LLM Output Validation

Parse AI output as JSON, repair common syntax mistakes and check supported schema rules. Returns parsed output and validation errors.

Pay by wallet (x402) llm-output-validate

Example

Example answer

{
  "valid": false,
  "errors": [],
  "auto_fixed": false,
  "error_count": 1,
  "parse_error": "Unexpected token 'e', \"test\" is not valid JSON",
  "parsed_output": null
}

Inputs

Field	Type	Required	What it is
`llm_output`	string	Yes	Raw LLM output string
`strict_mode`	boolean	No	—
`expected_schema`	object	No	JSON Schema to validate against

Output fields

How reliably each field appears in a successful answer.

Field	Type	Appears
`valid`	boolean	Always (present in every successful answer)
`errors`	array	Always (present in every successful answer)
`auto_fixed`	boolean	Always (present in every successful answer)
`parsed_output`	any	Always (present in every successful answer)
`auto_fixed_output`	string	Usually (present for most inputs)

How to call it

The same tool through each route. MCP clients reach it through Strale’s server at https://api.strale.io/mcp; the call below is what the agent sends.

# Needs an API key. max_price_cents caps what this call may cost.
curl -X POST https://api.strale.io/v1/do \
  -H "Authorization: Bearer $STRALE_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "capability_slug": "llm-output-validate",
    "inputs": {
      "llm_output": "{\"name\": \"Alice\", \"age\": 30, \"active\": true}"
    },
    "max_price_cents": 5
  }'

{
  "tool": "strale_execute",
  "arguments": {
    "slug": "llm-output-validate",
    "inputs": {
      "llm_output": "{\"name\": \"Alice\", \"age\": 30, \"active\": true}"
    },
    "max_price_cents": 5
  }
}

import { Strale } from "straleio";

const strale = new Strale({ apiKey: process.env.STRALE_API_KEY! });
const result = await strale.do({
  capability_slug: "llm-output-validate",
  inputs: {
    "llm_output": "{\"name\": \"Alice\", \"age\": 30, \"active\": true}"
  },
  max_price_cents: 5,
});

import os
from straleio import Strale, DoRequest

strale = Strale(api_key=os.environ["STRALE_API_KEY"])
result = strale.do(DoRequest(
    capability_slug="llm-output-validate",
    inputs={
        "llm_output": "{\"name\": \"Alice\", \"age\": 30, \"active\": true}",
    },
    max_price_cents=5,
))

# No account. The first request answers 402 with the price in USDC;
# an x402 client pays it from your wallet and repeats the request.
curl -i 'https://api.strale.io/x402/v2/llm-output-validate?llm_output=%7B%22name%22%3A+%22Alice%22%2C+%22age%22%3A+30%2C+%22active%22%3A+true%7D'

Limitations

Factual correctness is not checked
Checks output structure and format only. It does not verify that the content is factually correct.
What to do instead: Combine with domain-specific validation (e.g., schema checks, reference lookups) for factual verification

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