feat(seo/geo): Dataset + Article + BreadcrumbList structured data, noindex archive
GEO (AI answer engines) — make the signal feeds and case studies machine-citeable: - Dataset JSON-LD on /trump, /kol, /trades (creator=Endorphin, publisher→#org, isAccessibleForFree, temporalCoverage). These are the "data/history/track record" entities Perplexity/Gemini/ChatGPT cite. - case-studies: ItemList of 5 Article nodes, each with headline/description/ articleBody/about + citation→evidence URL + author=Endorphin. ISO dates derived where parseable, omitted for vague labels. - public/llms-full.txt: single-doc full reference (methodology + glossary + case studies w/ sources inlined) for one-fetch AI ingestion; linked from llms.txt. SEO: - Breadcrumbs component (components/seo/Breadcrumbs.tsx) → BreadcrumbList JSON-LD on the 8 indexable content pages (trump/kol/macro/trades/analytics/ methodology/glossary/case-studies). - /archive split into server page + ArchivePageClient; server page sets robots noindex (legacy/test data — thin-content risk). - openGraph added to /trades and /analytics (previously meta+canonical only). Verified: tsc 0 errors, next build passes, runtime curl confirms all JSON-LD types render and llms-full.txt serves 200. No trading/API/component-logic changes. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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@@ -1,5 +1,6 @@
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import type { Metadata } from 'next'
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import Link from 'next/link'
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import Breadcrumbs from '@/components/seo/Breadcrumbs'
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const siteUrl = process.env.NEXT_PUBLIC_SITE_URL || 'https://trumpsignal.com'
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@@ -303,13 +304,60 @@ const SIGNAL_COLOR: Record<string, string> = {
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DIVERGENCE: '#f5a524',
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}
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// Map a free-text case date ("March 2, 2025", "April 2025", "Illustrative
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// composite") to an ISO date where possible. Returns undefined for vague /
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// non-date labels so we omit datePublished rather than emit garbage.
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function caseIsoDate(raw: string): string | undefined {
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const d = new Date(raw)
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return isNaN(d.getTime()) ? undefined : d.toISOString().slice(0, 10)
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}
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export default async function CaseStudiesPage({ params }: { params: Promise<{ locale: string }> }) {
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const { locale } = await params
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const copy = getCopy(locale)
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const isZh = false // i18n shelved — Chinese branches kept as dead code for future revival; see messages/zh.json
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// ── GEO: each case as a schema.org/Article in an ItemList ─────────────────
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// These documented event walkthroughs are exactly what AI answer engines
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// (Perplexity, Gemini, ChatGPT) cite for "did Trump posts move crypto"
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// queries. Structured data makes them machine-citeable. Evidence URLs become
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// citation links; Endorphin is the author/publisher.
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const pageUrl = `${siteUrl}/${locale}/case-studies`
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const caseJsonLd = {
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'@context': 'https://schema.org',
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'@type': 'ItemList',
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'@id': `${pageUrl}#cases`,
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name: copy.title,
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description: copy.description,
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itemListElement: copy.cases.map((c, i) => {
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const iso = caseIsoDate(c.date)
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const article: Record<string, unknown> = {
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'@type': 'Article',
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'@id': `${pageUrl}#${c.id}`,
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headline: c.title,
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description: c.summary,
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articleBody: c.detail,
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about: c.asset,
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author: { '@type': 'Organization', name: 'Endorphin', url: siteUrl },
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publisher: { '@id': `${siteUrl}/#org` },
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isPartOf: { '@id': `${siteUrl}/#website` },
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}
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if (iso) article.datePublished = iso
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if (c.externalUrl) {
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article.citation = c.externalUrl
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article.isBasedOn = c.externalUrl
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}
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return { '@type': 'ListItem', position: i + 1, item: article }
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}),
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}
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return (
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<div className="page" style={{ maxWidth: 780 }}>
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<script
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type="application/ld+json"
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dangerouslySetInnerHTML={{ __html: JSON.stringify(caseJsonLd) }}
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/>
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<Breadcrumbs items={[{ name: copy.heroTitle, path: `/${locale}/case-studies` }]} />
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<div className="page-head">
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<div>
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<h1 className="page-title">{copy.heroTitle}</h1>
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