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NetIntel JSON Repair
x402
NetIntel JSON Repair is a paid API for AI agents from netintel.dev, paid per call via x402, $0.02/call, status unknown (last checked 2026-10-11).
Repairs malformed JSON strings into valid JSON using a deterministic tokenizer with optional LLM fallback, schema validation, and type coercion
Price / call$0.02
Success—
StatusUnknown
How this service works
Repair malformed JSON into valid JSON — fixes code fences, trailing commas, single quotes, unquoted keys, bad escapes, duplicate keys, truncation, and JSON buried in prose. A deterministic tokenizer runs first (no LLM cost), with an optional Haiku fallback, plus optional schema validation and type coercion — so agents can rescue broken model output or dirty data in one call.
Output
Returns a JSON object with: repaired (the fixed JSON as an object/array/null), repair_succeeded (boolean), was_valid (boolean indicating input was already valid), method (how repair was achieved: deterministic or LLM), confidence (0-1 score), grade (letter grade of repair quality), changes (list of modifications made), warnings (non-fatal issues), schema_valid (boolean or null if no schema supplied), and validation_errors (list of schema violations if any).
Example use cases
Rescue broken LLM output
“The model returned this JSON with markdown code fences and trailing commas and it's breaking my parser — can you repair it into clean valid JSON? Here's the raw output: ```json
{"name": "Alice", "score": 95,}
```”
Validate and coerce dirty API data
“I'm getting JSON from a third-party API where numbers come in as strings and some keys are unquoted — can you fix it and coerce the values to the right types based on this schema: {"id": "integer", "price": "number", "active": "boolean"}?”
Extract JSON buried in prose
“This model response has a JSON object buried somewhere in the middle of a long paragraph of text — can you pull out the JSON and return it as a clean, valid object without any surrounding prose?”
Technical details
Endpoint
POSThttps://netintel.dev/json/repair?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to rescue broken JSON from LLM outputs, dirty data pipelines, or third-party APIs — especially when you want deterministic repair (no LLM cost) with an optional LLM fallback for trickier cases, plus built-in schema validation and type coercion in one call. Prefer it over hand-rolled parsers or generic LLM prompting when you need auditability (changes list, grade, confidence) and pay-per-call pricing without managing API keys.
Side effects
- Input too severely malformed for deterministic tokenizer and allow_llm is false — returns repair_succeeded: false with a 200
- Input exceeds 100KB limit — returns an error
- Schema validation fails after successful repair — repair_succeeded is true but schema_valid is false with validation_errors populated
- LLM fallback unavailable or fails — falls back to deterministic result or returns repair_succeeded: false
- Input is valid JSON already — returns was_valid: true with no changes
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"grade": "A",
"score": 100,
"method": "deterministic",
"changes": [
"removed markdown code fences",
"converted 3 single-quoted strings to double-quoted",
"removed 2 trailing commas"
],
"findings": [],
"repaired": {
"name": "acme",
"ports": [
80,
443
]
},
"warnings": [],
"was_valid": false,
"confidence": 1,
"schema_valid": null,
"repair_succeeded": true,
"validation_errors": []
}
}Tags
x402
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