The SIGNAL™ Framework

Implement a strict heading hierarchy (H1→H6) where every heading accurately describes the content beneath it - agents use headings as their primary navigation system

Add Schema.org JSON-LD markup for every content type: Article, FAQPage, HowTo, DefinedTerm, Person, Organization - this is the agent's metadata layer

Use semantic HTML5 elements (article, section, nav, aside, figure, figcaption) instead of generic divs - agents parse element semantics to understand content purpose

Structure data tables with proper thead, tbody, scope attributes, and data-value attributes for numeric cells - agents extract tabular data for comparison and citation

Ensure content renders without JavaScript - agents that cannot execute JS will see nothing if your content is client-side rendered only

Begin every page with a clear, factual summary (2-3 sentences) that states exactly what the content covers - agents use opening content to determine relevance before processing the full page

Define the scope explicitly: what this content addresses, what it does not address, and what related topics are covered elsewhere - ambiguity wastes agent processing and reduces citation confidence

Write for specificity over generality: 'Trust recovery takes an average of 3.2 interactions after a delegation failure' is citable; 'Trust recovery is important' is not

Include a clear content type declaration: is this a research essay, a framework guide, a case study, a glossary entry, or a how-to guide? Agents use content type to determine citation appropriateness

Provide explicit definitions for domain-specific terms on first use - agents cannot infer meaning from context the way experienced human readers can

Display author credentials prominently with structured Person schema: name, role, organisation, expertise areas, and links to verifiable profiles - agents use author authority as a primary trust signal

Include publication dates and last-updated timestamps in both human-readable and machine-readable formats (ISO 8601) - agents weight recency heavily in citation decisions

Provide explicit source attribution for all claims, statistics, and frameworks - agents trace citation chains and penalise unsourced assertions

Implement editorial standards signals: peer review status, editorial process description, correction policy, and version history - these are the trust credentials agents evaluate

Add institutional authority markers: organisation description, founding date, domain expertise, publication record, and affiliations - agents assess institutional credibility alongside individual author authority

Include a machine-readable table of contents with anchor links for every page longer than 500 words - agents use TOC structure to locate specific information without parsing the entire document

Implement breadcrumb navigation with BreadcrumbList schema on every page - agents use breadcrumbs to understand content hierarchy and site structure

Add explicit cross-references between related content using descriptive anchor text (not 'click here') - agents follow cross-references to build comprehensive understanding of topics

Create a logical URL structure that reflects content hierarchy: /topic/subtopic/specific-item - agents parse URL structure as a signal of content organisation

Provide sitelinks, XML sitemap, and llms.txt file that maps the complete content architecture - these are the agent's navigation guides to your entire content ecosystem

Assign stable, permanent URLs to every piece of content - agents store URLs as citation references; broken links destroy citation integrity and trust

Include citation metadata in structured data: title, author, publication date, publisher, URL, and abstract - this is the citation record agents extract

Write quotable passages: key findings, definitions, and conclusions should be self-contained sentences that make sense when extracted from context - agents cite passages, not pages

Provide canonical URLs and handle redirects properly - duplicate content with different URLs confuses agent citation systems and dilutes authority signals

Implement content versioning with clear version identifiers - when content is updated, agents need to know whether their cached version is still current

Display both publication date and last-reviewed date on every page - agents distinguish between 'published 2024, never updated' and 'published 2024, reviewed March 2026'

Implement a content review schedule and communicate it: 'This content is reviewed quarterly' gives agents confidence in ongoing accuracy

Use semantic versioning for major content changes and maintain a visible changelog - agents can track content evolution and cite specific versions

Mark deprecated or superseded content explicitly with links to current versions - agents that cite outdated content damage their own credibility and yours

Implement WebSub or similar notification protocols so agents can subscribe to content updates rather than polling - this is the real-time content maintenance infrastructure