Tutorials Prompt Engineering Tutorial
Schema Validation — Complete Guide
Schema Validation — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of Prompt Engineering Tutorial on Toolliyo Academy.
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Prompt Engineering Tutorial · Lesson 36 of 100
Schema Validation
Prompts → Apps
Prompts · 1 — Basics · ~6 min · Module 4: Structured Outputs
What is this?
Schema validation checks LLM output against JSON Schema or Zod before your app uses it — the guardrail after generation.
Why should you care?
PromptVerse Output Validator rejects malformed classifier payloads before Mongo insert.
See it live — copy this example
Copy the prompt into ChatGPT, Claude, or your LLM API playground and compare outputs.
const Ajv = require("ajv");
const ajv = new Ajv();
const validate = ajv.compile(ticketSchema);
const data = JSON.parse(llmText);
if (!validate(data)) {
throw new ValidationError(validate.errors);
}What happened?
- Compile schema once.
- Parse then validate.
- Errors array feeds self-correction prompt or dead-letter queue.
Practice next
- Write schema for one endpoint.
- Test valid and invalid samples.
- Pipe errors to retry prompt.
- Use enum for closed label sets.
- Add maxLength on free text fields.
Remember
Validate every LLM JSON response. Errors drive retry. Monitor validation failure rate.
Bad webhook day
Model returns extra field breaking CRM.
Outcome: Validator blocks write; retry fixes payload.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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