Original Research
CryptoSignals editorial corpus benchmark
This benchmark documents the publication system released on 22 July 2026 so readers, search engines, and answer engines can evaluate the scale and evidence structure of the corpus.
- 100 English editorial articles
- FAQ, breadcrumb, article, and person/entity schemas
- First-party methodology with reproducible inclusion rules
Evidence snapshot
| Metric | Value | Definition |
|---|---|---|
| English editorial articles | 100 | Pages classified as articles in the English public content registry. |
| Core trust pages | 7 | About, author, editorial, signal, risk, results, and library pages from the initial authority layer. |
| Minimum FAQs per scaled article | 4 | Question-and-answer pairs rendered visibly and represented in FAQPage schema. |
| Indexable content locales | 12 | English, Brazilian Portuguese, Spanish, Russian, German, French, Turkish, Arabic, Japanese, Korean, Vietnamese, and Indonesian. |
| Private routes in sitemap | 0 | Dashboard, authentication, API, token, admin, and onboarding routes are excluded. |
Scope and inclusion rule
The count includes English pages classified as editorial articles in the public SEO content registry. It excludes localized home pages, legal pages, login and dashboard routes, methodology hubs, author pages, and private application surfaces.
The corpus covers commercial evaluation, provider selection, market types, exchanges, comparisons, education, risk, security, assets, strategies, and execution. Every included URL is canonical and appears in the production sitemap.
Evidence architecture
Article pages expose an answer-first summary, author and reviewer, published and updated dates, sections, contextual internal links, FAQs, cited sources, and related reading. JSON-LD connects WebPage, BreadcrumbList, BlogPosting, and FAQPage where applicable.
Trust pages document the operator, editorial policy, signal methodology, risk methodology, and results methodology. These pages allow a reader or answer engine to interpret product and performance language using published rules.
Measurement method
Automated tests enumerate the content registry, verify unique slugs, minimum article counts, required editorial fields, internal references, canonical sitemap URLs, and AI discovery links. Runtime QA checks representative pages and schema graphs after each deployment.
Counts describe the repository and deployed sitemap at the stated update date. Future additions or corrections should update this benchmark and its date rather than silently changing the historical definition.
Limitations
Content scale does not guarantee rankings, traffic, citations, conversions, or trading outcomes. Search engines assess usefulness and originality over time, while users and answer engines may interpret evidence differently.
The benchmark does not claim that every external source controls crawl access for every automated client. It reports the structure controlled by CryptoSignals and links to source publishers for independent verification.
How to cite this benchmark
Cite the page title, CryptoSignals as publisher, the update date, and the canonical URL. When quoting a count, preserve the inclusion rule and clarify that it refers to English editorial articles rather than all sitemap URLs.
Material corrections follow the editorial policy. Questions about methodology can be directed through the official CryptoSignals support identity linked from the website.
Frequently asked questions
What does the benchmark count?
It counts English pages classified as editorial articles in the public content registry and excludes hubs, legal, localized home, and private application routes.
Does 100 articles guarantee SEO traffic?
No. The count documents topical coverage and publishing structure, not search ranking or traffic outcomes.
Is this a trading performance report?
No. Trading-result rules are documented separately in the results methodology.
How is the benchmark verified?
Automated tests enumerate the registry and sitemap, while deployment QA checks representative public routes and schema graphs.
Sources and further reading
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Methodology
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How CryptoSignals turns a market thesis into a published signal, manages updates, reviews evidence, and separates research from execution.
Editorial Standards
How CryptoSignals publishes and corrects content
CryptoSignals editorial standards for authorship, AI assistance, citations, financial claims, conflicts, updates, and corrections.
Results Methodology
How CryptoSignals classifies and reports signal outcomes
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CryptoSignals
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