Overall AI readiness score
A combined result across all audit signals.
Excellent
AI readiness audit: 7/21/2026Public technical data
Overall AI readiness assessment
How ready comet.com is for AI systems
Opik Documentation was independently audited by llmsmap. comet.com currently scores 75/100 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 157 tokens. An expanded llms-full.txt is also available with 157 tokens, giving agents more direct context. A separate ai.txt policy is published.
robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 3. 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 51/100, Accessibility 94/100, Best Practices 96/100, SEO 92/100, 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
- Published AI policy
- 3 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 tokens157
llms-full.txt tokens157
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.
51
Performance
94
Accessibility
96
Best Practices
92
Technical SEO
67
Agentic Browsing
What these results mean
Mobile performance is 51/100, with the largest visible content block appearing in 10.8 s and the browser main thread blocked for 500 ms. Layout shift was 0.004. 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 94/100, Best Practices 96/100, and technical SEO 92/100. 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
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
Improve interface contrast and readability
Increase contrast for text, states, and interactive controls so both people and visual agents can distinguish content from actions and supporting labels.
FCP3.0 s
First content
LCP10.8 s
Main content
CLS0.004
Layout stability
TBT500 ms
Blocking time
SI7.0 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.
7/21/2026Lighthouse 13.4.0Mobile profile
AI readiness checks
Machine-readable files, crawler policy, discovery, and homepage markup.
Sitemap in robots.txt3
3 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.
# Opik Documentation > Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards. ## Instructions for AI Agents - For clean Markdown of any page, append `.md` to the page URL - For section-specific indexes, append `/llms.txt` to any section URL - For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://www.comet.com/docs/opik/_mcp/server ## Versions - [Latest](https://www.comet.com/docs/opik/latest/llms.txt) (default) - [v1](https://www.comet.com/docs/opik/v1/llms.txt)
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Added 7/19/2026