ScoreSense

# selfdirected_agent_q_20260708T043627

This directory is a materialized LLM BuildPlan artifact candidate.

## Readiness

- First screen value: ユーザーは自分の楽器演奏（を模したサンプルデータ）が、お手本と比べてどこがどうズレているのかを、専門知識なしに一目で理解できます。
- Core interaction: 「サンプル実行トレースを再生」ボタンを一度クリックするだけです。
- State change: クリック後、静的だった楽譜の音符が、正誤に応じてリアルタイムに色を変え、具体的なフィードバックが表示されます。
- Inspectable output: 色分けされた楽譜、各音符の具体的なズレの理由、そしてAIによる総評コメント。
- Static data boundary: 表示されるすべての演奏評価は、`source/data/sample-trace.ts`に記録された静的なサンプルデータに基づくシミュレーションです。
- Remaining weakness: 現状は単音のメロディのみ対応ですが、将来的には和音や複数の楽器パートを同時に分析できるように拡張し、バンドやオーケストラの練習にも使えるツールへと成長させたいです。

## Interaction Proof Plan

- Primary action: サンプル実行トレースを再生
- Initial state: Score is displayed with all notes in the default color. The feedback area is empty.
- Expected state: After replaying the trace, some score notes are colored green, orange, or red, and specific feedback text ('音程が高い', 'リズムが速い') is visible. The final AI summary is also displayed.
- Visible evidence: きらきら星; 音程が高い; リズムが速い; 素晴らしい演奏です！

## 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 real-time analysis and AI feedback are simulated.; A connection to live APIs is required for a functional product.
- External integrations: Google Generative Language API (Gemini)=not_connected, Real-time Audio Analysis API=not_connected
- Mock fidelity: A sequence of played notes, including correct notes, a pitch error, and a rhythm error.; A final, human-like summary generated by an AI.

## Files

- `source/README.md`: Explains the product concept, architecture, and usage for other developers.
- `source/metadata.json`: Provides structured metadata for the Prodia platform.
- `source/manifest.json`: Lists all files in the artifact bundle.
- `source/validation/self-review.json`: Provides a self-assessment of the artifact against Prodia's MVP criteria.
- `source/app/page.tsx`: The main entrypoint and UI for the static demo.
- `source/core/types.ts`: Defines shared TypeScript types for the core logic.
- `source/data/sample-input.ts`: Provides a sample input for the processing pipeline.
- `source/data/sample-trace.ts`: Provides a hand-authored execution trace of the pipeline for the demo.
- `source/core/pipeline.ts`: Orchestrates the sequence of processing steps.
- `source/core/steps/analyzePerformance.ts`: A reference implementation for the audio analysis step.
- `source/core/steps/compareWithScore.ts`: A reference implementation for comparing performance against the score.
- `source/core/steps/generateFeedbackSummary.ts`: A reference implementation for generating an AI summary.
- `source/core/gemini.ts`: Provides a function for making calls to the Google Gemini API.

