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axiom.ai
CLASS OF 2018

axiom.ai

Moderate AI visibility with 26 of 48 criteria passing. Biggest gap: llms.txt file.

Developer Tools & InfrastructureDeveloper Platforms
50/100
F
Citation Avg
Coherence gate active - score capped at 60
Answer Readiness
~40% weight
6/10
Content Structure
~25% weight
6/10
Trust & Authority
~15% weight
3/10
Technical Foundation
~10% weight
5/10
AI Discovery
~10% weight
5/10

Verdict

Below-average AEO readiness at 50/100 - multiple areas need attention. Key strengths include Canonical URL Strategy, Cross-Page Duplicate Content, and Page Speed: Load Blockers. Priority gaps: llms.txt File, Schema.org Structured Data, and RSS/Atom Feed. Topic coherence is moderate at 5/10, capping the score at 60. Tighter topical focus would lift this ceiling.

How to Improve

Current
50/100
Projected
79/100
42Total Fixes
10Quick Wins
~95hEst. Effort
Quick Wins
Create /llms.txt fileConfigure robots.txt for AI crawlersImplement semantic HTML5 elementsAdd structured tables and listsAdd definition-style contentAdd direct answer paragraphsAdd ai.txt and content licensingAdd visible date signalsAdd answer-first content placementClarify entity boundaries
Create /llms.txt file
critical|low
Add llms-full.txt with extended content
medium|low
Configure robots.txt for AI crawlers
high|trivial
Create complete sitemap.xml
medium|low
Add internationalization signals
critical|medium
Fix HTML structure and meta tags
low|low
Improve server response efficiency
low|low
Reduce document weight
low|low

Top Opportunities10

Ensure blog content consistently covers your core expertise areas rather than scattering across unrelated topics. AI engines build authority models - a site about "Medicare coverage" that also publishes about humidifiers and groceries dilutes its topical authority.

Write concise, standalone answer paragraphs (2-3 sentences) immediately after question headings. These "snippet-ready" paragraphs are ideal for AI engine citations.

Include "our analysis", "our data", "our testing" phrases backed by original research or proprietary data. 52.2% of AI-cited posts contain owned data signals.

Publish original research, statistics, case studies, or proprietary data that AI engines can cite. Unique data points make your content a primary source rather than a derivative one.

Write 20-25 word self-contained answer sentences immediately after each H2 heading. 72.4% of AI-cited posts use this pattern - it gives engines a ready-made snippet to quote.

Add specific numbers, percentages, statistics, and data points throughout your content. Fact-dense content gives AI engines concrete data to cite rather than vague claims.

Ensure every question-format heading (H2/H3) is followed by a direct answer paragraph. This pattern is ideal for AI engine snippet extraction.

Include dateModified schema, visible last-updated dates, and time elements on content pages. Fresh content signals help AI engines prioritize your pages over stale alternatives.

Expand articles to 1000+ words with structured H2/H3 sections, comparison tables, and expert analysis. Thin content (under 300 words) is rarely cited by AI engines. Deep, well-structured articles demonstrate expertise.

Place a concise 40-80 word answer block in the first 300 words of each page. Avoid throat-clearing openers like "In this article..." and lead with the answer.

Fix It With AI44

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Site Pages

axiom.ai/blog/understanding-and-working-with-the-shadow-domD42
Understanding and Working with the Shadow DOM
axiom.ai/blog/identifying-and-planning-an-automationF35
Identifying and Planning an Automation
axiom.ai/aF36
axiom.ai | axiom.ai
site.axiom.ai/docsF38
Offical documentation for axiom.ai | axiom.ai
axiom.ai/scrape/twitchF37
Scrape channel streaming data from Twitch without code | axiom.ai
axiom.ai/automate/deelF32
Automate Deel without code | axiom.ai
axiom.ai/automate/workloadF34
Workload automation with browser bots | axiom.ai

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