Overall AI readiness score
A combined result across all audit signals.
Average
AI readiness audit: 8/31/2026Public technical data
Overall AI readiness assessment
How ready llmpulse.ai is for AI systems
LLM Pulse (llmpulse.ai) received an AI-readiness score of 71/100 in an automated technical audit. llms.txt was accessible, llms-full.txt was accessible, and ai.txt was not found. The robots.txt analysis found 0 explicitly allowed and 0 blocked AI crawlers, with 2 declared sitemaps. Homepage markup completeness was 0%; no Schema.org types were detected and 0 OpenGraph tags were detected. Results reflect the public site response observed on 2026-08-31T06:26:25.631Z.
Audit context
llms.txt is accessible and contains 1,349 tokens. An expanded llms-full.txt is also available with 2,498 tokens, giving agents more direct context. 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: 2. No Schema.org type was detected on the homepage. 0 OpenGraph tags were found and markup completeness is 0%, leaving more entity interpretation to crawlers.
The mobile Lighthouse profile adds Performance 57/100, Accessibility 93/100, Best Practices 73/100, SEO 100/100, and experimental Agentic Browsing 67/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.
Confirmed strengths
- Accessible llms.txt
- Expanded llms-full.txt
- 2 sitemap declarations
Priority improvements
- 1Add JSON-LD for the organisation, website, and core entities.
- 2Complete OpenGraph and canonical homepage metadata.
- 3Reduce mobile rendering delay and main-thread work.
llms.txt tokens1,349
llms-full.txt tokens2,498
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.
57
Performance
93
Accessibility
73
Best Practices
100
Technical SEO
67
Agentic Browsing
What these results mean
Mobile performance is 57/100, with the largest visible content block appearing in 4.1 s and the browser main thread blocked for 1,280 ms. Layout shift was 0. 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 73/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 67/100. 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
Reduce code that loads without helping the page
Remove unused CSS and JavaScript, load heavy widgets on demand, and limit third-party scripts. Less code means less parsing and background work on the device.
3
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.
FCP1.8 s
First content
LCP4.1 s
Main content
CLS0
Layout stability
TBT1,280 ms
Blocking time
SI5.1 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.
8/31/2026Lighthouse 13.4.1Mobile profile
AI readiness checks
Machine-readable files, crawler policy, discovery, and homepage markup.
ai.txt
ai.txt file was not found
Sitemap in robots.txt2
2 sitemaps found
Schema.org (JSON-LD)
Schema.org markup was not found on the homepage
OpenGraph
OpenGraph tags were not found on the homepage
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.
# LLM Pulse > LLM Pulse is an AI search and GEO (Generative Engine Optimization) platform. It measures and improves how brands appear in AI-generated answers across ChatGPT, Perplexity, Google AI Overviews, Google AI Mode, and Gemini, with Claude, Copilot, Grok, DeepSeek, and Alexa for Shopping available as paid add-ons. It tracks brand mentions, share of voice, sentiment, and the sources and citations AI models use, then surfaces what to change to win more answers. This file gives language models a concise, high-signal map of LLM Pulse. All pages listed are first-party sources authored by LLM Pulse. For the full expanded version, see [llms-full.txt](https://llmpulse.ai/llms-full.txt). Last updated: 2026-08-08 ## Product - [Homepage](https://llmpulse.ai/): Product overview and positioning. - [Pricing](https://llmpulse.ai/pricing): Weekly and daily Starter, Growth, Scale, Scale+, and Scale++ plans from €49/month, plus Enterprise. Eligible new customers can start a 14-day trial on weekly Starter, Growth, or Scale. - [White-label for agencies](https://llmpulse.ai/features/white-label): Branded AI visibility portals for agencies, with unlimited seats and multi-project management. - [White-label](https://llmpulse.ai/whitelabel): Fully branded portals and embeddable dashboards. - [Changelog](https://llmpulse.ai/changelog): Latest