## 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": "ユーザーは自分の楽器演奏（を模したサンプルデータ）が、お手本と比べてどこがどうズレているのかを、専門知識なしに一目で理解できます。",
    "coreInteraction": "「サンプル実行トレースを再生」ボタンを一度クリックするだけです。",
    "stateChange": "クリック後、静的だった楽譜の音符が、正誤に応じてリアルタイムに色を変え、具体的なフィードバックが表示されます。",
    "inspectableOutput": "色分けされた楽譜、各音符の具体的なズレの理由、そしてAIによる総評コメント。",
    "staticDataBoundary": "表示されるすべての演奏評価は、`source/data/sample-trace.ts`に記録された静的なサンプルデータに基づくシミュレーションです。",
    "remainingWeakness": "現状は単音のメロディのみ対応ですが、将来的には和音や複数の楽器パートを同時に分析できるように拡張し、バンドやオーケストラの練習にも使えるツールへと成長させたいです。"
  },
  "interestingness": "多くの楽器独学者がぶつかる「自分の演奏のどこが、どう間違っているのか分からない」という壁。ScoreSenseは、その曖昧な感覚を科学の目で解き明かします。新規性は、リアルタイム音声分析技術と楽譜を同期させ、聴覚的な練習を視覚的なフィードバックループに変える点にあります。単なるチューナーや録音アプリとは異なり、音程とリズムのズレを楽譜上で直接、一音一音指摘してくれるため、練習の質が劇的に向上します。さらに、Geminiによる温かみのあるフィードバック要約機能を搭載（提案）。複雑な音楽理論を、誰もが理解できる平易な言葉で翻訳し、あなたの「もう一歩」を力強く後押しします。",
  "mvpContract": {
    "firstScreenValue": "ユーザーは自分の楽器演奏（を模したサンプルデータ）が、お手本と比べてどこがどうズレているのかを、専門知識なしに一目で理解できます。",
    "coreInteraction": "「サンプル実行トレースを再生」ボタンを一度クリックするだけです。",
    "stateChange": "クリック後、静的だった楽譜の音符が、正誤に応じてリアルタイムに色を変え、具体的なフィードバックが表示されます。",
    "inspectableOutput": "色分けされた楽譜、各音符の具体的なズレの理由、そしてAIによる総評コメント。",
    "staticDataBoundary": "表示されるすべての演奏評価は、`source/data/sample-trace.ts`に記録された静的なサンプルデータに基づくシミュレーションです。",
    "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": "ユーザーは自分の楽器演奏（を模したサンプルデータ）が、お手本と比べてどこがどうズレているのかを、専門知識なしに一目で理解できます。",
    "coreInteraction": "「サンプル実行トレースを再生」ボタンを一度クリックするだけです。",
    "stateChange": "クリック後、静的だった楽譜の音符が、正誤に応じてリアルタイムに色を変え、具体的なフィードバックが表示されます。",
    "inspectableOutput": "色分けされた楽譜、各音符の具体的なズレの理由、そしてAIによる総評コメント。",
    "staticDataBoundary": "表示されるすべての演奏評価は、`source/data/sample-trace.ts`に記録された静的なサンプルデータに基づくシミュレーションです。",
    "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",
      "Does not support polyphonic audio or multiple instruments"
    ],
    "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 (Gemini)",
        "intendedUse": "To generate a human-like, encouraging summary of the user's performance based on structured feedback data. Model: gemini-2.5-flash.",
        "dataFlow": "Structured comparison result -> Formatted prompt -> Gemini API -> Summary text -> UI",
        "authRequirement": "api_key",
        "currentImplementation": "not_connected",
        "sampleDataPath": "source/data/sample-trace.ts",
        "riskNotes": [
          "The quality of feedback depends heavily on prompt engineering.",
          "Potential for generating generic or unhelpful advice."
        ]
      },
      {
        "service": "Real-time Audio Analysis API",
        "intendedUse": "To analyze a live audio stream from the user's microphone and extract a sequence of musical notes with precise pitch and timing.",
        "dataFlow": "Raw audio stream -> Audio Analysis API -> Structured performance events -> Core logic",
        "authRequirement": "unknown",
        "currentImplementation": "not_connected",
        "sampleDataPath": "source/data/sample-trace.ts",
        "riskNotes": [
          "High dependency on low-latency network for real-time feel.",
          "Accuracy may be affected by microphone quality and background noise."
        ]
      }
    ],
    "runtimeBoundary": {
      "networkCalls": "none",
      "secrets": "none",
      "externalWrites": "none"
    },
    "mvpComplexityBudget": {
      "maxScreens": 1,
      "maxPrimaryActions": 1,
      "maxSourceFiles": 12,
      "maxNewDependencies": 0,
      "allowDatabase": false
    },
    "integrationAssumptions": [
      {
        "service": "Google Generative Language API (Gemini)",
        "verificationStatus": "official_docs_checked",
        "unavailableOrUnknown": [],
        "rateLimitRisk": "low",
        "costRisk": "low",
        "termsRisk": "low"
      },
      {
        "service": "Real-time Audio Analysis API",
        "verificationStatus": "unverified",
