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  "markdown": "## What is agent readability?\n\nAgent readability is how easily AI agents — ChatGPT, Claude, Perplexity, Google Gemini, coding assistants, MCP clients — can discover, parse, and act on a website. It spans three surfaces: discovery files (`llms.txt`, `robots.txt`, sitemaps), structural signals (semantic headings, canonical links, structured data, markdown mirrors), and protocol manifests (MCP Server Cards, A2A Agent Cards, agents.json, agent-permissions.json).\n\n## Why does AI agent readability matter for SEO?\n\nAI agents crawl what loads cleanly and cite what parses correctly. The incentives are sharp: a [July 2025 Pew Research study](https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/) found users who encounter a Google AI Overview click on a source link only about 8% of the time — roughly half the rate of searches without an AI summary. Princeton’s [GEO study (KDD 2024)](https://arxiv.org/abs/2311.09735) measured that adding source citations to a page lifted its inclusion in AI answers by roughly 40%, with statistics and quotations close behind. Sites that score well get summarised accurately and referred qualified traffic; sites that score poorly get paraphrased (badly) or skipped entirely. Unlike traditional SEO, you don’t need to rank on page 1 — structured, citable content gets pulled even when organic rank is low.\n\n## What does the agent readability scanner check?\n\n-   **Vercel Agent Readability Spec** — 15 site-wide checks (llms.txt, robots.txt, sitemap.xml, sitemap.md, AGENTS.md, HTTPS, OpenAPI) plus 23 per-page checks (meta tags, JSON-LD, headings, markdown mirrors, content negotiation, code-block language tags, JS-rendering dependency).\n-   **llmstxt.org** — 10 checks against the llms.txt format (H1 present, blockquote summary, H2 sections, link format, content-type, llms-full.txt).\n-   **Agent protocols** — 12 checks covering MCP Server Cards (SEP-1649 / [RFC 9728](https://datatracker.ietf.org/doc/html/rfc9728) OAuth Protected Resource metadata), A2A Agent Cards (a2a.proto v1.0.0), Wildcard agents.json, agent-permissions.json, UCP (Universal Commerce Protocol), x402 (HTTP 402 Payment Required), and NLWeb (natural-language /ask endpoint).\n\n## How is the agent readability score calculated?\n\n`score = round((passed checks / total checks) × 100)`. The denominator compounds: 15 site-wide + (23 per-page × number of pages scanned). A systemic issue like a missing canonical link on every page compounds significantly. Ratings: 90-100 Excellent, 70-89 Good, 50-69 Fair, 0-49 Needs Improvement.\n",
  "fullPageMarkdown": "Agent Ready — AI Agent Readability Checker\n\n[Agent Readyagent.ready](https://agent-ready.dev/)[Sign in](https://agent-ready.dev/sign-in)\n\nNo sign-up required — scan instantly\n\n# Is your site ready for AI agents?\n\nScore any website against the Vercel Agent Readability Spec and llmstxt.org standard. Get actionable fixes in seconds.\n\nScan\n\nLast updated 2026-05-11\n\n[\n\n## Readability spec\n\n15 site-wide + 23 per-page checks from the Vercel Agent Readability Spec\n\n](https://agent-ready.dev/agent-readability-score)[\n\n## llms.txt\n\n10 checks against the llmstxt.org specification for LLM-friendly content\n\n](https://agent-ready.dev/llms-txt-checker)[\n\n## Agent protocols\n\n12 checks covering MCP, A2A, agents.json, UCP, x402, and NLWeb\n\n](https://agent-ready.dev/mcp-card-validator)\n\n## Fix guidance\n\nEvery failing check includes a clear, actionable how-to-fix explanation\n\n## What is agent readability?\n\nAgent readability is how easily AI agents — ChatGPT, Claude, Perplexity, Google Gemini, coding assistants, MCP clients — can discover, parse, and act on a website. It spans three surfaces: discovery files (`llms.txt`, `robots.txt`, sitemaps), structural signals (semantic headings, canonical links, structured data, markdown mirrors), and protocol manifests (MCP Server Cards, A2A Agent Cards, agents.json, agent-permissions.json).\n\n## Why does AI agent readability matter for SEO?