JSON Fixer
Pricing
from $0.50 / 1,000 json cleaneds
JSON Fixer
Repairs malformed JSON such as LLM output: strips Markdown fences, fixes curly quotes and trailing commas, and optionally validates the result against a JSON Schema.
Pricing
from $0.50 / 1,000 json cleaneds
Rating
0.0
(0)
Developer
林 吴
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
14 hours ago
Last modified
Categories
Security
Limited permissionsShare
Repair malformed JSON from LLMs, logs, and hand-edited config files. Paste raw text and get valid, parsed JSON back.
What it does
- Strips Markdown code fences (for example, json-fenced blocks) and surrounding prose
- Replaces curly quotes (“ ” ‘ ’) with straight quotes
- Removes trailing commas before
}and] - Removes UTF-8 BOM and whitespace noise
- Supports both JSON objects and top-level arrays
- Optionally validates the result against a JSON Schema and reports field-level errors
Input
| Field | Type | Required | Description |
|---|---|---|---|
raw_text | string | Yes | Raw text that may contain Markdown, curly quotes, trailing commas, or missing brackets |
expected_schema | string | No | JSON Schema (as a JSON string) used to validate the cleaned result |
Example input:
{"raw_text": "Here is the result:\n{\"name\": \"Lin\", \"tags\": [\"json\", \"cleanup\",], \"quote\": “hello”}","expected_schema": "{\"type\":\"object\",\"required\":[\"name\"]}"}
Output
One item is pushed to the default dataset:
{"success": true,"cleaned_json": {"name": "Lin","tags": ["json", "cleanup"],"quote": "hello"},"errors": []}
If parsing or schema validation fails, success is false, cleaned_json is {}, and errors contains the parser or validation messages.
Pricing
Pay per event. The $0.01 charge applies only when the JSON is successfully repaired and parsed. Failed attempts are not charged the repair fee, but standard start and dataset events still apply.
Use cases
- Cleaning structured output from LLM APIs before downstream processing
- Fixing JSON copied from chat, docs, or logs
- Validating scraped data against an expected schema
- Preparing malformed config snippets for automation pipelines
Notes
This Actor performs deterministic string repair; it does not call any external AI model, so results are fast and reproducible.