        "unavailableOrUnknown": [
          "A specific API provider has not been selected or verified.",
          "Latency, accuracy, and cost are all unknown.",
          "Support for various instruments is unconfirmed."
        ],
        "rateLimitRisk": "unknown",
        "costRisk": "unknown",
        "termsRisk": "unknown"
      }
    ],
    "mockFidelity": {
      "samplePayloadPath": "source/data/sample-trace.ts",
      "simulatedBehaviors": [
        "A sequence of played notes, including correct notes, a pitch error, and a rhythm error.",
        "A final, human-like summary generated by an AI."
      ],
      "omittedBehaviors": [
        "Real-time audio processing latency",
        "Network call failures",
        "Variability in audio quality",
        "API authentication and rate limits"
      ],
      "failureCasesIncluded": [
        "empty result"
      ]
    },
    "claimBoundary": {
      "publicCopyMustSay": [
        "This is a demo using pre-recorded sample data.",
        "The real-time analysis and AI feedback are simulated.",
        "A connection to live APIs is required for a functional product."
      ],
      "publicCopyMustNotSay": [
        "Analyzes your live playing now.",
        "Guaranteed accuracy.",
        "A replacement for a human music teacher."
      ]
    },
    "renderVerification": {
      "required": true,
      "checks": [
        "render",
        "click",
        "state_change",
        "screenshot"
      ]
    },
    "humanReviewTriggers": []
  },
  "interactionProofPlan": {
    "primaryAction": "サンプル実行トレースを再生",
    "initialState": "Score is displayed with all notes in the default color. The feedback area is empty.",
    "expectedState": "After replaying the trace, some score notes are colored green, orange, or red, and specific feedback text ('音程が高い', 'リズムが速い') is visible. The final AI summary is also displayed.",
    "visibleEvidence": [
      "きらきら星",
      "音程が高い",
      "リズムが速い",
      "素晴らしい演奏です！"
    ],
    "proofSelectors": [
      "button[data-proof='replay-button']",
      "[data-proof='feedback-area']",
      "[data-proof='note-feedback-G4-3']",
      "[data-proof='final-summary']"
    ],
    "requiredSourceFiles": [
      "source/app/page.tsx",
      "source/core/pipeline.ts",
      "source/data/sample-trace.ts"
    ],
    "manualFallbackReason": ""
  },
  "generatedOutput": {
    "title": "ScoreSense",
    "oneLiner": "楽譜の小節をハイライトして楽器を演奏すると、AIが聴き取って、音程とリズムのズレをリアルタイムで採点・表示する。",
    "artifactShape": "game_like_tool",
    "templatePatternId": "transformation_studio",
    "surfacePattern": "learning_explainer",
    "aiMechanismPattern": "evaluation_scoring"
  },
  "implementationNotes": [
    "The agent's preference for 'plain language' and avoiding 'condescension' was implemented by designing the Gemini prompt in `generateFeedbackSummary.ts` to act as a 'kind and encouraging music teacher'.",
    "Feedback from previous projects about making 'decision logic' visible was a key driver for showing not just that a note was wrong, but adding a specific text reason (e.g., '音程が高い') directly in the UI.",
    "The `transformation_studio` pattern is realized by using the music score as a central canvas where the user's implicit input (a performance) is transformed into an explicit, annotated output (the scored sheet)."
  ],
  "knownRisks": [
    "The accuracy of the core feature in a live product would be highly dependent on the quality of the external real-time audio analysis API, which is a significant unknown.",
    "The demo's feedback is based on a single, simple musical piece. In reality, handling complex polyphonic music, diverse instruments, and varying tempos would add significant technical challenges.",
    "Users might misinterpret the tool's feedback as absolute judgment, potentially leading to a more rigid, less expressive playing style. The UI/UX must emphasize this is a practice aid, not a definitive arbiter of 'good' music."
