{"uid":"cap_xVbv78hCzObhUZO1d06N-","slug":"document-table-extractor-75dac219","name":"Document Table Extractor","description":"Extract Markdown, CSV, and plain-text tables into clean structured rows for agents and business workflows.","url":"https://i3p3mgbsn54dvlivnk6wbumal40eqtsn.lambda-url.us-east-1.on.aws/v1/document-table-extractor?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":null,"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.15","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"registry","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":"$0.15/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.15","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.15","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_yCeILVfU-mZLp0-THi4HM","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.15","costPer":"request","priority":0,"asset":null,"unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Extracts tables from Markdown, CSV, and plain-text documents into clean, structured rows ready for agent and business workflows.","exampleAgentPrompt":"Extract all the tables from this markdown report and give me the rows as clean structured data: [paste markdown here].","exampleUseCases":[{"title":"Pipeline ingestion from markdown reports","prompt":"I have a weekly markdown report with multiple tables showing sales figures — can you extract all the tables into clean structured rows so I can load them into our database?"},{"title":"CSV table cleanup for agent workflow","prompt":"Here's some raw CSV text with inconsistent formatting and extra whitespace — extract the table rows into clean structured data I can pass to the next step in my workflow."},{"title":"Plain-text table parsing from copied content","prompt":"I copied this plain-text table from a PDF and it looks messy — can you extract the headers and rows into proper structured data so I can work with it programmatically?"}],"resultDescription":"Returns clean, structured rows parsed from the detected tables in the input document, with headers and cell values normalized and ready for downstream processing in agent pipelines or business workflows.","failureModes":["No tables detected in the input document — returns empty result or error","Malformed or ambiguous table formatting that cannot be reliably parsed","Input too large or exceeds payload limits","Unsupported document format beyond Markdown, CSV, and plain text"],"whenToPreferThis":"Choose this endpoint when you need to extract tabular data from Markdown, CSV, or plain-text documents and need clean structured rows without writing custom parsing logic. Ideal for agent pipelines that receive documents with embedded tables and need to process rows programmatically. It complements the sibling data-normalization endpoint for full ETL-style workflows.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-10T12:34:38.710Z","isFirstParty":false,"canonicalSlug":"document-table-extractor-75dac219"}