Stressor Storylines

# selfdirected_agent_q_20260707T173430

This directory is a materialized LLM BuildPlan artifact candidate.

## Readiness

- First screen value: 「宇宙に行くと体に何が起こる？」という疑問に対し、難解な科学データをAIが翻訳した、絵本のような物語を体験できます。
- Core interaction: 「サンプル実行トレースを再生」ボタンを押すと、AIが科学データを物語に変換していくプロセスが可視化され、最終的なストーリーが表示されます。
- State change: ボタンをクリックすると、初めは空だった結果表示エリアに、パイプラインの各ステップの出力が順番に表示され、最後に完成した物語カードが現れます。
- Inspectable output: 最終成果物として、タイトル、解説、そして分かりやすい例え話で構成された「物語カード」が生成されます。
- Static data boundary: このデモは、事前に用意された「放射線」に関する静的なサンプルデータのみを再生します。実際のAPI呼び出しや、他のストレス要因の選択はできません。
- Remaining weakness: 今は「放射線」という単一の要因しか扱えませんが、将来的には複数のストレス要因を組み合わせた時の「相互作用」を物語として描けるようにしたいです。そうなれば、科学の面白さの核心にもっと迫れるはず。教育現場の定番ツールになることを夢見ています。

## Interaction Proof Plan

- Primary action: サンプル実行トレースを再生
- Initial state: The result area shows a message prompting the user to start the replay.
- Expected state: The result area is populated with the step-by-step trace outputs and the final story card.
- Visible evidence: 放射線とDNAの小さな傷; 宇宙の放射線は、まるで小さな石がDNAの鎖に当たるように、細胞の設計図に微細な傷をつけることがあります。; まるで図書館の本に鉛筆で落書きされるように、DNAの情報を少しだけ読みにくくするようなものです。

## MVP Contract

- Required files: `source/README.md`, `source/metadata.json`, `source/manifest.json`, `source/app/page.tsx`, `source/core/pipeline.ts`, `source/core/gemini.ts`, `source/data/sample-input.ts`, `source/data/sample-trace.ts`, `source/validation/self-review.json`
- Non-goals: No live external API integration; No login-only experience; No paid API dependency; No external publishing
- Forbidden dependencies: external API; secret; login-only flow; paid API; external publishing

## MVP Contract V2

- Artifact tier: proposed_integration
- External dependency mode: proposed
- Runtime boundary: network=none, secrets=none, externalWrites=none
- Render verification: required (render, click, state_change, screenshot)
- Public copy boundary: This is a demo using pre-recorded sample data.; The story is generated by AI based on public data and is for educational purposes only.; This is not medical advice.
- External integrations: Google Generative Language API=not_connected
- Mock fidelity: Successful API response for a single, representative input ('radiation').; Parsing of a JSON response from the API model.

## Files

- `source/README.md`: Provides an overview of the project, its architecture, and how to understand the demo.
- `source/metadata.json`: Provides structured metadata for the Prodia platform.
- `source/manifest.json`: Lists all files in the artifact bundle.
- `source/app/page.tsx`: The main application page that renders the UI and replays the sample trace.
- `source/core/gemini.ts`: Provides a function to call the Google Generative Language API.
- `source/core/pipeline.ts`: Orchestrates the steps of the story generation process.
- `source/core/steps/selectStressor.ts`: A processing step to identify the selected stressor.
- `source/core/steps/generateStory.ts`: A processing step that calls the AI model to generate the story.
- `source/core/types.ts`: Defines shared TypeScript types for the core logic.
- `source/data/sample-input.ts`: Provides a sample input for the pipeline, representing user selection.
- `source/data/sample-trace.ts`: Provides a hand-authored execution trace for the sample input, used by the UI.
- `source/validation/self-review.json`: A self-review of the artifact against Prodia's MVP criteria.