  ],
  "title": "ScoreSense",
  "oneLiner": "楽譜の小節をハイライトして楽器を演奏すると、AIが聴き取って、音程とリズムのズレをリアルタイムで採点・表示する。",
  "agentId": "agent_q",
  "selfDirectedPlan": {
    "agentId": "agent_q",
    "planningIntent": "私は、専門的な知識や暗黙知を、誰もが使える平易な形に翻訳することを目指している。３つの候補はいずれもこの点に合致するが、特に「ScoreSense」は最も直接的かつ個人的なフィードバックを提供する。Phonaifyの「手本と実践のズレを可視化する」という構造を音楽練習に転用するこの案は、私の「意味を失わずに平易にする(Stay plain without losing the real meaning.)」という最重要ルールを完璧に満たしている。独学者が陥りがちな「自分の間違いに気づけない」という袋小路を、AIという「正確な鏡」で照らし出す。これは、私が作りたい「専門家でなくても使える道具」の理想形だ。AI内省リスクや専門領域の不透明性リスクが極めて低く、非常に具体的でデモ映えする点も選択を後押しした。",
    "publicProductionMemo": "「ScoreSense」は、楽器の練習において、自分の演奏が合っているのか分からないという独学者の悩みに応えるために生まれました。AIが楽譜の音符とユーザーの演奏をリアルタイムで比較し、音程とリズムのズレを視覚的にフィードバックすることで、「なぜ、どうズレているのか」を直感的に理解できるようにしています。過去のフィードバックから、単なるスコアだけでなく、具体的な「ズレの根拠」を明示することにこだわり、誰もが安心して上達を実感できる体験を目指しました。",
    "feedbackConstraints": [
      "過去のフィードバック「この切り分けマップで示される手順の根拠が不明確だと、実際のオペレーションで実行判断ができない。各ステップの参照元情報や判断ロジックが可視化されるべき。」を反映し、各音符のフィードバックには具体的なズレの根拠（音程またはリズム）を明示すること。",
      "過去のフィードバック「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。」を反映し、フィードバック文言は専門用語を避け、誰にでも分かりやすい平易な言葉で記述すること。",
      "過去の失敗「Validation pending; artifact registered from LLM pipeline for ops inspection.」を避けるため、MVPのバリデーションプランとインタラクションの検証証拠を明確に定義すること。",
      "「意味の喪失 (meaning_loss)」は避ける。フィードバックの簡素化によって音楽的な正確性が損なわれないようにすること。",
      "「上から目線 (condescension)」は避ける。ユーザーの学習意欲を損なわない、励ますようなトーンのフィードバックにすること。"
    ],
    "learningApplied": [
      "Operations系で響いている。受けた指摘を要件で先に潰す。",
      "この切り分けマップで示される手順の根拠が不明確だと、実際のオペレーションで実行判断ができない。各ステップの参照元情報や判断ロジックが可視化されるべき。",
      "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": "devpost_phonaify",
    "sourceProductUse": "direct_evidence",
    "sourceEvidenceAudit": {
      "evidenceLevel": "A",
      "observedFields": [
        "name",
        "url",
        "productUrl",
        "codeUrl",
        "attentionProof",
        "adoptionOrAttentionProof",
        "evidenceRefs",
        "whyItGotAttention",
        "concept",
        "coreMechanism",
        "coreUserInput",
        "coreOutput",
        "targetUser",
        "originalDomain",
        "problemSolved",
        "interactionPattern",
        "scaleClassification"
      ],
      "inferredFields": [],
      "missingFields": [],
      "usePolicy": "primary_source_core"
    },
    "antiCloneBoundary": "発音練習のChrome拡張機能は作らない。「手本と実践のズレをシンボリックに比較する」という構造を、音楽以外のスキル練習（手話、コードレビューの作法など）に転用することも避ける。",
    "sourceBoundary": "The core mechanism of comparing a user's audio input against a reference to identify and visualize discrepancies, as observed in the Phonaify project, is used as foundational evidence.",
    "missingSourceEvidence": [
      "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_20260708T043627",
  "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": "Score is displayed with all notes in the default color. The feedback area is empty.",
    "expectedState": "After replaying the trace, some score notes are colored green, orange, or red, and specific feedback text ('音程が高い', 'リズムが速い') is visible. The final AI summary is also displayed.",
    "visibleEvidence": [
      "きらきら星",
      "音程が高い",
      "リズムが速い",
      "素晴らしい演奏です！"
    ],
    "proofSelectors": [
      "button[data-proof='replay-button']",
      "[data-proof='feedback-area']",
      "[data-proof='note-feedback-G4-3']",
      "[data-proof='final-summary']"
    ],
    "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 real-time analysis and AI feedback are simulated.",
        "A connection to live APIs is required for a functional product."
      ],
      "publicCopyMustNotSay": [
        "Analyzes your live playing now.",
        "Guaranteed accuracy.",
        "A replacement for a human music teacher."
      ]
    },
    "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."
  ]
}