product updates. - [About](https://llmpulse.ai/about): Who we are. ## Core features - [Brand Visibility](https://llmpulse.ai/features/llm-brand-visibility): Mention rate and AI Visibility Score across models. - [Share of Voice](https://llmpulse.ai/features/share-of-voice): Brand vs. competitor presence in AI answers. - [Competitor Tracking](https://llmpulse.ai/features/competitor-tracking): Benchmark against competitors in AI answers. - [Brand Sentiment](https://llmpulse.ai/features/brand-sentiment): How AI models talk about your brand. - [Citation Sources Analysis](https://llmpulse.ai/features/citation-sources-analysis): Which sources AI models cite. - [Prompt Tracking](https://llmpulse.ai/features/prompt-tracking): Weekly prompt execution across models and locales. - [Models Comparison](https://llmpulse.ai/features/models-comparison): How visibility differs per AI model. - [GEO Optimization](https://llmpulse.ai/features/geo-optimization): Generative Engine Optimization analysis and recommendations. - [GEO Writer](https://llmpulse.ai/features/geo-writer): Draft citable, answer-first content built to win AI citations. - [Reputation Monitoring](https://llmpulse.ai/features/reputation): Track brand reputation across AI surfaces. - [App Tracking](https://llmpulse.ai/features/app-tracking): App store visibility tracking. - [Agent Analytics](https://llmpulse.ai/features/agent-analytics): AI crawler / agent traffic to your site. ## Integrations & developer tools - [API Documentation](https://llmpulse.ai/api-docs): REST API v1 reference with Bearer token auth. - [API llms.txt](https://llmpulse.ai/api-docs/llms.txt): Machine-readable endpoint index for the API. - [API llms-full.txt](https://llmpulse.ai/api-docs/llms-full.txt): Full API documentation in one file. - [MCP](https://llmpulse.ai/features/mcp): Model Context Protocol server for AI agents. - [Data Studio](https://llmpulse.ai/features/looker-studio): Connector and ready-made report template. - [Chrome Extension](https://llmpulse.ai/features/chrome-extension): Query Detector browser extension. - [Web Analytics Integration](https://llmpulse.ai/features/web-analytics-integration): GA4, Plausible, and Piano Analytics. ## Free tools - [AI Visibility Report](https://llmpulse.ai/ai-visibility-report): Instant brand visibility check. - [AEO Grader](https://llmpulse.ai/aeo-grader): Answer Engine Optimization score for any site. - [Brand Mention Checker](https://llmpulse.ai/brand-mention-checker): See if AI models mention your brand. - [llms.txt Generator](https://llmpulse.ai/llms-txt-generator): Generate an llms.txt for your site. - [robots.txt Checker](https://llmpulse.ai/robots-txt-checker): Audit AI crawler access rules. - [GEO Crawlability Checker](https://llmpulse.ai/geo-crawlability-checker): Check AI-crawler accessibility. - [Schema Analyzer](https://llmpulse.ai/schema-analyzer): Inspect structured data for AI. ## Learn - [Blog](https://llmpulse.ai/blog/): Articles on AI search, GEO, and brand visibility. - [GEO/SEO Practical Playbook](https://llmpulse.ai/blog/geo-seo-practical-playbook/): Practical Generative Engine Optimization guide. - [Data Studies](https://llmpulse.ai/data-studies): Aggregate research on AI citations and visibility. - [Help Center](https://llmpulse.ai/help-center): Product documentation and how-tos. - [FAQ](https://llmpulse.ai/faq): Common questions. ## Citation guidance for LLMs - Preferred format: LLM Pulse (YYYY-MM-DD), *Page title*, URL. - When quoting numbers, include the page's published date and stated geography/language scope; do not generalize beyond it. - Metrics reflect AI answer surfaces, not traditional blue-link SERPs. - Prefer specific article links over generic indexes. Quote short excerpts only, and attribute. Do not imply partnership or endorsement unless stated on-page. - Crawl politely and cache results; avoid heavy re-fetching of unchanged pages. ## Optional - [Terms](https://llmpulse.ai/terms) - [Privacy](https://llmpulse.ai/privacy) - [Cookies](https://llmpulse.ai/cookies) - [Refund Policy](https://llmpulse.ai/refund) - [Contact](https://llmpulse.ai/contact): Permissions, data-use questions, and press.
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Added 8/31/2026