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feat: add motivation cards and proposition box to enhance user engagement and clarity
1 parent c80af87 commit 89cfcb3

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Lines changed: 107 additions & 1 deletion

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docs/src/app/page.module.css

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@@ -294,6 +294,70 @@
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margin: 0 0 40px;
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}
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.motivationGrid {
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display: grid;
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grid-template-columns: repeat(3, 1fr);
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gap: 18px;
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margin-bottom: 24px;
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}
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.motivationCard {
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background: #ffffff;
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border: 1px solid #cfd9ea;
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border-radius: 14px;
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padding: 22px 24px;
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box-shadow: 0 2px 8px rgba(30, 64, 175, 0.04);
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}
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.motivationCardTag {
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display: inline-block;
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font-size: 12px;
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font-weight: 700;
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letter-spacing: 0.07em;
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text-transform: uppercase;
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color: #1e3a8a;
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background: #dbeafe;
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border: 1px solid #93c5fd;
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border-radius: 999px;
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padding: 4px 10px;
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margin-bottom: 12px;
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}
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.motivationCardTitle {
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font-size: 1rem;
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font-weight: 700;
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color: #0f172a;
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margin: 0 0 8px;
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line-height: 1.35;
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}
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.motivationCardDesc {
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margin: 0;
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font-size: 0.92rem;
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color: #475569;
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line-height: 1.65;
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}
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.propositionBox {
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background: linear-gradient(135deg, rgba(29, 78, 216, 0.05) 0%, rgba(30, 64, 175, 0.08) 100%);
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border: 1px solid rgba(29, 78, 216, 0.2);
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border-left: 4px solid #1d4ed8;
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border-radius: 10px;
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padding: 18px 22px;
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margin-bottom: 40px;
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}
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.propositionBox p {
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margin: 0;
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font-size: 0.975rem;
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color: #1e3a8a;
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line-height: 1.7;
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}
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.propositionBox strong {
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color: #1e3a8a;
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}
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.archImgWrap {
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border-radius: 14px;
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overflow: hidden;
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grid-template-columns: 1fr;
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}
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.motivationGrid {
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grid-template-columns: 1fr;
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}
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.pipelineGrid {
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grid-template-columns: 1fr;
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}

docs/src/app/page.tsx

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@@ -88,6 +88,27 @@ const pipelineStages = [
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},
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];
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const motivationCards = [
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{
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tag: 'Env-Grounded Eval',
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title: 'Static Eval Is Insufficient',
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description:
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'Agents must interact with live network state to verify hypotheses — static eval is insufficient.',
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},
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{
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tag: 'Non-Reproducible Faults',
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title: 'No Controlled Baseline Exists',
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description:
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'Real DCN incidents occur once and cannot be re-staged — no controlled baseline exists.',
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},
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{
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tag: 'Long Dev Cycles',
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title: 'Trial-and-Error Costs Mount',
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description:
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'Without a replayable testbed, comparing strategies is slow — trial-and-error costs mount.',
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},
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];
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const benchmarkCards = [
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{
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src: '/assets/benchmark/fig_avg_score.png',
@@ -197,8 +218,25 @@ export default function HomePage() {
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<div className={styles.sectionLabel}>Research-Industry Gap</div>
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<h2 className={styles.sectionTitle}>Agentic RCA lacks production-grade evaluation</h2>
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<p className={styles.sectionDesc}>
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Despite Agentic RCA progress, 71% of large enterprises hesitate to fully automate network operations [1]. NetOpsBench bridges this gap by providing an evidence-oriented, reproducible benchmark for LLM-driven diagnosis.
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Despite Agentic RCA progress, 71% of large enterprises hesitate to fully automate
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network operations [1]. Three structural barriers block principled evaluation:
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</p>
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<div className={styles.motivationGrid}>
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{motivationCards.map((card) => (
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<article key={card.tag} className={styles.motivationCard}>
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<div className={styles.motivationCardTag}>{card.tag}</div>
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<h3 className={styles.motivationCardTitle}>{card.title}</h3>
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<p className={styles.motivationCardDesc}>{card.description}</p>
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</article>
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))}
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</div>
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<div className={styles.propositionBox}>
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<p>
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<strong>NetOpsBench</strong> provides controlled, reproducible DCN fault environments
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with <strong>localization-first scoring</strong> accounting for physical equivalences
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— enabling principled, repeatable agent evaluation.
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</p>
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</div>
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<div className={styles.archImgWrap}>
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<img
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className={styles.archImg}

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