AgentLint.io

Comprehensive analysis for the agentic web.

We check 20+ data points across five categories to ensure your content is optimized for consumption by Large Language Models and AI Agents.

Crawler Access

Verify robots.txt, sitemap accessibility, and bot detection rules specifically for AI scrapers like GPTBot.

Markdown & llms.txt

Ensure clean markdown conversion paths and properly formatted llms.txt for standardized agent discovery.

Structured Data

Validate JSON-LD and Schema.org markup depth to help agents understand entities and relationships.

Rendering Analysis

Test how headless browsers render your dynamic content and identify heavy JS payloads that block parsing.

Token Efficiency

Optimize content density to reduce token usage costs for consumers of your data.

Cut through the noise.

Modern websites are bloated with div soup. AI agents spend 80% of tokens parsing navigation, footers, and ads instead of your core content.

Standard Web Page24k Tokens
Agent Optimized4k Tokens
raw_output.htmlBad
<div class="wrapper">
  <div class="ad-banner-top">...</div>
  <nav class="mega-menu">
    <ul><li>Home</li>...</ul>
  </nav>
  <div class="content-wrapper">
    <div class="sidebar-left">...</div>
    <article>
      <h1>The meaningful content</h1>
    </article>
    <div class="cookie-consent">...</div>
  </div>
</div>
agent_ready.mdOptimized
# The meaningful content

Here is the core information without any distractions.

## Key Takeaways
* Point 1
* Point 2

[No nav] [No ads] [No scripts]
1

Paste URL

Input your landing page or documentation URL.

2

Get Audit

Receive a detailed breakdown of crawler blocks and token waste.

3

Fix Code

Implement our suggestions to boost your RAG visibility.

Integrate into your CI/CD.

Don't let regressions slip into production. Use our GitHub Action to block PRs that break agent compatibility.

  • Zero-config setup for most frameworks
  • Blocks PRs with low agent scores
  • Detailed reports in PR comments
name: AgentLint Check
on: [push]

jobs:
  audit:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Run AgentLint
        uses: agentlint/action@v1
        with:
          token: ${{ secrets.AGENTLINT_KEY }}
          min-score: 85

Simple, transparent pricing

Start for free, scale when you need automation.

MonthlyAnnualSave ~17%
Hobby
$0
  • 2 websites
  • 5 audits per site / month
  • Score + category overview

Current plan

Most Popular
Pro
$29/mo

billed monthly

  • 20 websites
  • Unlimited audits
  • Full detailed reports
  • Site crawl (up to 10 pages)
  • CI/CD Integration
  • Historical trend data
Agency
$99/mo

billed monthly

  • Everything in Pro
  • 100 websites
  • Unlimited audits
  • Site crawl (100+ pages)
  • Team seats
  • White-label reports
  • Need more? Contact sales

Frequently asked questions

Why does my site need to be agent-ready?
AI agents (like ChatGPT, Perplexity, and custom bots) are increasingly used to discover information. If your site blocks them or provides messy data, you lose traffic and visibility in the AI era.
What is llms.txt?
It's a proposed standard file (similar to robots.txt) that tells Large Language Models specifically where to find the most relevant, markdown-formatted content on your website.
Does this impact SEO?
Yes. While traditional SEO focuses on Google Search, "Agent SEO" focuses on being cited by AI models. Improving structured data and crawlability helps both.

Ready to optimize?

Join 10,000+ developers building for the agentic web.