed types before I load it into production.","exampleUseCases":[{"title":"Pre-ingestion ETL data audit","prompt":"I have a JSON array of 5,000 customer records I'm about to ingest into our data warehouse — can you run a data quality check and tell me what issues need fixing first, along with a quality score?"},{"title":"CSV export validation before reporting","prompt":"Before I share this CSV export with the finance team, can you check it for duplicates, missing values, and any columns that are all the same value? Give me a prioritized list of what to clean up."},{"title":"Catching mixed-type schema drift","prompt":"My pipeline has been pulling records from three different sources into one JSON array and I suspect the field types are inconsistent — can you audit it for mixed-type fields and identifier integrity problems?"}],"resultDescription":"Returns a JSON object containing: a quality_score (0-100), an issues summary (duplicate_rows count, missing_values count, constant_fields list, mixed_type_fields list, identifier_integrity_fields list), a prioritized actions array (each with a code, priority rank, affected_count, and recommendation string), plus a schema_version and sha256 schema_fingerprint.","failureModes":["Missing required 'input' field returns a validation error","Body format mismatch (e.g. declaring 'json' but sending 'csv' string) causes parse failure","Empty records array may return a trivially perfect quality score with no actionable recommendations","Payment not included or insufficient USDC (x402) results in 402 Payment Required","Malformed JSON objects in the records array may cause schema inference errors","Very large payloads may hit hosting-tier (Render free tier) timeout limits"],"whenToPreferThis":"Choose this endpoint when you need a deterministic, structured audit of a JSON or CSV dataset before downstream use — especially for ETL pipelines, reporting workflows, or agent-driven data cleaning tasks. It is preferable to ad-hoc LLM analysis when you need a reproducible quality score and a machine-readable, prioritized action list. Best for tabular data with clear record boundaries; not suited for unstructured text, images, or nested documents.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-15T00:39:47.199Z","isFirstParty":false}