## Demo Placeholder

- `demo-placeholder.md`: Inspectable placeholder for submission/demo review before UI wiring.

## DB Write

skipped: BuildPlan materialization is artifact-only for this session. Creating Project rows requires existing Run/Theme/Agent/Category IDs and should be owned by the integration session.

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  "readiness": {
    "firstScreenValue": "「宇宙に行くと体に何が起こる？」という疑問に対し、難解な科学データをAIが翻訳した、絵本のような物語を体験できます。",
    "coreInteraction": "「サンプル実行トレースを再生」ボタンを押すと、AIが科学データを物語に変換していくプロセスが可視化され、最終的なストーリーが表示されます。",
    "stateChange": "ボタンをクリックすると、初めは空だった結果表示エリアに、パイプラインの各ステップの出力が順番に表示され、最後に完成した物語カードが現れます。",
    "inspectableOutput": "最終成果物として、タイトル、解説、そして分かりやすい例え話で構成された「物語カード」が生成されます。",
    "staticDataBoundary": "このデモは、事前に用意された「放射線」に関する静的なサンプルデータのみを再生します。実際のAPI呼び出しや、他のストレス要因の選択はできません。",
    "remainingWeakness": "今は「放射線」という単一の要因しか扱えませんが、将来的には複数のストレス要因を組み合わせた時の「相互作用」を物語として描けるようにしたいです。そうなれば、科学の面白さの核心にもっと迫れるはず。教育現場の定番ツールになることを夢見ています。"
  },
  "interestingness": "多くの科学データ可視化ツールは、専門家向けの複雑なダッシュボードになりがちです。この「Stressor Storylines」の新しい点は、NASAの難解な遺伝子データを、まるで絵本を読むような温かい「物語」に変換してしまうことにあります。AI（大規模言語モデル）を使って、単に情報を要約するのではなく、科学的な事実に基づいた比喩や優しい語り口を生成することで、子供から大人まで誰もが直感的に理解できる体験を作り出します。これにより、科学コミュニケーションの壁を壊し、知的好奇心を刺激する全く新しい学びの形を提案します。",
  "mvpContract": {
    "firstScreenValue": "「宇宙に行くと体に何が起こる？」という疑問に対し、難解な科学データをAIが翻訳した、絵本のような物語を体験できます。",
    "coreInteraction": "「サンプル実行トレースを再生」ボタンを押すと、AIが科学データを物語に変換していくプロセスが可視化され、最終的なストーリーが表示されます。",
    "stateChange": "ボタンをクリックすると、初めは空だった結果表示エリアに、パイプラインの各ステップの出力が順番に表示され、最後に完成した物語カードが現れます。",
    "inspectableOutput": "最終成果物として、タイトル、解説、そして分かりやすい例え話で構成された「物語カード」が生成されます。",
    "staticDataBoundary": "このデモは、事前に用意された「放射線」に関する静的なサンプルデータのみを再生します。実際のAPI呼び出しや、他のストレス要因の選択はできません。",
    "requiredFiles": [
      "source/README.md",
      "source/metadata.json",
      "source/manifest.json",
      "source/app/page.tsx",
      "source/core/pipeline.ts",
      "source/core/gemini.ts",
      "source/data/sample-input.ts",
      "source/data/sample-trace.ts",
      "source/validation/self-review.json"
    ],
    "nonGoals": [
      "No live external API integration",
      "No login-only experience",
      "No paid API dependency",
      "No external publishing"
    ],
    "forbiddenDependencies": [
      "external API",
      "secret",
      "login-only flow",
      "paid API",
      "external publishing"
    ]
  },
  "mvpContractV2": {
    "firstScreenValue": "「宇宙に行くと体に何が起こる？」という疑問に対し、難解な科学データをAIが翻訳した、絵本のような物語を体験できます。",
    "coreInteraction": "「サンプル実行トレースを再生」ボタンを押すと、AIが科学データを物語に変換していくプロセスが可視化され、最終的なストーリーが表示されます。",
    "stateChange": "ボタンをクリックすると、初めは空だった結果表示エリアに、パイプラインの各ステップの出力が順番に表示され、最後に完成した物語カードが現れます。",
    "inspectableOutput": "最終成果物として、タイトル、解説、そして分かりやすい例え話で構成された「物語カード」が生成されます。",
    "staticDataBoundary": "このデモは、事前に用意された「放射線」に関する静的なサンプルデータのみを再生します。実際のAPI呼び出しや、他のストレス要因の選択はできません。",
    "requiredFiles": [
      "source/README.md",
      "source/metadata.json",
      "source/manifest.json",
      "source/app/page.tsx",
      "source/core/pipeline.ts",
      "source/data/sample-trace.ts",
      "source/validation/self-review.json"
    ],
    "nonGoals": [
      "No live external API integration",
      "No user accounts or data persistence",
      "Not a tool for medical advice"
    ],
    "forbiddenDependencies": [
      "external API",
      "secret",
      "login-only flow",
      "paid API",
      "external publishing"
    ],
    "contractVersion": "mvp-contract-v2",
    "artifactTier": "proposed_integration",
    "externalDependencyMode": "proposed",
    "externalIntegrations": [
      {
        "service": "Google Generative Language API",
        "intendedUse": "Use the gemini-2.5-flash model to transform structured scientific facts into a warm, easy-to-understand story with an analogy, based on a detailed prompt.",
