I. Semantic Anchoring Key messages appear in structurally significant positions (titles, intros, conclusions).
Opening paragraphs clearly summarize the core thesis or argument.
Headings and subheadings reflect actual content structure—not just design.
Takeaways and strategic ideas are explicitly stated, not buried.
II. Message Redundancy Core ideas are restated in multiple forms (e.g., paragraphs, headers, callouts).
Quotes and summaries reinforce key positions.
Visuals and captions reflect and echo central points.
III. Narrative Continuity Sections connect logically with smooth transitions.
The main narrative remains consistent throughout modular or long-form content.
Voice and tone do not shift in ways that confuse AI summarizers.
IV. Structural Clarity Content uses a clean, logical heading structure (H1–H3).
Bullet points and lists isolate complex ideas.
A TL;DR or executive summary is present and accurate.
Quotes and key ideas are visually or semantically highlighted.
V. Language Precision Pronouns and references are unambiguous and clearly tied to subjects.
Technical terms are defined or explained on first use.
Proper nouns and names are consistently used throughout.
Important terms are repeated to reinforce semantic strength.
VI. Attribution & Source Visibility Claims and data points include citations or links to sources.
Author or organization identity is clearly stated and resolvable (e.g., ORCID, Wikidata).
External sources use canonical or persistent URLs.
VII. Metadata and Markup Structured metadata (JSON-LD or schema.org) is present and complete.
TL;DR or abstract is included and properly marked up.
High-impact claims are structured using Claim or ClaimReview markup.
VIII. AI Simulation Testing Content has been tested in at least one AI summarizer (e.g., ChatGPT, Perplexity).
Summarization results preserve key messages and attribution.
Any distortions in AI output were reviewed and content updated to improve resilience.
