{"uid":"cap_2aB9D98huuEhtSWhsCN6u","slug":"agent402-judge-llm-as-judge-evaluation-endpoint-6a058861","name":"Agent402 Judge – LLM-as-Judge Evaluation Endpoint","description":"Ask a typed question about any content and get an answer your code can branch on, not prose to parse. Send state (the content, a string or object) and questions (your own ids mapped to question objects); get back answers keyed by those ids. Three question types: choice (pick one of your named options: returns choice, probabilities per option and confidence), score (a position on levels you describe, lowest first: returns score as a fractional level index, probabilities per level index.","url":"https://agent402.tools/v1/judge?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"model":{"enum":["gpt-6-luna","microsoft-decision-1","jev-latest","jev-preview"],"type":"string","description":"Which model answers first; the others are fallbacks. microsoft-decision-1 is Microsoft Decision-1, a model-backed judgment, not deterministic. Defaults to jev-latest."},"state":{"type":["string","object","array"],"description":"The content to judge. Up to 8000 characters."},"questions":{"type":"object","description":"Your own ids mapped to question objects. Each has type (choice/score/noul), instructions, and criteria for choice/score."}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.001","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.001/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.001","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_fQMcvp2AcXhTX_n_Hgfnx","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.001","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Evaluates arbitrary content against custom question sets using LLM-as-a-judge, returning structured scores, choices, or classifications per question.","exampleAgentPrompt":"Judge this AI-generated summary against my two questions: first, 'Is the summary factually accurate?' as a score from 0–10 with criteria focusing on factual grounding, and second, 'Is the tone professional?' as a choice between yes/no — use jev-latest and here's the content: 'The Eiffel Tower was built in 1889 and stands 330 metres tall.'","exampleUseCases":[{"title":"Automated agent output quality check","prompt":"Score this agent response on three criteria — relevance, completeness, and clarity — each on a 0–10 scale, using jev-latest. Here's the response: 'To reset your password, go to Settings > Security > Reset, then check your email for the link.'"},{"title":"Content policy classification","prompt":"Judge this user-submitted comment and tell me whether it violates any of these three policies — hate speech, spam, or misinformation — using jev-latest. The comment is: 'Buy cheap meds now!! Doctors don't want you to know this cure!'"},{"title":"RAG answer faithfulness evaluation","prompt":"Use jev-latest to evaluate how faithful this generated answer is to the provided context: question is 'What year did the Apollo 11 moon landing occur?', the answer given is '1969', and my context document says 'Apollo 11 landed on the moon on July 20, 1969.' Score faithfulness from 0–10."}],"resultDescription":"A structured JSON object containing per-question judgments keyed by the caller's own question IDs — each entry includes the question type result (a numeric score, a selected choice option, or a noul result), enabling automated downstream branching or reporting.","failureModes":["state field exceeds 8000 characters — request rejected or truncated","invalid model enum value — returns validation error","malformed questions object (missing type, instructions, or criteria) — error response","payment not settled (x402 / MPP flow incomplete) — 402 or auth failure","ambiguous question types causing low-confidence or inconsistent judgments"],"whenToPreferThis":"Choose this endpoint when you need structured, multi-dimensional LLM evaluation of arbitrary content without managing an API key or subscription — ideal for automated eval pipelines, agent output grading, or content moderation where pay-per-call pricing is more cost-effective than a standing API plan. Prefer it over rolling your own judge prompt when you want consistent, versioned judge models (jev-latest/jev-preview) with a schema-enforced question format.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-11T21:53:03.824Z","isFirstParty":false,"canonicalSlug":"agent402-judge-llm-as-judge-evaluation-endpoint-6a058861"}