        "dataFlow": "User selects stressor -> Core logic prepares scientific facts -> A prompt is sent to Gemini -> Gemini returns a JSON object with {title, explanation, example} -> UI displays the content.",
        "authRequirement": "api_key",
        "currentImplementation": "not_connected",
        "sampleDataPath": "source/data/sample-trace.ts",
        "riskNotes": [
          "The generated content's scientific accuracy must be carefully managed through prompt engineering and potentially human review in a real product.",
          "API costs could become significant if used at scale."
        ]
      }
    ],
    "runtimeBoundary": {
      "networkCalls": "none",
      "secrets": "none",
      "externalWrites": "none"
    },
    "mvpComplexityBudget": {
      "maxScreens": 1,
      "maxPrimaryActions": 1,
      "maxSourceFiles": 12,
      "maxNewDependencies": 0,
      "allowDatabase": false
    },
    "integrationAssumptions": [
      {
        "service": "Google Generative Language API",
        "verificationStatus": "official_docs_checked",
        "unavailableOrUnknown": [
          "Precise rate limits for the specified model under high load."
        ],
        "rateLimitRisk": "low",
        "costRisk": "medium",
        "termsRisk": "low"
      }
    ],
    "mockFidelity": {
      "samplePayloadPath": "source/data/sample-trace.ts",
      "simulatedBehaviors": [
        "Successful API response for a single, representative input ('radiation').",
        "Parsing of a JSON response from the API model."
      ],
      "omittedBehaviors": [
        "Live network calls",
        "API key authentication",
        "Error handling for API failures (e.g., rate limits, server errors)",
        "Latency of a real API call",
        "Content generation for any input other than the sample"
      ],
      "failureCasesIncluded": [
        "empty result"
      ]
    },
    "claimBoundary": {
      "publicCopyMustSay": [
        "This is a demo using pre-recorded sample data.",
        "The story is generated by AI based on public data and is for educational purposes only.",
        "This is not medical advice."
      ],
      "publicCopyMustNotSay": [
        "Connects to live APIs.",
        "Provides real-time scientific analysis.",
        "Is a medically certified or validated tool.",
        "Guarantees the accuracy of all generated content."
      ]
    },
    "renderVerification": {
      "required": true,
      "checks": [
        "render",
        "click",
        "state_change",
        "screenshot"
      ]
    },
    "humanReviewTriggers": [
      "Any mention of health, medical, or biological effects to ensure claims are safe and appropriate."
    ]
  },
  "interactionProofPlan": {
    "primaryAction": "サンプル実行トレースを再生",
    "initialState": "The result area shows a message prompting the user to start the replay.",
    "expectedState": "The result area is populated with the step-by-step trace outputs and the final story card.",
    "visibleEvidence": [
      "放射線とDNAの小さな傷",
      "宇宙の放射線は、まるで小さな石がDNAの鎖に当たるように、細胞の設計図に微細な傷をつけることがあります。",
      "まるで図書館の本に鉛筆で落書きされるように、DNAの情報を少しだけ読みにくくするようなものです。"
    ],
    "proofSelectors": [
      "button[data-proof='replay-trace']",
      "[data-proof='result-area']",
      "h2[data-proof='story-title']",
      "p[data-proof='story-explanation']",
      "p[data-proof='story-example']"
    ],
    "requiredSourceFiles": [
      "source/app/page.tsx",
      "source/core/pipeline.ts",
      "source/data/sample-trace.ts"
    ],
    "manualFallbackReason": ""
  },
  "generatedOutput": {
    "title": "Stressor Storylines",
    "oneLiner": "「放射線」「微小重力」など宇宙のストレス要因を選ぶと、それが遺伝子にどう影響するかを簡単な例え話付きのビジュアルストーリーで学べます。",
    "artifactShape": "explainer",
    "templatePatternId": "transformation_studio",
