{"uid":"cap_ZSTn2-8deV8LZoAUYLVnx","slug":"agentbit-app-text-to-json-extractor-f4f70b60","name":"agentbit.app Text-to-JSON Extractor","description":"Turn messy text into clean JSON. Pass text plus a field `schema` or plain `instructions`; get a validated JSON object back. Uses the provider JSON mode.","url":"https://agentbit.app/v1/ai/extract?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"text":{"type":"string","description":"Source text to extract from (required, up to ~16 KB)."},"schema":{"type":"object","description":"Optional map of field name → description of the value to extract."},"instructions":{"type":"string","description":"Optional plain-English extraction instructions (used if no schema)."}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.01","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":"$0.01/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.01","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_aQzL0sXJC-6bW3hj9Ouqt","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.01","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Converts unstructured text into a validated JSON object using a provided schema or plain-English extraction instructions.","exampleAgentPrompt":"Take this raw customer email and extract the sender's name, order number, and complaint topic as a clean JSON object — use the schema: {name: 'customer full name', order_number: 'order ID mentioned', complaint: 'main issue described'}.","exampleUseCases":[{"title":"Parse invoice text into fields","prompt":"I have this raw text from a scanned invoice — can you extract the vendor name, invoice number, total amount, and due date as structured JSON? Here's the text: 'Invoice #4521 from Acme Supplies. Total due: $3,240.00. Please remit by March 15, 2025.'"},{"title":"Structure survey free-text responses","prompt":"I've got a bunch of open-ended survey answers in plain text and I need to pull out the respondent's age, satisfaction level, and main feedback as JSON so I can load them into a database. Here's one: 'I'm 34 and overall pretty happy with the product, though shipping was way too slow.'"},{"title":"Extract contact details from email signature","prompt":"Can you parse this email signature text and extract the person's full name, job title, company, phone number, and email address into a clean JSON object? Here's the signature: 'Jane Doe | Senior Account Manager | GlobalCorp Inc. | +1 (415) 555-0192 | jane.doe@globalcorp.com'"}],"resultDescription":"A validated JSON object with the fields specified in the schema or derived from the plain-English instructions, populated with values extracted from the input text. The response conforms to JSON mode output, ensuring it is always parseable and structurally valid.","failureModes":["Input text exceeds ~16 KB limit — request may be truncated or rejected","No schema or instructions provided — extraction may be ambiguous or fail","Requested fields not present in source text — missing fields returned as null or omitted","Malformed schema object — may cause validation errors or incorrect extraction","Text is too ambiguous for reliable extraction — low-confidence values may be returned"],"whenToPreferThis":"Choose this endpoint when you have unstructured or semi-structured text and need a validated, schema-conforming JSON object back without writing custom parsing logic. It is particularly useful when the structure is defined at runtime (e.g. user-supplied schemas) or when plain-English instructions are more practical than formal schemas. Prefer this over general LLM calls when you need guaranteed JSON output with field-level extraction rather than a free-form narrative response.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:36:02.966Z","isFirstParty":false,"canonicalSlug":"agentbit-app-text-to-json-extractor-f4f70b60"}