{"uid":"cap_C17DIv9IoJ4mbPquZ8plY","slug":"coco-csv-lint-f23686d3","name":"CoCo CSV Lint","description":"Zach Riehn's lab: an about-me and portfolio, a news desk, The Atelier for AI experiments, Launch Lab for XRP research, and Fracture for games.","url":"https://cocoeatsai.com/area4/agent/tools/csv-lint?utm_source=zero.xyz","method":"GET","headers":{},"bodySchema":{"type":"object","$schema":"https://json-schema.org/draft/2020-12/schema","required":["input","output"],"properties":{"input":{"type":"object","required":["type","method","queryParams"],"properties":{"type":{"const":"http"},"method":{"enum":["GET"]},"queryParams":{"type":"object","properties":{}}},"additionalProperties":false},"output":{"type":"object","required":["type","example"],"properties":{"type":{"const":"json"},"example":{"type":"object","required":["delimiter"],"properties":{"delimiter":{"type":"string"}}}}}}},"responseSchema":{"type":"json","example":{"ok":true,"rows":1,"header":["name","value"],"columns":2,"delimiter":",","ragged_rows":{},"column_profile":[{"name":"name","type":"text","empty":0,"distinct":1},{"name":"value","type":"integer","empty":0,"distinct":1}],"duplicate_rows":[],"duplicate_row_count":0,"duplicate_header_names":[]},"exampleNote":"Computed offline with demonstration inputs; time/random values are illustrative."},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.001","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":"$0.001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_glILRF85iNXai9LTCkn_L","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.001","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Validates and profiles a CSV file, detecting delimiters, column types, duplicate rows, ragged rows, and other data quality issues.","exampleAgentPrompt":"Can you lint this CSV file for me and tell me if there are any duplicate rows, ragged rows, what delimiter it uses, and the data types of each column?","exampleUseCases":[{"title":"Pre-import data quality check","prompt":"Before I load this CSV into my database, can you check it for any issues like ragged rows, duplicate entries, or mismatched column types?"},{"title":"Delimiter and structure detection","prompt":"I have a CSV file and I'm not sure if it's comma-separated or tab-separated — can you analyze it and tell me the delimiter, number of columns, and what each column contains?"},{"title":"Duplicate row audit","prompt":"Can you scan this CSV and tell me exactly which rows are duplicates, how many there are, and whether any column headers are repeated?"}],"resultDescription":"Returns a JSON object with: ok status, total row count, column count, detected delimiter, array of column names (header), column profiles (name, inferred type, empty count, distinct count), list of duplicate rows, duplicate row count, ragged row map, and any duplicate header names.","failureModes":["Malformed or empty CSV input returns an error or unexpected structure","Very large CSV files may time out or hit payload limits","CSV with no header row may cause incorrect column profiling","Binary or non-UTF-8 encoded files may produce garbled results","Network or payment failure returns a 402 or connection error"],"whenToPreferThis":"Choose this endpoint when you need a quick, inexpensive automated quality check on a CSV file before ingesting it into a pipeline, database, or analysis tool. It is especially useful for detecting structural issues (ragged rows, bad delimiters, duplicate headers) and column-level profiling in a single call, without needing a full ETL tool.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-19T12:44:44.422Z","isFirstParty":false,"canonicalSlug":"coco-csv-lint-f23686d3"}