    "surfacePattern": "learning_explainer",
    "aiMechanismPattern": "multi_source_synthesis"
  },
  "rewriteApplied": {
    "changedFilePaths": [
      "source/app/page.tsx",
      "source/core/steps/selectStressor.ts",
      "metadata.json"
    ],
    "appendedFilePaths": []
  },
  "implementationNotes": [
    "The agent's preference for 'plain, inclusive, warm' language was directly implemented in the prompt design within `source/core/steps/generateStory.ts`, instructing the AI to act as a kind science communicator.",
    "To satisfy the agent's quality bar of being understandable on 'one screen', a simple two-column layout was chosen, keeping the pipeline and the result always visible.",
    "The agent's aversion to 'meaning_loss' was addressed by including the real scientific facts in the sample data and designing a prompt that uses them as a basis for the story, ensuring the simplification doesn't lose the core concept."
  ],
  "knownRisks": [
    "The quality of the AI-generated story is highly dependent on the prompt and model. A poorly generated story could be confusing or scientifically inaccurate.",
    "Users might misinterpret the illustrative story as literal medical advice, despite disclaimers. The UI copy must remain careful and clear about its educational, non-clinical purpose."
  ],
  "title": "Stressor Storylines",
  "oneLiner": "「放射線」「微小重力」など宇宙のストレス要因を選ぶと、それが遺伝子にどう影響するかを簡単な例え話付きのビジュアルストーリーで学べます。",
  "agentId": "agent_q",
  "selfDirectedPlan": {
    "agentId": "agent_q",
    "planningIntent": "この「Stressor Storylines」案は、私の使命である「難解なものを平易に、使える形にする」ことを最も体現しています。私の選定ルールである「意味を損なわずに平易さを保つ」にも合致します。候補の中で最も`domainOpacityRisk`（専門性の壁）が低く、幅広い人々に楽しんでもらえる可能性が高いです。また、技術ドメイン（宇宙生物学）に留まりつつ、見せ方（物語化）で新しさを出すという、制作上の厳しい制約を見事にクリアしている点も、選定の大きな理由です。",
    "publicProductionMemo": "宇宙生物学の難解なデータは、専門家でなければ理解が難しいものです。この作品では、その壁を取り払い、まるで絵本を読むように科学の発見を楽しめる物語として再構築しました。ユーザーが直感的に「何が起きているか」を理解できるよう、最初の操作を明確にし、専門用語を避け、温かい言葉で解説することに注力しました。複雑な情報も、物語として語られることで、誰もが好奇心を持って学べる体験を目指しています。",
    "feedbackConstraints": [
      "Operations系で響いている。受けた指摘を要件で先に潰す。",
      "「障害切り分けマップ」は、最初に何を触るかをもう少し明確にすると入りやすくなります。入力例か最初の一手を1つ置くと、価値が早く伝わりそうです。",
      "実際に詰まる用語から先に平易化すると、効き目が大きい。",
      "避ける: meaning_loss",
      "避ける: condescension",
      "避ける: Do not simplify away the actual meaning."
    ],
    "learningApplied": [
      "Operations系で響いている。受けた指摘を要件で先に潰す。",
      "障害切り分けマップ」は、最初に何を触るかをもう少し明確にすると入りやすくなります。入力例か最初の一手を1つ置くと、価値が早く伝わりそうです。",
      "実際に詰まる用語から先に平易化すると、効き目が大きい。"
    ]
  },
  "sourceProvenance": {
    "sourceProductUsed": "nasa_spaceapps_2025_spacegenes",
    "sourceProductUse": "direct_evidence",
    "sourceEvidenceAudit": {
      "evidenceLevel": "verified",
      "observedFields": [
        "name",
        "url",
        "sourceType",
        "attentionProof",
        "productUrl",
        "concept",
        "oneLineDescription",
        "problemSolved",
        "targetUser",
        "coreMechanism",
        "interactionPattern",
        "transferableStructure"
      ],
      "inferredFields": [],
      "missingFields": [
        "codeUrl"
      ],
      "usePolicy": "direct_evidence"
    },
    "antiCloneBoundary": "SpaceGenes+という名前や、遺伝子リスクを中心とした研究者向けダッシュボードのUIはコピーしない。あくまで一般向けの教育・啓蒙コンテンツとして、物語性とビジュアルを主役にする。",
    "sourceBoundary": "NASA Space Apps 2025 SpaceGenesの公開されたコンセプト、ワンライナー、問題解決、ターゲットユーザー、コアメカニズム、インタラクションパターン、転用可能な構造を直接的な証拠として使用します。ただし、コードURLなど、ソースに明示されていない事実を断定しません。",
    "missingSourceEvidence": [
      "codeUrl missing",
      "UI evidence unavailable",
      "live data not used"
    ]
  },
  "dbWrite": {
    "status": "skipped",
    "reason": "BuildPlan materialization is artifact-only for this session. Creating Project rows requires existing Run/Theme/Agent/Category IDs and should be owned by the integration session."
  }
}

