Synthex Forge MCP Eval Judge

x402

Synthex Forge MCP Eval Judge is a paid API for AI agents from x402.synthexforge.com, paid per call via x402, $0.15/call, status unknown (last checked 2026-10-23).

Grades a candidate LLM response against a multi-criterion rubric, returning a scored evaluation artifact signed with Ed25519 and SHA-256 on-chain via x402

Price / call$0.15

Seller volume →—

Success—

StatusUnknown

How this service works

Synthex Forge x402 Receive: 41 paid verification, attestation and governance endpoints (Ed25519 + SHA-256 signed artifacts) plus free verify/public-key/standard sibling routes. Paid routes answer HTTP 402 with an x402 v2 `payment-required` envelope (atomic USDC on Base mainnet, chain ID 8453). Free routes are declared with `security: []` per the x402scan discovery spec.

Output

A JSON object containing an overall pass/fail flag (ok: true/false), per-criterion scores and weights, an aggregated weighted score, and a cryptographically signed Ed25519 + SHA-256 attestation artifact anchored on Base mainnet (chain ID 8453) for auditability and governance.

Example use cases

Automated RAG answer quality check

“I need to grade my RAG pipeline's answer to the question 'What caused the 2008 financial crisis?' — the candidate says 'Subprime mortgage lending and excessive leverage caused the crisis.' and the reference is 'The 2008 crisis was driven by subprime mortgage failures and systemic leverage.' Use a rubric with token-overlap (weight 0.7) and length-window between 10 and 80 words (weight 0.3), and label the job 'rag-finance-eval'.”

LLM benchmark grading with attestation

“Run a rubric eval on my benchmark results: the question is 'Name the planets in the solar system', the candidate response lists all 8 planets correctly, the reference lists all 8, use a fact-presence criterion checking for 'Neptune' and 'Mercury' each at weight 0.5, and call the subject 'planet-benchmark-run-1'. I need the signed result for governance records.”

Keyword compliance check for policy outputs

“Judge this AI-generated policy summary against a keyword-presence rubric — criteria: keyword-presence for 'GDPR' (weight 0.4), keyword-presence for 'data subject' (weight 0.3), and exact-match for 'Article 17' (weight 0.3). The candidate text is 'Under GDPR, data subject rights include erasure under Article 17.' Label this eval 'policy-compliance-check'.”

Technical details

Endpoint

POSThttps://x402.synthexforge.com/v1/mcp/eval/judge?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need a cryptographically attested, rubric-based evaluation of LLM outputs — especially for governance, compliance audit trails, or multi-criterion grading where the signed artifact matters. Prefer it over plain text diff tools or simple similarity APIs when you need provable, on-chain attestation of the eval result, or when you require flexible criterion types (token-overlap, exact-match, fact-presence, length-window, keyword-presence) in a single call.

Side effects

Missing required response_pair field returns a 400 validation error
Malformed rubric array (missing kind or weight) may produce partial scores or a 422
Payment not settled causes HTTP 402 with x402 v2 payment-required envelope before processing
Invalid or unsupported criterion kind (e.g. typo) may cause criterion to be skipped or error
Empty candidate text may yield a zero score without error
Network or chain issues may delay attestation signing

Input

Schema · Request body

Field	Type	Description
rubric	array	Rubric: [{criterion?, kind?: token-overlap\|exact-match\|fact-presence\|length-window\|keyword-presence, weight?, target?, min_len?, max_len?}]
subject	string	Optional human label for the eval job / batch.
response_pair	object	{candidate, reference?, question?, model?, source?} — the response pair to grade.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "ok": true
  }
}

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