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 microsoft.github.io is for AI systems
GenAIScript was independently audited by llmsmap. microsoft.github.io currently scores 54/100 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 614 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 was not found, so explicit crawler policy could not be confirmed. 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 61/100, Accessibility 96/100, Best Practices 81/100, SEO 92/100, and experimental Agentic Browsing 50/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.
Confirmed strengths
- Accessible llms.txt
Priority improvements
- 1Add llms-full.txt for richer first-party context.
- 2Publish robots.txt with explicit search and AI crawler rules.
- 3Declare the current sitemap.xml in robots.txt.
- 4Add JSON-LD for the organisation, website, and core entities.
llms.txt tokens614
llms-full.txt tokens367,614
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.
61
Performance
96
Accessibility
81
Best Practices
92
Technical SEO
50
Agentic Browsing
What these results mean
Mobile performance is 61/100, with the largest visible content block appearing in 7.3 s and the browser main thread blocked for 0 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 96/100, Best Practices 81/100, and technical SEO 92/100. The experimental Agentic Browsing category scored 50/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.
1
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.
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
Clarify search and canonical signals
Verify unique titles and descriptions, crawlability, canonicals, descriptive link text, and language relationships. This reduces ambiguity for search engines and AI systems selecting a page.
FCP5.0 s
First content
LCP7.3 s
Main content
CLS0
Layout stability
TBT0 ms
Blocking time
SI6.3 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.
llms-full.txt
Full version was not found
ai.txt
ai.txt file was not found
robots.txt
robots.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
OpenGraph0%
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
# GenAIScript > GenAIScript is a JavaScript/TypeScript library and environment to build productive script using LLMs. ## Markdown Documentation All pages of the documentation have a markdown route by adding '.md' to the URL. For example, the markdown for https://microsoft.github.io/genaiscript/reference/scripts is at https://microsoft.github.io/genaiscript/reference/scripts.md ## Guidance for Code Generation - GenAIScript programs are meant to be executed through the genaiscript cli (https://www.npmjs.com/package/genaiscript). - When generating code for GenAIScript, always target TypeScript, Node.JS, ESM. Prefer await/async, keep it simple. - ambient types and definitions defined in "genaiscript.d.ts" are preloaded at runtime. you do not need to import them. - you keep the code simple, avoid exception handlers or error checking. - you add TODOs where you are unsure so that the user can review them - you use the global types in genaiscript.d.ts are already loaded in the global context, no need to import them. - save generated code in the "./genaisrc" folder with ".genai.mts" extension ## Documentation Sets - [Abridged documentation](https://microsoft.github.io/genaiscript/llms-small.txt): a compact version of the documentation for GenAIScript, with non-essential content removed - [Complete documentation](https://microsoft.github.io/genaiscript/llms-full.txt): the full documentation for GenAIScript - [Getting Started](https://microsoft.github.io/genaiscript/_llms-txt/getting-started.txt): Sequence of short tutorials on how to get started with GenAIScript - [Configuration](https://microsoft.github.io/genaiscript/_llms-txt/configuration.txt): Configure access to LLMs and other services - [Reference](https://microsoft.github.io/genaiscript/_llms-txt/reference.txt): full reference documentation (runtime and cli) - [Reference Scripts](https://microsoft.github.io/genaiscript/_llms-txt/reference-scripts.txt): full reference documentation for the runtime - [Reference CLI](https://microsoft.github.io/genaiscript/_llms-txt/reference-cli.txt): full reference documentation for the command line interface and Node.JS runtime - [Guides](https://microsoft.github.io/genaiscript/_llms-txt/guides.txt): Guides on various LLM programming topics ## Notes - The complete documentation includes all content from the official documentation - The content is automatically generated from the same source as the official documentation
Share or continue the analysis
Share this audit
Discuss with AI
Added 7/19/2026