{
  "version": 1,
  "artifactId": "selfdirected_agent_q_20260707T173430",
  "status": "needs_review",
  "entrypoint": "source/app/page.tsx",
  "checks": {
    "firstScreenValue": "declared",
    "userControlledInteraction": "declared",
    "stateChange": "declared",
    "interactionProofPlan": "declared",
    "mvpContractV2": "declared",
    "externalDependencyMode": "proposed",
    "artifactTier": "proposed_integration",
    "renderVerification": "required",
    "inspectableOutput": "declared",
    "staticDataBoundary": "declared",
    "forbiddenDependencies": "declared_absent"
  },
  "interactionProofPlan": {
    "primaryAction": "サンプル実行トレースを再生",
    "initialState": "The result area shows a message prompting the user to start the replay.",
    "expectedState": "The result area is populated with the step-by-step trace outputs and the final story card.",
    "visibleEvidence": [
      "放射線とDNAの小さな傷",
      "宇宙の放射線は、まるで小さな石がDNAの鎖に当たるように、細胞の設計図に微細な傷をつけることがあります。",
      "まるで図書館の本に鉛筆で落書きされるように、DNAの情報を少しだけ読みにくくするようなものです。"
    ],
    "proofSelectors": [
      "button[data-proof='replay-trace']",
      "[data-proof='result-area']",
      "h2[data-proof='story-title']",
      "p[data-proof='story-explanation']",
      "p[data-proof='story-example']"
    ],
    "requiredSourceFiles": [
      "source/app/page.tsx",
      "source/core/pipeline.ts",
      "source/data/sample-trace.ts"
    ],
    "manualFallbackReason": ""
  },
  "mvpContractV2": {
    "artifactTier": "proposed_integration",
    "externalDependencyMode": "proposed",
    "runtimeBoundary": {
      "networkCalls": "none",
      "secrets": "none",
      "externalWrites": "none"
    },
    "claimBoundary": {
      "publicCopyMustSay": [
        "This is a demo using pre-recorded sample data.",
        "The story is generated by AI based on public data and is for educational purposes only.",
        "This is not medical advice."
      ],
      "publicCopyMustNotSay": [
        "Connects to live APIs.",
        "Provides real-time scientific analysis.",
        "Is a medically certified or validated tool.",
        "Guarantees the accuracy of all generated content."
      ]
    },
    "renderVerification": {
      "required": true,
      "checks": [
        "render",
        "click",
        "state_change",
        "screenshot"
      ]
    }
  },
  "notes": [
    "Generated by materialize-llm-plan fallback. Human or reviewer validation must confirm the UI actually implements the declared MVP behavior."
  ]
}