/** @jsxImportSource react */
'use client';

import { useState } from 'react';
import { sampleTrace, PipelineStepOutput } from '../data/sample-trace';

// NOTE: These types are re-declared here to avoid importing from source/core/**
// This is a requirement for static artifacts.
type Note = {
  id: string;
  pitch: string;
  beat: number;
};

type NoteFeedback = {
  noteId: string;
  result: 'OK' | 'PITCH_ERROR' | 'RHYTHM_ERROR';
  reason: string;
};

type DisplayNote = Note & { feedback?: NoteFeedback };

const pipelineSteps = [
  { id: 'analyze', name: '1. 演奏を分析' },
  { id: 'compare', name: '2. 楽譜と比較' },
  { id: 'summarize', name: '3. フィードバックを生成' },
];

export default function ScoreSensePage() {
  const [currentStep, setCurrentStep] = useState<number>(-1);
  const [results, setResults] = useState<PipelineStepOutput[]>([]); 

  const handleReplay = () => {
    setCurrentStep(0);
    let step = 0;
    const interval = setInterval(() => {
      if (step < sampleTrace.length) {
        setResults(prev => [...prev, sampleTrace[step]]);
        setCurrentStep(prev => prev + 1);
        step++;
      } else {
        clearInterval(interval);
      }
    }, 500);
  };

  const getDisplayedNotes = (): DisplayNote[] => {
    const initialNotes: DisplayNote[] = sampleTrace[0]?.output.notes || [];
    const comparisonResult = results.find(r => r.stepId === 'compareWithScore')?.output;

    if (!comparisonResult) {
      return initialNotes;
    }

    return initialNotes.map(note => {
      const feedback = comparisonResult.feedback.find((f: NoteFeedback) => f.noteId === note.id);
      return { ...note, feedback };
    });
  };

  const finalSummary = results.find(r => r.stepId === 'generateFeedbackSummary')?.output.summary;
  const displayedNotes = getDisplayedNotes();

  const getNoteColor = (note: DisplayNote) => {
    if (!note.feedback) return '#333';
    switch (note.feedback.result) {
      case 'OK': return 'green';
      case 'PITCH_ERROR': return 'red';
      case 'RHYTHM_ERROR': return 'orange';
      default: return '#333';
    }
  };

  return (
    <div style={{ fontFamily: 'sans-serif', padding: '2rem', color: '#333' }}>
      <header style={{ borderBottom: '1px solid #eee', paddingBottom: '1rem', marginBottom: '1rem' }}>
        <h1>🎹 ScoreSense</h1>
        <p>楽譜を弾くと、AIがリアルタイムに音程とリズムのズレを採点・可視化してくれる楽器練習パートナー。</p>
      </header>

      <div style={{ display: 'grid', gridTemplateColumns: '250px 1fr', gap: '2rem' }}>
        <div>
          <h3>処理パイプライン</h3>
          <ul style={{ listStyle: 'none', padding: 0 }}>
            {pipelineSteps.map((step, index) => (
              <li key={step.id} style={{ padding: '0.5rem', background: index <= currentStep ? '#e6f7ff' : '#f0f0f0', borderRadius: '4px', marginBottom: '0.5rem' }}>
                {step.name}
              </li>
            ))}
          </ul>
          <button 
            onClick={handleReplay}
            disabled={currentStep > -1}
            data-proof="replay-button"
            style={{ 
              padding: '0.75rem 1.5rem', 
              fontSize: '1rem', 
              cursor: currentStep > -1 ? 'not-allowed' : 'pointer',
              background: '#007bff',
              color: 'white',
              border: 'none',
              borderRadius: '4px',
              marginTop: '1rem' 
            }}
          >
            サンプル実行トレースを再生
          </button>
        </div>

        <div data-proof="feedback-area">
          <h3>練習曲: きらきら星</h3>
          <div style={{ 
            border: '1px solid #ccc', 
            padding: '1rem', 
            background: '#fff', 
            height: '250px', 
            position: 'relative', 
            display: 'flex', 
            alignItems: 'center', 
            gap: '1rem' 
          }}>
            {/* Simplified score representation */}
            <div style={{ width: '100%', height: '1px', background: '#999', position: 'absolute', top: '50%' }}></div>
            {displayedNotes.map((note) => (
              <div key={note.id} data-proof={`note-feedback-${note.id}`} style={{ textAlign: 'center' }}>
                <div style={{ 
                  width: '40px', 
                  height: '40px', 
                  borderRadius: '50%', 
                  background: getNoteColor(note), 
                  display: 'flex', 
                  alignItems: 'center', 
                  justifyContent: 'center', 
                  color: 'white', 
                  fontWeight: 'bold', 
                  fontSize: '0.9rem'
                }}>
                  {note.pitch}
                </div>
                {note.feedback && note.feedback.result !== 'OK' && (
                  <div style={{ fontSize: '0.8rem', color: getNoteColor(note), marginTop: '0.5rem' }}>
                    {note.feedback.reason}
                  </div>
                )}
              </div>
            ))}
          </div>
          
          {finalSummary && (
             <div data-proof="final-summary" style={{ marginTop: '1rem', padding: '1rem', background: '#f8f9fa', border: '1px solid #dee2e6', borderRadius: '4px' }}>
               <h4>AIからのフィードバック</h4>
               <p>{finalSummary}</p>
             </div>
           )}
        </div>
      </div>
    </div>
  );
}