Updated August 27, 2026
AI JSON Output Checklist
AI-generated JSON should be treated as draft structured data. Parse it, check its shape, and review unexpected fields before it enters a workflow.
Validation checks
| Check | Why it matters | Local action |
|---|---|---|
| One main snippet | Multiple objects can make downstream parsers choose the wrong data. | Extract the intended object or array. |
| Valid JSON syntax | Trailing commas, comments, and prose break strict JSON parsers. | Parse before copying. |
| Required fields | Missing keys can break imports, templates, and app flows. | Check required keys with a small schema. |
| Expected value types | A string where an array is expected can pass visual review but fail code. | Compare common schema types. |
| Unexpected fields | Extra fields can signal prompt drift or unsupported details. | Warn on fields outside the schema. |
Shape is not truthJSON validation checks format and structure. It does not prove that titles, numbers, citations, or claims are correct.
References
Questions
What is the minimum useful JSON check?
Parse the JSON, confirm the top-level type, and verify required fields before using the output.
Should AI JSON be checked locally?
Yes when it contains drafts, internal data, or unpublished content. A local parser can catch many workflow-breaking issues.