Files
trumpsignal-frontend/app/[locale]/trades/page.tsx
T
k aa6ede051e 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>
2026-05-30 03:08:59 +08:00

59 lines
2.2 KiB
TypeScript

import type { Metadata } from 'next'
import { getLocale } from 'next-intl/server'
import TradesPageClient from './TradesPageClient'
import Breadcrumbs from '@/components/seo/Breadcrumbs'
const siteUrl = process.env.NEXT_PUBLIC_SITE_URL || 'https://trumpsignal.com'
export async function generateMetadata(): Promise<Metadata> {
const locale = await getLocale()
const isZh = false // i18n shelved — Chinese branches kept as dead code for future revival; see messages/zh.json
const title = isZh ? '交易执行与持仓' : 'Trades & Open Positions'
const description = isZh
? '查看当前持仓、历史成交、按信号来源拆分的盈亏,以及机器人是否已经具备真实执行条件。'
: 'Review open positions, historical executions, source-level P&L, and whether the bot is ready for live trading.'
return {
title,
description,
openGraph: { title, description },
alternates: {
canonical: `${siteUrl}/${locale}/trades`,
languages: {
en: `${siteUrl}/en/trades`,
},
},
}
}
// GEO: the trade history is a dataset — every bot execution with entry/exit,
// P&L, hold time, and the signal that triggered it. Cited for "track record"
// and "does it work" queries.
const tradesDataset = {
'@context': 'https://schema.org',
'@type': 'Dataset',
'@id': `${siteUrl}/en/trades#dataset`,
name: 'Trump Alpha trade execution history',
description:
'Record of every signal-triggered trade: asset, direction, entry and exit price, realised P&L, hold time, and the source signal that triggered it. Public and timestamped.',
url: `${siteUrl}/en/trades`,
keywords: ['crypto trading track record', 'Hyperliquid', 'P&L', 'backtest', 'signal performance'],
isAccessibleForFree: true,
creator: { '@type': 'Organization', name: 'Endorphin', url: siteUrl },
publisher: { '@id': `${siteUrl}/#org` },
license: `${siteUrl}/en/terms`,
temporalCoverage: '2025-01-01/..',
}
export default function TradesPage() {
return (
<>
<script
type="application/ld+json"
dangerouslySetInnerHTML={{ __html: JSON.stringify(tradesDataset) }}
/>
<Breadcrumbs items={[{ name: 'Trades', path: '/en/trades' }]} />
<TradesPageClient />
</>
)
}