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>
This commit is contained in:
k
2026-05-30 03:08:59 +08:00
parent f8805f5ba6
commit aa6ede051e
13 changed files with 443 additions and 133 deletions
+48
View File
@@ -1,5 +1,6 @@
import type { Metadata } from 'next'
import Link from 'next/link'
import Breadcrumbs from '@/components/seo/Breadcrumbs'
const siteUrl = process.env.NEXT_PUBLIC_SITE_URL || 'https://trumpsignal.com'
@@ -303,13 +304,60 @@ const SIGNAL_COLOR: Record<string, string> = {
DIVERGENCE: '#f5a524',
}
// Map a free-text case date ("March 2, 2025", "April 2025", "Illustrative
// composite") to an ISO date where possible. Returns undefined for vague /
// non-date labels so we omit datePublished rather than emit garbage.
function caseIsoDate(raw: string): string | undefined {
const d = new Date(raw)
return isNaN(d.getTime()) ? undefined : d.toISOString().slice(0, 10)
}
export default async function CaseStudiesPage({ params }: { params: Promise<{ locale: string }> }) {
const { locale } = await params
const copy = getCopy(locale)
const isZh = false // i18n shelved — Chinese branches kept as dead code for future revival; see messages/zh.json
// ── GEO: each case as a schema.org/Article in an ItemList ─────────────────
// These documented event walkthroughs are exactly what AI answer engines
// (Perplexity, Gemini, ChatGPT) cite for "did Trump posts move crypto"
// queries. Structured data makes them machine-citeable. Evidence URLs become
// citation links; Endorphin is the author/publisher.
const pageUrl = `${siteUrl}/${locale}/case-studies`
const caseJsonLd = {
'@context': 'https://schema.org',
'@type': 'ItemList',
'@id': `${pageUrl}#cases`,
name: copy.title,
description: copy.description,
itemListElement: copy.cases.map((c, i) => {
const iso = caseIsoDate(c.date)
const article: Record<string, unknown> = {
'@type': 'Article',
'@id': `${pageUrl}#${c.id}`,
headline: c.title,
description: c.summary,
articleBody: c.detail,
about: c.asset,
author: { '@type': 'Organization', name: 'Endorphin', url: siteUrl },
publisher: { '@id': `${siteUrl}/#org` },
isPartOf: { '@id': `${siteUrl}/#website` },
}
if (iso) article.datePublished = iso
if (c.externalUrl) {
article.citation = c.externalUrl
article.isBasedOn = c.externalUrl
}
return { '@type': 'ListItem', position: i + 1, item: article }
}),
}
return (
<div className="page" style={{ maxWidth: 780 }}>
<script
type="application/ld+json"
dangerouslySetInnerHTML={{ __html: JSON.stringify(caseJsonLd) }}
/>
<Breadcrumbs items={[{ name: copy.heroTitle, path: `/${locale}/case-studies` }]} />
<div className="page-head">
<div>
<h1 className="page-title">{copy.heroTitle}</h1>