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fedt.ai

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

AI agent readiness scanning for public websites

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.

Core capabilities

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.

Public-signal analysis

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.

Multi-factor readiness scoring

Surface a score and readiness breakdown across Discovery, Structure, Affordance, and MCP readiness, plus a small penalty for active bot blocking.

Prioritised fix plan

Produce a deeper report that highlights what agents can and cannot understand today, the main blockers, and which fixes matter now versus later.

Implementation handoff

Generate copy-paste prompts for tools such as Cursor, Replit, Claude, Codex, Lovable, or a developer team, along with a fedt.md handoff file.

Structured report output

Show a report format that includes an executive summary, evidence citations, blockers, a phased action surface, and an MCP recommendation.

When teams would use fedt.ai

  • Check a live marketing site

    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.

  • Audit product documentation and public structure

    Helpful for product teams that want a structured read on whether docs, metadata, and public navigation give agents enough context to understand the product.

  • Assess readiness for agent interaction

    Relevant for builders planning agent-facing workflows who need to see whether public endpoints, structured data, or other machine-readable clues are visible today.

  • Turn findings into an action plan

    Useful when you want a practical implementation plan, not just a score, because the paid report includes prioritised fixes, prompts, and a handoff file.

Pros and Cons

Pros

  • Grounded in observable site signals rather than a generic AI assessment.
  • Covers several practical readiness dimensions, including discovery, structure, affordance, and MCP readiness.
  • Provides a free preview before the paid Deep Scan and Fix Pack.
  • Turns findings into prioritised fixes and copy-paste prompts that can be handed to a developer or AI coding tool.
  • Includes evidence references so readers can see what the report is based on.

Cons

  • The pricing page at the provided URL is currently unavailable, so the broader pricing structure is unclear from the collected sources.
  • The report only reflects publicly visible signals, so it cannot account for private systems or undocumented features that are not exposed on the site.
  • There is no visible integration catalog or supported ecosystem information in the collected material.

FAQ

How does the free scan work?

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.

What does the report evaluate?

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.

What do I get if I pay for the Fix Pack?

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.

What is the pricing?

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.

Are there limitations to the report?

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.

Quick Facts

Category
AI agent readiness scanning
Primary output
Free preview scan plus paid Deep Scan and Fix Pack
Workflow
Submit a URL, review preview results, then unlock the deeper report and fix pack
Price shown on site
$19 one-time for the Fix Pack
Source domain
fedt.ai
Report basis
Public website signals and visible agent-facing context