Free preview scan
Run a lightweight first pass on a submitted URL to get an initial signal about how the site appears to AI agents, including obvious strengths and gaps.
fedt.ai checks how ready a public website is for AI agents, then offers a free preview scan and a paid Deep Scan and Fix Pack with prioritized fixes.
fedt.ai is an AI agent readiness check for public websites. It helps site owners see how discoverable, understandable, and usable their site appears to AI agents by scanning public signals such as page metadata, crawl files, visible structure, and agent-facing context.
The product is built around a two-step experience: a free preview scan that gives a quick read, and a paid Deep Scan and Fix Pack that expands the evidence set into a prioritised implementation plan. The output is designed to show what agents can read, miss, misunderstand, or fail to act on, rather than offering a generic AI verdict.
Run a lightweight first pass on a submitted URL to get an initial signal about how the site appears to AI agents, including obvious strengths and gaps.
Inspect public signals such as page titles, metadata, navigation, crawl files, visible structure, structured data, docs, and public endpoints to build an evidence-backed report.
Surface a score and readiness breakdown across Discovery, Structure, Affordance, and MCP readiness, plus a small penalty for active bot blocking.
Produce a deeper report that highlights what agents can and cannot understand today, the main blockers, and which fixes matter now versus later.
Generate copy-paste prompts for tools such as Cursor, Replit, Claude, Codex, Lovable, or a developer team, along with a fedt.md handoff file.
Show a report format that includes an executive summary, evidence citations, blockers, a phased action surface, and an MCP recommendation.
Useful for marketers or founders who want to know whether an existing site is easy for AI agents to discover and summarize before investing in deeper changes.
Helpful for product teams that want a structured read on whether docs, metadata, and public navigation give agents enough context to understand the product.
Relevant for builders planning agent-facing workflows who need to see whether public endpoints, structured data, or other machine-readable clues are visible today.
Useful when you want a practical implementation plan, not just a score, because the paid report includes prioritised fixes, prompts, and a handoff file.
You paste a product URL and run a free preview scan. The site then shows a score and a surface-level view of what AI agents can discover, understand, and use before you decide whether to run the deeper scan and Fix Pack.
The site says the full report covers public signals such as page titles and metadata, navigation, crawl and discovery files like robots.txt, sitemap.xml, and llms.txt, visible content structure, structured data, public docs, and any public APIs or agent-facing interfaces it can observe.
The full report is presented as a five-step workflow on the site: run a free check, review the preview scan, unlock the Deep Scan and Fix Pack, then use the prioritised fixes and implementation prompts it generates.
The pricing page at the provided URL currently returns a 404, so the site only clearly confirms the one-time $19 Fix Pack price on the home page. No broader plan structure is visible in the collected content.
The report is based on public website signals at the time of the scan. It is not described as a private internal code audit, and it does not crawl or index sites broadly.
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