{"slug":"netintel-dev-extract-table-899e7e","title":"Extract tabular data from messy text or HTML using Claude Haiku — detects column","host":"netintel.dev","method":"POST","resource":"https://netintel.dev/extract/table","category":"search","description":"Extract tabular data from messy text or HTML using Claude Haiku — detects columns and rows in unstructured content and returns clean structured JSON (columns + rows) so agents can turn pasted tables, HTML tables, and delimited text into usable data in one call.","price_listed":0.02,"price_asked":0.02,"state":"answering","state_label":"Answering","checks_7d":1,"answered_7d":1,"latency_ms_median":935,"reported_calls_30d":1,"reported_payers_30d":1,"networks":["eip155:8453","solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp"],"badge":"unverified","paid_checks_7d":0,"paid_ok_7d":0,"example_input":{"body":{"text":"product | price | qty\nWidget A | 5.00 | 10\nWidget B | 7.50 | 4"},"bodyType":"json","method":"POST","type":"http"},"output_schema":{"$schema":"https://json-schema.org/draft/2020-12/schema","properties":{"input":{"additionalProperties":false,"properties":{"body":{"properties":{"text":{"description":"The messy text or HTML containing tabular data to extract. Max 10000 words or 50KB. Aliases also accepted: content, html, csv, table, markdown, data.","type":"string"}},"required":["text"],"type":"object"},"bodyType":{"enum":["json","form-data","text"],"type":"string"},"method":{"enum":["POST"],"type":"string"},"type":{"const":"http","type":"string"}},"required":["type","method","bodyType","body"],"type":"object"},"output":{"properties":{"example":{"properties":{"cached":{"description":"True if served from the in-memory cache.","type":"boolean"},"column_count":{"description":"Number of columns detected.","type":"number"},"findings":{"description":"Informational findings (e.g. no_table_found, count_mismatch).","items":{"type":"string"},"type":"array"},"grade":{"description":"Letter grade A-F","type":"string"},"score":{"description":"Quality score 0-100","type":"number"},"table":{"description":"Parsed table: columns (array of column names), rows (array of objects keyed by column name), and row_count (number of rows). Empty columns/rows with row_count 0 when no tabular structure is detected.","type":"object"}},"type":"object"},"type":{"type":"string"}},"required":["type"],"type":"object"}},"required":["input"],"type":"object"},"history":[{"day":"2026-09-24","reachable":true,"status":402,"valid_402":true,"asked_usdc":0.02,"price_match":true,"latency_ms":935,"error":null}],"description_full":"Extract tabular data from messy text or HTML using Claude Haiku — detects columns and rows in unstructured content and returns clean structured JSON (columns + rows) so agents can turn pasted tables, HTML tables, and delimited text into usable data in one call.","last_updated":"2026-09-03T00:30:09.911Z","schemes":["exact"]}