Summary  
This chapter covers validating and debugging JSON payloads by iteratively diagnosing syntax errors with a validator or AI assistant and applying core formatting rules (double quotes for keys/strings, no trailing commas, proper brackets, correct primitive types) to produce clean, valid JSON.  

General domain of usage  
Web APIs

JSON breaks easily, and when it does, your workflow stops cold. The goal here is simple, **find the exact issue**, **fix it fast**, and return a **clean, valid payload**. No guessing and no rewriting everything,  just **quick diagnosis**, **precise corrections**, and **instant revalidation** to keep the workflow moving.

### Validator

Use an online JSON validator or formatter.

1. Paste the JSON into a validator;
2. Click **Format/Validate**;
3. Read the first error, note the **line and column**, and what the parser **expected**.
4. Fix **that** one issue only;
5. Revalidate and repeat until it turns green.

### LLM Assist

When you don't have time to hunt through lines of text.

1. Paste the exact JSON payload **and** the error message into an AI assistant;
2. Ask for a **corrected JSON object or array only**;
3. If it still fails, paste the new validator error and iterate once or twice.

Validators show only the first error. Always fix from **top to bottom**, many problems chain from a single missing quote or bracket.

Note

Most JSON errors disappear when you follow a few rules: use double quotes for all keys and strings, never leave trailing commas, keep booleans lowercase and unquoted, and treat numbers as real numbers, not strings. Use objects `{}` for a single item with fields and arrays `[]` for lists. If the format is invalid, n8n or any API will reject it immediately, exactly as JSON is meant to.

What is the best first step when fixing broken JSON?

n8n is a flexible automation platform for connecting apps, transforming data, and building AI-powered workflows. You'll develop strong fundamentals through real, practical examples, covering triggers, JSON handling, data-flow theory, AI integration, webhooks, and complete automation builds. The focus is on understanding how information moves through a workflow and how to structure that information so nodes and APIs behave predictably. The result is the ability to design, debug, and ship reliable automations that work end to end.

A practical overview of n8n's environment, core tools, and the mindset needed to build automations. Concepts include using AI effectively, understanding how data flows through nodes, importing templates, and transforming raw inputs into structured output.

A focused exploration of the essential workflow components. Triggers, data manipulation nodes, HTTP requests, webhooks, and flow control logic. The material builds a clear mental model for how executions start, how data is shaped, and how routing decisions are made.

A deep dive into how n8n represents and processes data. Topics include JSON structure, reading full payloads, repairing malformed JSON, handling arrays and objects, and working with binary files. The goal is predictable, confident data handling across all workflows.

A step-by-step transformation of an ODT plan into a structured automation blueprint. The material covers reliable RSS feeds, preparing data for LLMs, generating tweets with Airtable loops, designing outcome-driven flows, and mapping the full workflow inside Miro.

A complete build from initial concept to final output. Topics include structuring the flow, normalizing API data, looping, error-proofing, and writing back to Airtable with polished automation that demonstrates end-to-end reliability and clarity.

Fixing JSON Fast

Validator

LLM Assist

Common Mistakes Validators Catch

Awesome!

Fixing JSON Fast

Validator

LLM Assist

Common Mistakes Validators Catch