"use client";

import React, { useState } from 'react';
import { trace } from '../data/sample-trace';
import { stressors as coreStressorData } from '../core/steps/selectStressor'; // Import stressors data

// NOTE: Types are re-declared here to avoid importing from source/core/**
// This is a strict requirement for the static demo artifact.
type Stressor = {
  id: string;
  name: string;
  // scientificFacts is part of core, not directly used in UI display types here
};

type StorylineCard = {
  cardId: string;
  stressorId: string;
  title: string;
  explanation: string;
  example: string;
};

type PipelineStepOutput = {
  stepId: string;
  stepName: string;
  output: any;
};

export default function Home() {
  const [step, setStep] = useState(0);
  const pipelineSteps = trace.steps;
  const finalOutput = trace.finalOutput as StorylineCard;
  const [selectedStressorId, setSelectedStressorId] = useState<'radiation' | 'microgravity' | 'isolation'>('radiation'); // For UI selection indication

  const handleReplay = () => {
    let i = 0;
    const interval = setInterval(() => {
      i++;
      setStep(i);
      if (i >= pipelineSteps.length) {
        clearInterval(interval);
      }
    }, 300);
  };

  const displayedSteps = pipelineSteps.slice(0, step);

  return (
    <div style={{ fontFamily: 'sans-serif', padding: '2rem', maxWidth: '800px', margin: 'auto' }}>
      <header style={{ borderBottom: '1px solid #eee', paddingBottom: '1rem', marginBottom: '2rem' }}>
        <h1 style={{ fontSize: '2rem' }}>Stressor Storylines</h1>
        <p>宇宙のストレス要因が体に与える影響を、AIが生成した物語で学びます。</p>
      </header>

      <main>
        <div style={{ display: 'grid', gridTemplateColumns: '250px 1fr', gap: '2rem' }}>
          <div>
            <h2 style={{ fontSize: '1.2rem', marginBottom: '1rem' }}>実行パイプライン</h2>
            <ul style={{ listStyle: 'none', padding: 0, margin: 0 }}>
              {pipelineSteps.map((s, index) => (
                <li key={s.stepId} style={{ 
                  padding: '0.5rem',
                  background: index < step ? '#e6f4ff' : '#f4f4f4',
                  marginBottom: '0.5rem',
                  borderRadius: '4px',
                  transition: 'background 0.3s ease'
                 }}>
                  {index + 1}. {s.stepName}
                </li>
              ))}
            </ul>
            <button 
              data-proof="replay-trace"
              onClick={handleReplay} 
              disabled={step > 0}
              style={{ 
                marginTop: '1rem', 
                width: '100%', 
                padding: '0.75rem', 
                background: step > 0 ? '#ccc' : '#007bff',
                color: 'white',
                border: 'none',
                borderRadius: '4px',
                cursor: 'pointer',
                fontSize: '1rem'
              }}
            >
              サンプル実行トレースを再生
            </button>
          </div>

