Overall AI readiness score
A combined result across all audit signals.
Average
AI readiness audit: 7/21/2026Public technical data
Overall AI readiness assessment
How ready svelte.dev is for AI systems
svelte.dev was independently audited by llmsmap. svelte.dev currently scores 70/100 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 419 tokens. An expanded llms-full.txt is also available with 291,518 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: 0. No Schema.org type was detected on the homepage. 1 OpenGraph tags were found and markup completeness is 10%, leaving more entity interpretation to crawlers.
The mobile Lighthouse profile adds Performance 96/100, Accessibility 100/100, Best Practices 100/100, 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
- Expanded llms-full.txt
- Strong Google agentic signals
Priority improvements
- 1Declare the current sitemap.xml in robots.txt.
- 2Add JSON-LD for the organisation, website, and core entities.
- 3Complete OpenGraph and canonical homepage metadata.
llms.txt tokens419
llms-full.txt tokens291,518
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.
96
Performance
100
Accessibility
100
Best Practices
100
Technical SEO
100
Agentic Browsing
What these results mean
The mobile page renders efficiently; its largest visible content block appeared in 2.6 s.
Accessibility scored 100/100, Best Practices 100/100, 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.
FCP1.7 s
First content
LCP2.6 s
Main content
CLS0
Layout stability
TBT0 ms
Blocking time
SI1.7 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.
ai.txt
ai.txt file was not found
Sitemap in robots.txt
Sitemap is not declared in robots.txt
Schema.org (JSON-LD)
Schema.org markup was not found on the homepage
OpenGraph10%
1 OG tag 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
OpenGraph tags
Social preview metadata found on the homepage.
# Svelte Documentation for LLMs > Svelte is a UI framework that uses a compiler to let you write breathtakingly concise components that do minimal work in the browser, using languages you already know — HTML, CSS and JavaScript. ## Documentation Sets - [Abridged documentation](https://svelte.dev/llms-medium.txt): A shorter version of the Svelte and SvelteKit documentation, with examples and non-essential content removed - [Compressed documentation](https://svelte.dev/llms-small.txt): A minimal version of the Svelte and SvelteKit documentation, with many examples and non-essential content removed - [Complete documentation](https://svelte.dev/llms-full.txt): The complete Svelte and SvelteKit documentation including all examples and additional content ## Individual Package Documentation - [Svelte documentation](https://svelte.dev/docs/svelte/llms.txt): This is the developer documentation for Svelte. - [SvelteKit documentation](https://svelte.dev/docs/kit/llms.txt): This is the developer documentation for SvelteKit. - [Svelte CLI documentation](https://svelte.dev/docs/cli/llms.txt): This is the developer documentation for Svelte CLI. - [Svelte AI documentation](https://svelte.dev/docs/ai/llms.txt): This is the developer documentation for Svelte AI. ## Notes - The abridged and compressed documentation excludes legacy compatibility notes, detailed examples, and supplementary information - The complete documentation includes all content from the official documentation - Package-specific documentation files contain only the content relevant to that package - The content is automatically generated from the same source as the official documentation
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Added 6/21/2026
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