I built a JSON repair tool for LLM output — here's why it exists

You ask an LLM for JSON. You get this:

json

{

"name": "test",

"valid": True,

"items": [1, 2,

markdown

Three problems in one response: markdown fences the LLM wasn't supposed to add, True instead of true (Python literal), and the response was cut off mid-array.

JSON.parse() throws on all three. A linter tells you what's wrong. But you're left fixing it manually.

I kept hitting this wall so often that I built a dedicated repair pipeline: AI JSONMedic.

Why existing tools don't cut it

JSONLint / JSONFormatter — great for valid-ish JSON with one missing comma. Not built for LLM failure modes: they flag errors but don't repair them.

jsonrepair (npm) — solid library, handles many cases. AI JSONMedic actually uses it as a last-resort fallback. But it doesn't tell you what it changed, and doesn't handle all the LLM-specific cases we needed.

The 14 failure modes we target

Through building this, we catalogued how LLMs specifically break JSON:

1. 
   Markdown fences — `json wrapping the output


2. 
   Trailing commas — [1, 2, 3,] (the model "runs out" of items but adds one more comma)


3. 
   Python literals — True, False, None instead of true, false, null
   


4. 
   Single quotes — {'key': 'value'} instead of double quotes


5. 
   Smart quotes — "key" (curly quotes from copy-paste)


6. 
   Unclosed brackets — truncated at max_tokens mid-array or mid-object


7. 
   Unclosed strings — "value without closing
   


8. 
   Concatenated objects — {"a":1}{"b":2} when streaming produces multiple chunks


9. 
   NDJSON — newline-delimited JSON that needs wrapping


10. 
    Python-style comments — # this is a comment inside JSON


11. 
    JavaScript-style comments — // inline or /* block */
    


12. 
    Escaped backslashes — \\n instead of \n
    


13. 
    Duplicate keys — same key appearing twice (ambiguous — we warn, not silently pick)


14. 
    BOM / encoding issues — UTF-8 BOM at start of response

What makes the repair pipeline different

Each pass targets one failure mode. The order matters — strip fences first, then normalize quotes, then fix commas, then close truncated structures. Each change is tracked.

The result isn't just a fixed JSON blob — it's a diff showing exactly what changed:

`

✅ Removed markdown code fence (`json ... `)

✅ Converted Python literal: True → true

✅ Closed truncated array (added missing `]`)

`

That explanation is half the value when you're debugging a production pipeline.

100% client-side

The repair runs entirely in your browser. Your production payloads never leave your machine. Open the Network tab — there's no request for the repair itself.

JSON Studio

Beyond repair, there's a full JSON toolbox:

• Format / minify


• Validate with error highlighting


• Tree view


• Diff two JSON blobs


• Convert: JSON ↔ CSV, YAML, XML, SQL


• JSONPath query


• JSON Schema generation


• TypeScript type generation


• JWT decode

We're launching on Product Hunt July 23

If you find it useful — or find broken JSON it doesn't handle — I'd love to hear about it.

Check it out on Product Hunt →

Launching Wednesday July 23 — would mean a lot if you upvoted on the day. And if you paste in broken JSON that beats the repair engine, I'll add a pass for it.