Docs benchmark

Can agents use your docs?

Run the benchmark on any public docs site and see whether an agent can find the right page, read clean text, and follow the instructions without guesswork.

171 tracked docs7 benchmark categories80 average benchmark scoreAFDocs-informed scoring

Try one of these public docs URLs:

We run the crawl here first, then open the full report with scores, failed checks, and next fixes.
Leaderboard

The docs benchmark leaderboard.

Browse public benchmark reports, compare category scores, and open the full breakdown for each docs site.

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Categories7 tracked segments

Showing 25 of 171 matching docs.

Why it matters

Docs quality now affects AI usability.

This is not a vanity score. It measures whether an agent can discover, read, and act on your documentation.

02

Docs quality now affects activation

Agent-readable docs shape implementation speed, support load, and whether a product feels trustworthy during evaluation.

03

Benchmarks make docs quality comparable

A shared benchmark gives teams a concrete way to compare docs quality, spot weak areas, and track improvements over time.

Methodology

How the benchmark scores docs.

This scoring model is informed by AFDocs and adapted into a public benchmark teams can inspect, compare, and rerun.

Checks for llms.txt, sitemaps, and a clear public docs entry point.

  • LLMS TXT existsAn llms.txt file is published at a predictable docs path.
  • LLMS TXT is structuredThe llms.txt file follows a format agents can parse quickly.
  • Docs entry point is obviousThe primary docs home is easy to identify.
  • Docs sitemap existsThe crawl map is present and reachable.
  • Key docs links resolveThe sampled entry links resolve without dead ends.
  • Public indexing path is stableAgents can stay on a stable public path while crawling the docs.
Built by DocsAlot

Need help improving the score?

DocsAlot helps teams improve help centers, developer docs, API docs, and CLI docs so they are easier for humans to use and easier for agents to read.