\n\nAI agents crawl what loads cleanly and cite what parses correctly. The incentives are sharp: a [July 2025 Pew Research study](https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/) found users who encounter a Google AI Overview click on a source link only about 8% of the time — roughly half the rate of searches without an AI summary. Princeton’s [GEO study (KDD 2024)](https://arxiv.org/abs/2311.09735) measured that adding source citations to a page lifted its inclusion in AI answers by roughly 40%, with statistics and quotations close behind. Sites that score well get summarised accurately and referred qualified traffic; sites that score poorly get paraphrased (badly) or skipped entirely. Unlike traditional SEO, you don’t need to rank on page 1 — structured, citable content gets pulled even when organic rank is low.\n\n## What does the agent readability scanner check?\n\n-   **Vercel Agent Readability Spec** — 15 site-wide checks (llms.txt, robots.txt, sitemap.xml, sitemap.md, AGENTS.md, HTTPS, OpenAPI) plus 23 per-page checks (meta tags, JSON-LD, headings, markdown mirrors, content negotiation, code-block language tags, JS-rendering dependency).\n-   **llmstxt.org** — 10 checks against the llms.txt format (H1 present, blockquote summary, H2 sections, link format, content-type, llms-full.txt).\n-   **Agent protocols** — 12 checks covering MCP Server Cards (SEP-1649 / [RFC 9728](https://datatracker.ietf.org/doc/html/rfc9728) OAuth Protected Resource metadata), A2A Agent Cards (a2a.proto v1.0.0), Wildcard agents.json, agent-permissions.json, UCP (Universal Commerce Protocol), x402 (HTTP 402 Payment Required), and NLWeb (natural-language /ask endpoint).\n\n## How is the agent readability score calculated?\n\n`score = round((passed checks / total checks) × 100)`. The denominator compounds: 15 site-wide + (23 per-page × number of pages scanned). A systemic issue like a missing canonical link on every page compounds significantly. Ratings: 90-100 Excellent, 70-89 Good, 50-69 Fair, 0-49 Needs Improvement.\n",
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  "llmsTxtPreview": "# Agent Ready\n\n> AI agent readability scanner. Runs 60 checks against the Vercel Agent Readability Spec, llmstxt.org, and agent-protocol specs (MCP, A2A, agents.json, agent-permissions.json), returning a 0–100 score and per-check fix guidance.\n\n## Documentation\n- [API & integrations](https://agent-ready.dev/docs/api)\n- [REST API reference](https://agent-ready.dev/docs/api/reference)\n\n## Main\n- [Agent Ready — AI Agent Readability Checker](https://agent-ready.dev/): Score any website against the Vercel Agent Readability Spec and llmstxt.org standard. Get actionable fixes to make your…\n- [Pricing](https://agent-ready.dev/pricing)\n- [Sign in](https://agent-ready.dev/sign-in)\n- [Agent Readability Score](https://agent-ready.dev/agent-readability-score)\n- [llms.txt Checker](https://agent-ready.dev/llms-txt-checker)\n- [AGENTS.md Validator](https://agent-ready.dev/agents-md-validator)\n- [MCP Card Validator](https://agent-ready.dev/mcp-card-validator)\n- [A2A Card Validator](https://agent-ready.dev/agent-card-validator)\n- [agents.json Validator](https://agent-ready.dev/agents-json-validator)\n- [Permissions Validator](https://agent-ready.dev/agent-permissions-validator)\n\n## Legal\n- [Privacy Policy](https://agent-ready.dev/privacy)\n- [Terms of Service](https://agent-ready.dev/terms)\n\n",
  "llmsTxtExisting": "# Agent Ready\n\n> Agent Ready is a free tool that scores any website against the Vercel Agent Readability Spec, the llmstxt.org specification, and agent-protocol specs (MCP, A2A, agents.json). It runs 60 checks and provides actionable fix guidance for every failing check.\n\nUse this file as a compact, curated index of the most useful resources. For the full scoring logic, all 60 check definitions, and the API reference, fetch [/llms-full.txt](https://agent-ready.dev/llms-full.txt).