Score Index › dbt Labs
This site
60/100
Average across all scans
41/100
AI Search Ready threshold
90/100
Gap to close
30 pts
Score breakdown
Agent Permissions
6/7 checks passed
Content Discoverability
3/5 checks passed
Structured Data
2/5 checks passed
Pricing Transparency
4/4 checks passed
Agent Infrastructure
2/11 checks passed
Trust & Identity
5/5 checks passed
Issues found
No Content-Signal header
No Content-Signal header. AI systems have to guess whether they're allowed to use your content for training, search, or as agent input. Declaring your policy proactively builds trust with AI platforms.
Fix: Add a Content-Signal HTTP response header to tell AI systems your content permissions: Content-Signal: ai-train=yes, search=yes, ai-input=yes In Next.js (next.config.js): headers: async () => [{ source: '/(.*)', headers: [{ key: 'Content-Signal', value: 'ai-train=yes, search=yes, ai-input=yes' }] }] This header is part of the emerging Content Signals standard (contentsignals.org) adopted by Cloudflare and others. It declares explicitly what AI can do with your content.
No llms.txt found
No llms.txt found. This standard (like robots.txt but for LLMs) tells AI exactly what to use and how to describe you. Less than 5% of sites have it.
Fix: Create a plain text file at /llms.txt. Minimum: # [Your Company] > [One sentence: what you do and who you serve] ## What we do [2–3 sentences] ## Key pages - /pricing , Plans and pricing - /docs , API documentation Use Faro's llms.txt Generator to build a complete version automatically.
No HTTP Link discovery header
No HTTP Link header advertising discovery files. AI agents that don't know to look for llms.txt won't find it. A Link header in the HTTP response signals discovery files proactively , before the agent even reads the page.
Fix: Add a Link header to your HTTP responses pointing to your discovery files: Link: </llms.txt>; rel="ai-content", </sitemap.xml>; rel="sitemap" In Next.js (next.config.js): headers: async () => [{ source: '/(.*)', headers: [{ key: 'Link', value: '</llms.txt>; rel="ai-content", </sitemap.xml>; rel="sitemap"' }] }] This is the HTTP equivalent of a signpost , an agent making its first request sees where to find your llms.txt immediately.
JSON-LD structured data
No JSON-LD schema. Agents have to guess your business details from unstructured text , they often get it wrong.
Fix: Add a JSON-LD script block to your homepage <head>. Use Faro's AI Schema Creator to generate the right schema for your business type.
sameAs entity links (Wikidata / LinkedIn / Crunchbase)
No sameAs links. Without them, AI agents can't verify who you are across Wikidata, LinkedIn, and Crunchbase , a key trust gap.
Fix: Add a sameAs array to your Organization schema: "sameAs": [ "https://linkedin.com/company/yourcompany", "https://www.crunchbase.com/organization/yourcompany", "https://www.wikidata.org/wiki/Q..." ]
What's working
robots.txt exists and accessible
GPTBot (ChatGPT) allowed
ClaudeBot (Anthropic) allowed
PerplexityBot allowed
What about your site?
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What the Faro score measures
The Faro AI readiness score tells you how well an AI agent — acting on behalf of a buyer — can navigate, understand, and evaluate a business. A score of 80+ means the site is genuinely AI-navigable. Below 40 means key signals are missing and the site risks being skipped during agent evaluations.
The scan checks six categories: agent permissions (robots.txt, GPTBot, ClaudeBot), discoverability (sitemap, llms.txt, canonical), structured data (JSON-LD, schema markup), pricing transparency, agent infrastructure (API docs, agents.json), and content readability. Each category contributes to the total score of 100.
The average score across all sites Faro has scanned is 41/100. Even well-resourced companies frequently block AI crawlers, omit structured data, or serve pricing in formats that agents cannot parse. These are fixable gaps — and the Faro scan tells you exactly where to start.