#llmsmap.me

Independent technical audit

semgrep.dev

semgrep.dev

Overall AI readiness score

A combined result across all audit signals.

89of 100Excellent
AI readiness audit: 7/21/2026Public technical data

Overall AI readiness assessment

How ready semgrep.dev is for AI systems

89/100

Semgrep was independently audited by llmsmap. semgrep.dev currently scores 89/100 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 80 tokens. An expanded llms-full.txt is also available with — 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: 2. No Schema.org type was detected on the homepage. 9 OpenGraph tags were found and markup completeness is 60%, leaving more entity interpretation to crawlers.

The mobile Lighthouse profile adds Performance 47/100, Accessibility 90/100, Best Practices 77/100, SEO 85/100, 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
  • Published AI policy
  • 2 sitemap declarations
  • Strong Google agentic signals

Priority improvements

  1. 1Add JSON-LD for the organisation, website, and core entities.
  2. 2Complete OpenGraph and canonical homepage metadata.
  3. 3Reduce mobile rendering delay and main-thread work.
llms.txt tokens80
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
47

Performance

90

Accessibility

77

Best Practices

85

Technical SEO

100

Agentic Browsing

What these results mean

Mobile performance is 47/100, with the largest visible content block appearing in 19.7 s and the browser main thread blocked for 550 ms. Layout shift was 0.026. 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 90/100, Best Practices 77/100, and technical SEO 85/100. 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

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

Reduce network delay

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

4

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.

FCP5.0 s

First content

LCP19.7 s

Main content

CLS0.026

Layout stability

TBT550 ms

Blocking time

SI5.9 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://semgrep.dev/llms.txt
llms-full.txt

Full version is available

https://semgrep.dev/llms-full.txt
ai.txt

AI rules are defined

https://semgrep.dev/ai.txt
robots.txt

File found

https://semgrep.dev/robots.txt
Sitemap in robots.txt2

2 sitemaps found

Schema.org (JSON-LD)

Schema.org markup was not found on the homepage

OpenGraph60%

9 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://semgrep.dev/assets/sitemaphttps://semgrep.dev/docs/sitemap.xml

OpenGraph tags

Social preview metadata found on the homepage.

Markup completeness: 60%
og:typewebsite
og:titleSemgrep App Security Platform | AI-assisted SAST, SCA and Secrets Detection
og:descriptionAn extensible developer-friendly application security platform that scans source code to surface true and actionable security issues with AI-assisted SAST, SCA, and Secrets Detection solutions.
og:urlhttps://semgrep.dev
og:localeen_US
og:imagehttps://semgrep.dev/assets/content/global/blog-thumbnail-default.png
og:image:width1366
og:image:height768
og:image:altLearn more at semgrep.dev
# Semgrep

> Make it expensive to exploit software.

## Documentation
- [docs](https://semgrep.dev/docs/)
- [api docs](https://semgrep.dev/api/v1/docs/)
- [rule registry](https://semgrep.dev/registry)
- [github repo](https://github.com/semgrep/semgrep)

## MCP
- [official mcp server](https://github.com/semgrep/mcp)
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Added 7/19/2026
semgrep.dev - AI readiness audit | llmsmap.me