prompt
FreeEnforce schema-compliant JSON extraction from any text
FreeFree tier
About prompt
A specialized system prompt designed to convert unstructured text into strictly valid JSON objects adhering to a user-provided schema. It enforces type safety, handles missing data with designated null values, and outputs only raw JSON without any preamble. Includes rules for multi-record extraction and a validation checklist to ensure compliance.
Key Features
Schema-driven extraction that strictly follows user-defined fields
Type safety enforcement for string, number, boolean, array, and object types
Automatic handling of missing data with designated null values per type
Source fidelity: extracts only what exists in the text, no invention
No preamble output: returns only the JSON object
Multi-record extraction support with ordered array output
Built-in validation checklist before final output
Ambiguity handling for dates, numbers, booleans, and arrays
Pros & Cons
Pros
- Ensures generated JSON is valid and matches the schema exactly
- Reduces hallucination by strictly adhering to source text
- Handles edge cases like missing data with explicit null values
- Supports extraction of multiple records from a single text input
- Clear and reusable prompt that can be applied to various domains
Cons
- Requires the user to define a schema beforehand, adding upfront effort
- Output quality heavily depends on the underlying AI model's ability to follow instructions
- May be overly rigid for simple extractions where flexibility is acceptable
- No built-in error recovery if the schema is incompatible with the source text
Best For
Converting customer feedback or survey responses into structured dataParsing invoices or receipts into a predefined JSON schemaAutomating data entry from freeform text into databasesExtracting structured information from log files or error messagesBuilding data pipelines that require consistent JSON output from LLMs
FAQ
Can I use this prompt with any AI model?
The prompt is designed for LLMs that support system prompts and JSON output. It has been synthesized from sources like Anthropic's Structured Outputs docs and production patterns, so it works best with models that follow instructions precisely.
What happens if the input text lacks some fields from the schema?
Missing fields are automatically filled with designated null values: empty string for string, null for number and boolean, empty array for array, empty object for object.
Does this prompt work for extracting multiple records?
Yes. The prompt includes multi_record_extraction rules that instruct the model to return a JSON array of objects in the order they appear in the source text.
Can I modify the schema on the fly?
The prompt expects the user to provide a schema. It does not generate or infer schemas. You must supply a valid JSON schema as part of your request.