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    agent-ready-api

    Agent Ready Api

    by Mark Lavercombe

    Score and optimize any website for AI agent-readability using the Agent Ready REST API.

    Updated Jun 2026
    0 installs

    Free

    Included in download

    • Downloadable skill package
    • Works with Claude Code, Cursor
    • 3 permissions declared
    • Instant install

    Sample input

    Run an Agent Ready scan on https://docs.example.com to see if it follows the llms.txt standard and Vercel spec.

    Sample output

    Scan complete for docs.example.com. Score: 82/100 (Rating: Good)

    • llms.txt: Found, but missing 'optional' section (Check L4 failed).
    • Vercel Spec: Pass (95/100).
    • Issue: Missing agent-permissions.json (Check C2). Full Report: https://agent-ready.dev/share/scan_01HXYZ...

    Screenshots

    About This Skill

    Optimize Your Site for AI Agents

    The Agent Ready skill allows developers to programmatically audit any public URL for "AI readiness." As the web shifts from human-centric to agent-centric browsing, this skill ensures your documentation and site structure are easily parsable by LLMs and autonomous agents.

    What it does

    • Comprehensive Auditing: Scans sites against 60+ benchmarks, including the Vercel Agent Readability Spec and llmstxt.org standards.
    • Protocol Validation: Checks for modern agent manifests like MCP server cards, agents.json, A2A, and NLWeb.
    • Technical Scoring: Provides automated scores (0-100) and categorical ratings (Excellent to Needs Improvement).
    • Remediation Guidance: Returns specific failure reasons and "how-to-fix" instructions for every failing check.

    Why use this skill?

    Prompting an AI to "look at my site" often results in surface-level feedback based on visual layout. This skill uses a specialized REST API to perform a deep structural crawl, looking for the specific invisible files and metadata that actual production agents (like Claude Code or GPT-4o) depend on. It provides a repeatable, data-driven score that you can track over time or integrate into CI/CD pipelines.

    The Output

    You receive a structured summary featuring an overall score, sub-scores for specific specifications (like llms.txt), a list of the highest-impact failing checks, and a shareable URL for a detailed visual dashboard.

    Use Cases

    • Validate llms.txt compliance for technical documentation sites
    • Audit site manifests like agents.json and MCP server cards
    • Identify structural issues preventing AI agents from crawling your site
    • Get actionable remediation steps to improve AI readability scores

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell
    Network Access
    Environment Variables

    Allowed Hosts

    agent-ready.dev
    example.com
    github.com

    File Scopes

    agent-ready-api/**

    Tags

    seo-for-ai
    web-scraping
    llms-txt
    mcp
    api-util
    Documentation

    Claude Code, Cursor, Windsurf, Aider, and any agent with shell access.

    Creator

    Mark Lavercombe

    Frequently Asked Questions

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