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Getting Started

Run your first audit, read the report, and fix findings in the order that moves your score most. Rendered from the canonical source in the repository: docs/getting-started.md

This walkthrough takes you from zero to a passing AX score: run your first audit, learn to read the report, and fix findings in the order that moves your score most.

1. Run your first audit

No install needed:

npx ax-audit https://your-site.com

You get a report like:

  AX Audit Report
  https://your-site.com

  ██████████████████████░░░░░░░░░░░░░░░░░░  56/100  Fair

  LLMs.txt (0/100)
    FAIL  /llms.txt not found
  ...

Three things to locate immediately:

  • The overall score and grade. 0–100, weighted across 14 checks. Grades: Excellent (≥90), Good (≥70), Fair (≥50), Poor (<50). The CLI exits 0 at Good or better — that is the CI gate.
  • Per-check scores. Each check is independent and scored 0–100. The weight of each check is in checks.md.
  • Findings. Every WARN/FAIL line carries a hint and a learnMoreUrl to a remediation guide with copy-pasteable fixes.

To see only what needs fixing:

npx ax-audit https://your-site.com --only-failures

2. Understand what you're optimizing

AI agents interact with your site differently than browsers: most don't execute JavaScript, they look for machine-readable discovery files, and they respect (or at least read) your declared crawler policy. The audit measures three layers — if you're new to the standards involved (llms.txt, A2A, MCP, RSL, Content Signals), read concepts.md first:

  1. Content — is there substance an agent can read, and can a browser agent act on it? (html-rendering, agent-operability, structured-data, seo-basics, content-negotiation)
  2. Access — can an agent actually retrieve it? (agent-access, ai-directives, http-hygiene, tls-https, crawl-efficiency)
  3. Discovery — can an agent find your machine-readable files? (robots-txt, llms-txt, http-headers, sitemap, meta-tags)
  4. Policy — what usage rights do you declare, and do they agree? (usage-policy, security-txt, rsl)
  5. Protocols — what can an agent call? (api-discovery, agent-card, mcp-discovery, agent-skills, auth-discovery)

Protocol checks are conditional: if your site has no API to describe and no MCP server, they report n/a and leave the score alone rather than counting as failures.

3. Fix in impact order

The fastest path from Fair to Good, by weight and typical effort:

Step Check Weight Typical effort
1 Verify server-rendered content 11% Free if you already render on the server; significant if you ship an SPA shell. Nothing else matters if an agent sees an empty page.
2 Confirm nothing blocks AI crawlers 9% 15 minutes in your WAF. Check agent-access first: your robots.txt may say one thing and your firewall another.
3 Configure robots.txt for the 12 core AI crawlers 9% 15 minutes; npx ax-init generates it
4 Name your buttons and label your inputs 7% Hours to days, and it is accessibility work you owed anyway
5 Check your page-level AI directives 6% 10 minutes. A stray nosnippet removes you from AI Overviews.
6 Add JSON-LD structured data 6% 1–2 hours
7 Create /llms.txt 5% 30 minutes — it is a Markdown file. Read the check's note on who actually fetches it first.

Steps 1 and 2 are the ones worth doing today. They are also the two most likely to be silently broken: a hydration-only page and a firewall rule are both invisible from inside the site.

The remaining checks (seo-basics, content-negotiation, usage-policy, http-hygiene, http-headers, security-txt, tls-https, sitemap, crawl-efficiency, rsl, meta-tags) are mostly configuration; the remediation guides give exact snippets for Nginx, Vercel, Netlify, and Express.

Re-run after each fix — all requests are cached per run, so audits are fast and cheap.

4. Lock in your progress with a baseline

Once you reach a score you're happy with, freeze it:

npx ax-audit https://your-site.com --save-baseline .ax-baseline.json
git add .ax-baseline.json && git commit -m "chore: AX baseline"

From then on, compare every run against it:

npx ax-audit https://your-site.com --baseline .ax-baseline.json --fail-on-regression 5

This catches drift you didn't cause — a CDN toggle, a WAF rule, a header dropped in a refactor. Wire it into CI with the recipes in ci.md.

5. Look at the informational checks

Four checks report findings without affecting your score yet (they will in v4.0): content-negotiation, rsl, agent-access, crawl-efficiency. Treat them as the early-warning lane — they cover the newest standards, and fixing them now means v4.0 changes nothing for you.

The one to check first is agent-access: it detects the failure mode you cannot see — your robots.txt allows GPTBot while your WAF returns it a 403:

npx ax-audit https://your-site.com --checks agent-access

Common first-run questions

  • "My score seems harsh." The audit measures the AI-agent surface, not site quality. A beautiful SPA with no llms.txt, no structured data, and an empty #root div is genuinely poor AX — that's the point of the tool.
  • "A check crashed / network error." Transient failures retry automatically (--retries, default 2). For slow staging environments raise --timeout.
  • "Which findings are safe to ignore?" See the FAQ — notably the agent-access verified-bots caveat, and the checks resting on draft specifications, which never affect your score.

Next steps

  • checks.md — exact scoring of all 26 checks, with the weight table
  • concepts.md — the AX standards landscape explained
  • cli.md — every flag · ci.md — CI recipes · api.md — programmatic use
  • ax-init — generates most of the files this tool audits