Overall AI readiness score
A combined result across all audit signals.
Excellent
AI readiness audit: 8/26/2026Public technical data
Overall AI readiness assessment
How ready heeb.ai is for AI systems
heeb was independently audited by llmsmap. heeb.ai currently scores 77/100 for AI readiness. The result combines AI-specific files, crawler policy, sitemap discovery, structured homepage data, and—when available—the mobile Google Lighthouse technical profile.
Audit context
llms.txt is accessible and contains 643 tokens. No accessible llms-full.txt was detected, so deeper context still has to be assembled from regular pages. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.
robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 1. No Schema.org type was detected on the homepage. 5 OpenGraph tags were found and markup completeness is 50%, leaving more entity interpretation to crawlers.
The mobile Lighthouse profile adds Performance 72/100, Accessibility 93/100, Best Practices 96/100, SEO 100/100, and experimental Agentic Browsing 100/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.
Confirmed strengths
- Accessible llms.txt
- 1 sitemap declaration
- Strong Google agentic signals
Priority improvements
- 1Add llms-full.txt for richer first-party context.
- 2Add JSON-LD for the organisation, website, and core entities.
- 3Complete OpenGraph and canonical homepage metadata.
- 4Reduce mobile rendering delay and main-thread work.
llms.txt tokens643
llms-full.txt tokens—
ai.txt
sitemap.xml
Google Lighthouse technical profile
A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.
72
Performance
93
Accessibility
96
Best Practices
100
Technical SEO
100
Agentic Browsing
What these results mean
Mobile performance is 72/100, with the largest visible content block appearing in 5.1 s and the browser main thread blocked for 0 ms. Layout shift was 0.002. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.
Accessibility scored 93/100, Best Practices 96/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 100/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.
1
Free the main thread and accelerate the first view
Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.
2
Optimise images and their loading order
Serve correctly sized modern formats, prioritise the primary visual, and lazy-load content below the first viewport.
3
Reduce network delay
Improve server response time, remove unnecessary redirects and repeat downloads, and use compression, caching, and selective preconnect hints.
4
Make controls unambiguous
Give buttons and links accessible names, associate labels with fields, and use ordered headings and semantic regions. The same structure helps screen readers and software agents understand actions.
FCP3.8 s
First content
LCP5.1 s
Main content
CLS0.002
Layout stability
TBT0 ms
Blocking time
SI3.8 s
Visual speed
Metric glossary
- FCP · First content
- When the first text or image appeared on screen.
- LCP · Main content
- When the largest visible element in the first viewport rendered.
- CLS · Layout stability
- How much content shifted unexpectedly while loading; lower is better.
- TBT · Blocking time
- How long the browser main thread could not respond quickly to input.
- SI · Visual speed
- How quickly the visible viewport filled with content.
8/26/2026Lighthouse 13.4.1Mobile profile
AI readiness checks
Machine-readable files, crawler policy, discovery, and homepage markup.
llms-full.txt
Full version was not found
ai.txt
ai.txt file was not found
Sitemap in robots.txt1
1 sitemap found
Schema.org (JSON-LD)
Schema.org markup was not found on the homepage
OpenGraph50%
5 OG tags found
AI bot access
Based on robots.txt analysis
GPTBotNot mentioned
OAI-SearchBotNot mentioned
ChatGPT-UserNot mentioned
Google-ExtendedNot mentioned
ClaudeBotNot mentioned
Claude-SearchBotNot mentioned
Claude-UserNot mentioned
BytespiderNot mentioned
CCBotNot mentioned
PerplexityBotNot mentioned
Perplexity-UserNot mentioned
Sitemaps
Declared discovery routes for crawlers and agents.
OpenGraph tags
Social preview metadata found on the homepage.
og:typewebsiteog:titleheeb | LLM Mentions APIog:descriptionLLM Mentions APIog:imagehttps://heeb.ai/og.pngog:urlhttps://heeb.ai/# heeb > AI SEO API allows developers to query and analyze multiple LLMs such as ChatGPT, Claude, Grok, and Perplexity with a single prompt. Get structured JSON responses containing each model's answer, its sources and citations, ranked brand mentions, per-model sentiment, and aggregate visibility and sentiment scores, so product, SEO, and research teams can measure AI visibility across models. ## Homepage - [heeb](https://heeb.ai/): heeb offers an AI SEO API to track brand mentions, sentiment, and visibility across top LLMs like ChatGPT and Perplexity. ## Integrations - [n8n | heeb](https://heeb.ai/integrations/n8n): Install the heeb community node in self-hosted n8n, connect an API key, and run brand visibility queries from a workflow. ## Blog - [Monitor AI visibility with n8n in five nodes | heeb](https://heeb.ai/blog/monitor-ai-visibility-with-n8n): Monitor AI visibility with n8n: install the Heeb node, import one workflow, and get a Slack message when AI models stop mentioning your brand. - [AI Search Visibility: A Practical Guide | heeb](https://heeb.ai/blog/ai-search-visibility-guide): Learn what AI search visibility measures, how AI answers use sources, and how to track brand mentions, citations, position, and sentiment. - [LLM Mentions API: heeb.ai Quick Walkthrough | heeb](https://heeb.ai/blog/llm-mentions-api-heeb-ai-quick-walkthrough): Learn how to integrate the heeb.ai LLM Mentions API into your workflow for automated brand visibility and sentiment tracking across AI models. - [Monitoring Brand Mentions Across LLMs | heeb](https://heeb.ai/blog/monitoring-brand-mentions-across-llms): LLMs shape brand discovery; monitor and optimize for AI visibility. - [Adapting SEO for Generative AI | heeb](https://heeb.ai/blog/adapting-seo-for-generative-ai): AI transforms SEO: 2025 trends, strategies, and case studies for visibility. - [Guide to llms.txt: What It Is and How It Works | heeb](https://heeb.ai/blog/guide-to-llmstxt-what-it-is-and-how-it-works): LLMs.txt: Markdown standard guiding LLMs to essential website content. - [AI and Data Analytics: Essential Insights | heeb](https://heeb.ai/blog/ai-and-data-analytics-essential-insights): AI revolutionizes data analytics with insights, trends, and ethical challenges for 2025. - [Top AI Tools for Marketing Analytics | heeb](https://heeb.ai/blog/top-ai-tools-for-marketing-analytics): AI transforms marketing analytics into predictive, real-time insights for better ROI. - [Top AI SEO Tools for Efficient Optimization | heeb](https://heeb.ai/blog/top-ai-seo-tools-for-efficient-optimization): AI revolutionizes SEO with automated tools and predictive analytics for future-proof strategies. - [Introducing heeb: The API for AI SEO and LLM Visibility Data | heeb](https://heeb.ai/blog/introducing-heeb-ai): Discover heeb, the API powering AI visibility and SEO automation. ## Contact - Website: [https://heeb.ai/](https://heeb.ai/) - Email: hello@heeb.ai - Company: heeb ## Last updated September 17th, 2026
Share or continue the analysis
Share this audit
Discuss with AI
Added 8/26/2026
Similar sites in the directory
Sites with a close AI-readiness score — compare how they set up llms.txt and markup.