reaction check derived

{
  "input": {
    "body": {
      "content": "Stress-test launch copy before you publish. LaunchCheck reviews messaging through eight audience lenses, flags positioning friction and unsupported claims, and returns concrete changes plus a fact-preserving rewrite.",
      "constraints": [
        "Do not invent metrics"
      ],
      "contentType": "landing-page",
      "desiredAction": "Run a paid reaction check.",
      "productContext": "An x402-paid API for structured pre-launch copy review.",
      "targetAudience": "Founders, product teams, and AI agents."
    },
    "type": "http",
    "method": "POST",
    "bodyType": "json"
  },
  "output": {
    "type": "json",
    "example": {
      "meta": {
        "model": "example-model",
        "cached": false,
        "engine": "openai-compatible",
        "generatedAt": "2026-07-26T12:00:00.000Z"
      },
      "report": {
        "score": 74,
        "verdict": "revise",
        "topRisks": [
          {
            "fix": "State the specific pre-launch decision the review helps make.",
            "title": "Differentiation is vague",
            "evidence": "The copy lists checks without explaining why they beat a generic critique.",
            "severity": "medium",
            "whyItMatters": "Readers may not see why the specialized review is worth using."
          }
        ],
        "inputIntegrity": {
          "status": "clean",
          "evidence": []
        },
        "likelyQuestions": [
          "Why use this instead of a generic model?"
        ],
        "requiredChanges": [
          "Clarify the specialized value."
        ],
        "executiveSummary": "Clear value, but the differentiation needs stronger evidence.",
        "suggestedRewrite": "Stress-test launch copy before you publish with eight audience lenses, evidence checks, concrete fixes, and a fact-preserving rewrite.",
        "audienceReactions": [
          {
            "lens": "Skeptical technical buyer",
            "friction": "Differentiation is unclear.",
            "reaction": "mixed",
            "confidence": 0.82,
            "likelyThought": "Useful, but why not use a generic model?"
          },
          {
            "lens": "Busy nontechnical decision-maker",
            "friction": "Differentiation is unclear.",
            "reaction": "mixed",
            "confidence": 0.82,
            "likelyThought": "Useful, but why not use a generic model?"
          },
          {
            "lens": "Price-sensitive solo user",
            "friction": "Differentiation is unclear.",
            "reaction": "mixed",
            "confidence": 0.82,
            "likelyThought": "Useful, but why not use a generic model?"
          },
          {
            "lens": "Privacy and security-conscious evaluator",
            "friction": "Differentiation is unclear.",
            "reaction": "mixed",
            "confidence": 0.82,
            "likelyThought": "Useful, but why not use a generic model?"
          },
          {
            "lens": "Existing customer scanning for regressions",
            "friction": "Differentiation is unclear.",
            "reaction": "mixed",
            "confidence": 0.82,
            "likelyThought": "Useful, but why not use a generic model?"
          },
          {
            "lens": "First-time visitor with low context",
            "friction": "Differentiation is unclear.",
            "reaction": "mixed",
            "confidence": 0.82,
            "likelyThought": "Useful, but why not use a generic model?"
          },
          {
            "lens": "Enthusiastic early adopter",
            "friction": "Differentiation is unclear.",
            "reaction": "mixed",
            "confidence": 0.82,
            "likelyThought": "Useful, but why not use a generic model?"
          },
          {
            "lens": "Support-minded operator anticipating questions",
            "friction": "Differentiation is unclear.",
            "reaction": "mixed",
            "confidence": 0.82,
            "likelyThought": "Useful, but why not use a generic model?"
          }
        ],
        "strongestElements": [
          "The pre-launch use case is clear."
        ],
        "optionalImprovements": [],
        "claimsNeedingEvidence": []
      },
      "requestId": "2e847847-52da-46c6-b627-f95dbd66919f"
    }
  }
}