One-page decision brief
Score breakdown, top risks and the first actions to share with a decision-maker.
AI Audit
Measure whether AI systems can access, interpret and discover your public content, with evidence from live crawler probes, page structure, policy files and discovery signals.
Best for sites that want to understand whether public pages are fetchable by bots such as GPTBot, ChatGPT-User, Google-Extended, ClaudeBot, PerplexityBot and CCBot.
Quick: a one-page executive brief. Full: crawler evidence, all tracked bot policies, content diagnostics and a prioritized implementation plan.
Run a free scan to see the AI readiness score, top findings and next actions here...
Score breakdown, top risks and the first actions to share with a decision-maker.
Executive summary plus bot-by-bot evidence, HTML diagnostics, discovery checks and ordered remediation steps.
What makes the audit useful
We resolve wildcard and explicit rules for 12 search, training and user-triggered AI agents.
Live probes reveal when CDN, WAF or challenge behavior disagrees with the published policy.
We inspect initial HTML, headings, canonical/indexation, internal trust links, JSON-LD and discovery files.
What the audit checks
See how robots.txt shapes AI crawler access and where teams usually over-block themselves.
A practical guide to allowing public AI crawlers without turning the site into a free-for-all.
What llms.txt can and cannot do, and why it is not a replacement for robots.txt.
A short pre-launch checklist for teams that want discoverable public content.
A breakdown of the most common causes: homepage errors, bot blocking, missing files and ambiguity.
No. It checks crawlability signals, not ranking, retrieval quality, citation policy or model behavior.
No. robots.txt is the more established crawler control layer. llms.txt is best treated as supplementary guidance.
Not necessarily. The useful decision is intentional access, not blanket access or blanket blocking by default.