\n\nAgent Ready checks three areas of agent readability:\n\n- Discovery — Can AI agents find your pages? (llms.txt, sitemaps, robots.txt)\n- Structure — Can agents parse your pages? (meta tags, headings, structured data, markdown mirrors)\n- Context — Can agents understand your content? (skill files, content negotiation, code documentation)\n\nLast updated: 2026-05-28. Spec compatibility: Vercel Agent Readability Spec · llmstxt.org · MCP 2025-11-25 (SEP-1649) · A2A v1.0.0 · Wildcard agents.json v0.1.0 · agent-permissions.json.\n\n## Recommended Starting Pages\n\nNew to agent readability? Start here:\n\n- [The complete guide to agent readability](https://agent-ready.dev/complete-guide-to-agent-readability): the hub guide — how agents discover, parse, and cite your site\n- [Methodology](https://agent-ready.dev/methodology): how the 0–100 score is computed across all 60 checks\n- [MCP vs A2A vs agents.json](https://agent-ready.dev/mcp-vs-a2a-vs-agents-json): choose the right agent-discovery protocol\n\n## For developers\n\nAgent Ready exposes a REST API and an MCP server for programmatic use. MCP server: https://agent-ready.dev/api/v1/mcp.\n\n- [Agent Ready quickstart](https://agent-ready.dev/quickstart): first scan in 60 seconds — curl, Node, Python, MCP\n- [Agent authentication for Agent Ready](https://agent-ready.dev/auth): how agents discover, register, use, and revoke credentials (WorkOS auth.md aligned)\n- [OpenAPI 3.1 spec](https://agent-ready.dev/api/v1/openapi.json): every endpoint, request/response schema, auth requirement\n- [MCP server endpoint](https://agent-ready.dev/api/v1/mcp): streamable-http MCP server, Bearer-token authenticated\n- [MCP server card](https://agent-ready.dev/.well-known/mcp/server-card.json): SEP-1649 discovery JSON for one-click MCP install\n- [OAuth protected-resource metadata](https://agent-ready.dev/.well-known/oauth-protected-resource): RFC 9728 auth discovery document\n\n## Pages\n\n- [Home](https://agent-ready.dev): Enter a URL to scan your site\n- [Agent Readability Score](https://agent-ready.dev/agent-readability-score): Get your Vercel Agent Readability score\n- [llms.txt Checker](https://agent-ready.dev/llms-txt-checker): Validate your llms.txt file against the llmstxt.org spec\n- [AGENTS.md Validator](https://agent-ready.dev/agents-md-validator): Check your skill file for coding agents\n- [MCP Server Card Validator](https://agent-ready.dev/mcp-card-validator): Validate your MCP server card at /.well-known/mcp.json\n- [A2A Agent Card Validator](https://agent-ready.dev/agent-card-validator): Validate your A2A agent card at /.well-known/agent-card.json\n- [agents.json Validator](https://agent-ready.dev/agents-json-validator): Validate your Wildcard agents.json manifest\n- [agent-permissions.json Validator](https://agent-ready.dev/agent-permissions-validator): Validate your agent-permissions.json manifest\n- [API & integrations](https://agent-ready.dev/docs/api): REST API, MCP server, and CI/CD action for Pro subscribers\n- [Quickstart](https://agent-ready.dev/quickstart): Run your first Agent Ready scan in under 60 seconds — curl, Node, Python, MCP\n- [Authentication](https://agent-ready.dev/auth): How agents authenticate to Agent Ready — Bearer tokens, OAuth protected-resource metadata, WWW-Authenticate discovery\n- [Ask (NLWeb)](https://agent-ready.dev/ask): Public natural-language /ask endpoint over Agent Ready's methodology, checks, and specs — POST JSON, returns Schema.org-typed results; also exposed as the `ask` MCP tool at /api/v1/mcp\n\n## Guides\n\n- [MCP vs A2A vs agents.json](https://agent-ready.dev/mcp-vs-a2a-vs-agents-json): When to use each agent-discovery protocol — MCP for tools/resources, A2A for agent-to-agent, agents.json for OpenAPI-backed REST APIs\n- [Methodology](https://agent-ready.dev/methodology): How Agent Ready computes its score — 60 checks across four categories, mapped to the Vercel Agent Readability Spec and llmstxt.org standard\n- [The complete guide to agent readability](https://agent-ready.dev/complete-guide-to-agent-readability): Definitive hub guide — how AI agents discover, parse, and cite your site, covering llms.txt, AGENTS.md, MCP