Independent technical audit

bertrand-bichat.github.io

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 bertrand-bichat.github.io is for AI systems

83/100

Bienvenue sur le site web professionel de Bertrand Bichat was independently audited by llmsmap. bertrand-bichat.github.io currently scores 83/100 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 283 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. The homepage exposes Schema.org types LocalBusiness; 7 OpenGraph tags were found and markup completeness is 90%.

The mobile Lighthouse profile adds Performance 90/100, Accessibility 93/100, Best Practices 92/100, 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
1 sitemap declaration
Schema.org: LocalBusiness
Complete social metadata

Priority improvements

1Add llms-full.txt for richer first-party context.

llms.txt tokens283

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.

Mobile · Lighthouse

Performance

Accessibility

Best Practices

100

Technical SEO

Agentic Browsing

What these results mean

The mobile page renders efficiently; its largest visible content block appeared in 3.0 s.

Accessibility scored 93/100, Best Practices 92/100, 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.

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.

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.

Reduce network delay

Improve server response time, remove unnecessary redirects and repeat downloads, and use compression, caching, and selective preconnect hints.

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.

FCP2.7 s

First content

LCP3.0 s

Main content

CLS0

Layout stability

TBT0 ms

Blocking time

SI2.9 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.txt

File found and accessible

https://bertrand-bichat.github.io/llms.txt

llms-full.txt

Full version was not found

ai.txt

ai.txt file was not found

robots.txt

File found

https://bertrand-bichat.github.io/robots.txt

Sitemap in robots.txt1

1 sitemap found

llms.txt in robots.txt

References: Allow: /llms.txt

Schema.org (JSON-LD)

Types: LocalBusiness

OpenGraph90%

7 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.

https://bertrand-bichat.github.io/sitemap.xml

OpenGraph tags

Social preview metadata found on the homepage.

Markup completeness: 90%

og:titleDéveloppeur web fullstack Ruby on Rails - Bertrand Bichat EI

og:typewebsite

og:urlhttps://bertrand-bichat.github.io/

og:imageimg/miniature.jpg

og:descriptionDéveloppeur web fullstack sur le framework Ruby on Rails depuis 4 années, je travaille en freelance sur Marseille ou à distance. Je fais principalement des SaaS, CRM et ERP.

og:site_namePortfolio - Bertrand Bichat EI

og:localefr_FR

Schema.org markup

Structured entities and properties exposed on the homepage.

Types found: 1 · Properties: 4

LocalBusiness

nameBertrand Bichat

urlhttps://bertrand-bichat.github.io/

imagehttps://bertrand-bichat.github.io/img/profile_with_bg.png

address{"@type":"PostalAddress","addressLocality":"Marseille","addressCountry":"France"}

# Bienvenue sur le site web professionel de Bertrand Bichat

> Développeur web full stack depuis mars 2020, basé à Marseille en France.
Spécialisé sur la conception de SaaS en monolithe utilisant le framework Ruby on Rails.
Ici, vous trouverez des informations sur son ses compétences, ses réalisations, ses avis clients.

## Liens utiles du site

- [Accueil, compétences, avis clients](https://bertrand-bichat.github.io/)
- [Portfolio](https://bertrand-bichat.github.io/portfolio)
- [Mentions légales](https://bertrand-bichat.github.io/legals)
- [Sitemap](https://bertrand-bichat.github.io/sitemap.xml)

## Liens utiles externes

- [Prendre un rendez-vous](https://calendly.com/bertrand-bichat/rdv-gratuit)
- [Linktr.ee (tous mes réseaux pro)](https://linktr.ee/bertrand.bichat)
- [Medium](https://medium.com/@bertrand.bichat)
- [GitHub](https://github.com/Bertrand-Bichat)
- [LinkedIn](https://www.linkedin.com/in/bertrand-bichat)
- [Profil Malt](https://www.malt.fr/profile/bertrandbichat)

## Optionnel

> N'hésitez pas à le contacter pour toute question ou collaboration à cette adresse mail : bertrand.bichat@gmail.com

---

Share or continue the analysis

Share this audit

Discuss with AI

Added 7/19/2026