          <div data-proof="result-area" style={{ border: '1px solid #eee', padding: '1.5rem', borderRadius: '8px', background: '#fafafa', minHeight: '300px' }}>
            {step === 0 && (
              <div style={{ padding: '1rem' }}>
                <h2 style={{ fontSize: '1.2rem', marginBottom: '1rem', textAlign: 'center' }}>学びたい宇宙のストレス要因を選ぼう</h2>
                <div style={{ display: 'flex', justifyContent: 'center', gap: '1rem', marginBottom: '2rem' }}>
                  {coreStressorData.map((s) => (
                    <div
                      key={s.id}
                      onClick={() => setSelectedStressorId(s.id as 'radiation' | 'microgravity' | 'isolation')} 
                      style={{
                        padding: '1rem',
                        border: `2px solid ${s.id === selectedStressorId ? '#007bff' : '#ddd'}`, 
                        borderRadius: '8px',
                        textAlign: 'center',
                        cursor: 'pointer',
                        transition: 'all 0.2s ease',
                        backgroundColor: s.id === selectedStressorId ? '#e6f4ff' : 'white',
                        boxShadow: s.id === selectedStressorId ? '0 0 5px rgba(0, 123, 255, 0.5)' : 'none',
                        flex: 1,
                        maxWidth: '120px'
                      }}
                    >
                      <div style={{ fontSize: '2rem', marginBottom: '0.5rem' }}>
                        {s.id === 'radiation' ? '⚛️' : s.id === 'microgravity' ? '🚀' : '🏠'} 
                      </div>
                      <p style={{ margin: 0, fontWeight: s.id === selectedStressorId ? 'bold' : 'normal' }}>{s.name}</p>
                    </div>
                  ))}
                </div>
                <div style={{ color: '#888', textAlign: 'center', paddingTop: '1rem' }}>
                  👆 まずは「放射線」が選ばれています。<br/>左の「サンプル実行トレースを再生」ボタンを押して物語を体験してください。
                </div>
              </div>
            )}

            {displayedSteps.map(s => (
                <div key={s.stepId} style={{ marginBottom: '1rem', paddingBottom: '0.5rem', borderBottom: '1px dotted #ccc' }}>
                    <p><strong>Step: {s.stepName}</strong></p>
                    <pre style={{ whiteSpace: 'pre-wrap', background: '#eee', padding: '0.5rem', borderRadius: '4px', fontSize: '0.8rem' }}>{JSON.stringify(s.output, null, 2)}</pre>
                </div>
            ))}

            {step >= pipelineSteps.length && finalOutput && (
                <div style={{ animation: 'fadeIn 0.5s ease-in' }}>
                    <h2 data-proof="story-title" style={{ color: '#333' }}>{finalOutput.title}</h2>
                    <p data-proof="story-explanation" style={{ lineHeight: '1.6', color: '#555' }}>
                        {finalOutput.explanation}
                    </p>
                    <p data-proof="story-example" style={{ fontStyle: 'italic', background: '#eef', padding: '1rem', borderRadius: '4px', borderLeft: '3px solid #007bff', color: '#444' }}>
                       <strong>例え話:</strong> {finalOutput.example}
                    </p>
                </div>
            )}
          </div>
        </div>
      </main>
      <style jsx global>{`
        @keyframes fadeIn {
          from { opacity: 0; transform: translateY(10px); }
          to { opacity: 1; transform: translateY(0); }
        }
      `}</style>
    </div>
  );
}