cards, JSON-LD, and the Vercel spec\n- [Agent readability glossary](https://agent-ready.dev/glossary): Plain-language definitions of llms.txt, AGENTS.md, MCP, A2A, content negotiation, and the rest of the agent-readability vocabulary\n- [What is NLWeb?](https://agent-ready.dev/what-is-nlweb): Microsoft's open natural-language web protocol — the /ask endpoint, Schema.org-typed results, and why every NLWeb instance is also an MCP server\n\n## Discovery\n\nAgent Ready implements the conventions it audits — these first-party manifests are live and machine-readable:\n\n- [MCP server card](https://agent-ready.dev/.well-known/mcp.json): SEP-1649 server metadata, transport, and capabilities (also at /.well-known/mcp/server-card.json)\n- [A2A agent card](https://agent-ready.dev/.well-known/agent-card.json): A2A v1.0.0 capability and skill discovery\n- [agents.json](https://agent-ready.dev/.well-known/agents.json): Wildcard v0.1.0 OpenAPI-backed action manifest\n- [agent-permissions.json](https://agent-ready.dev/.well-known/agent-permissions.json): declared agent action permissions\n- [API catalog](https://agent-ready.dev/.well-known/api-catalog): RFC 9727 linkset of the public API, its OpenAPI description, and the MCP endpoint\n- [OAuth protected-resource metadata](https://agent-ready.dev/.well-known/oauth-protected-resource): RFC 9728 metadata for the MCP endpoint\n- [Schema feed](https://agent-ready.dev/schema/pages.json): JSON-LD @graph of primary pages with dateModified, indexed by /schemamap.xml\n\n## Specs\n\n- [Vercel Agent Readability Spec](https://vercel.com/kb/guide/agent-readability-spec): The full specification we check against\n- [llmstxt.org](https://llmstxt.org): The llms.txt file specification\n- [Model Context Protocol (2025-11-25)](https://modelcontextprotocol.io): MCP server cards and OAuth protected-resource discovery\n- [A2A Protocol (v1.0.0)](https://a2a-protocol.org): Agent-to-agent discovery at `/.well-known/agent-card.json`\n- agents.json (Wildcard v0.1.0): discovery manifest checked at `/agents.json` or `/.well-known/agents.json`\n- agent-permissions.json: agent permissions manifest checked at `/.well-known/agent-permissions.json`\n\n## Optional\n\nSecondary material — useful for deep dives, but safe to skip when context is tight:\n\n- [Pricing](https://agent-ready.dev/pricing): Free and Pro tiers\n- [llms.txt vs sitemap.xml](https://agent-ready.dev/llms-txt-vs-sitemap-xml): When to use each — audience, format, scope, and why most sites should publish both\n- [ACP vs UCP vs AP2 vs x402](https://agent-ready.dev/acp-vs-ucp-vs-ap2-vs-x402): Comparison of the four agentic-commerce protocols — agent-surface checkout, merchant interoperability, delegated authorization, machine-to-machine payment\n- [AGENTS.md vs CLAUDE.md vs .cursorrules](https://agent-ready.dev/agents-md-vs-claude-md-vs-cursorrules): Which skill-file convention to ship for coding agents — and why most teams ship more than one\n- [How to add an llms.txt file to a Next.js site](https://agent-ready.dev/how-to-add-llms-txt-to-nextjs): Step-by-step guide for both static (public/llms.txt) and dynamic (route handler) approaches in Next.js 13+\n- [How to publish an MCP server card](https://agent-ready.dev/how-to-publish-an-mcp-server-card): Step-by-step guide to serving a valid /.well-known/mcp.json per SEP-1649, including transport, capabilities, and OAuth metadata\n- [How to write an effective AGENTS.md](https://agent-ready.dev/how-to-write-an-effective-agents-md): Step-by-step guide to writing a skill file that coding agents (Codex, Claude Code, Cursor) can actually use",
  "emergingProtocols": {
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      "url": "https://agent-ready.dev/.well-known/mcp.json",
      "name": "agent-ready",
      "version": "1.0.0",
      "description": "AI agent readability scanner. Scan any site and get scores + per-check remediation via MCP tools.",
      "transport": null,
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  "snippets": []
}

API를 사용하여 프로그래밍 방식으로 가져올 수 있습니다 (곧 출시)