分析済みURL
https://omniasec.ai/
計測: 3 週間前
AI-Readyスコア
普通
/ 100
トークン削減量
スコア内訳
新興プロトコル
6件中0件検出AIエージェントが探すwell-knownエンドポイント。検出されればエージェントが自動的にあなたのサービスを発見・接続できます。
-
OAuth Protected Resource RFC 9728
/.well-known/oauth-protected-resource -
OAuth Discovery RFC 8414
/.well-known/oauth-authorization-server -
MCP Server Card SEP-1649 draft
/.well-known/mcp/server-card.json -
A2A Agent Card A2A v1.0
/.well-known/agent-card.json -
API Catalog RFC 9727
/.well-known/api-catalog -
Agent Skills index Discovery RFC v0.2.0 draft
/.well-known/agent-skills/index.json
この数字は動きます。 モニタリングは開発中です。リストに登録すると公開時にお知らせします。
リストに登録されました!サービス開始時にお知らせします。
計測結果 No JSON-LD / Schema.org found
Schema.org構造化データが見つかりません。JSON-LDはAIエージェントがページから事実に基づいた構造化情報を抽出するのに役立ちます。
実装方法
Schema.orgマークアップを含む<script type="application/ld+json">ブロックを追加してください。適切なタイプを使用:ブログ投稿にはArticle、製品ページにはProduct、企業ページにはOrganization。
計測結果 No Markdown for Agents support detected
サイトがMarkdown for Agentsに対応していません。このCloudflare標準により、AIエージェントがmarkdown形式でコンテンツをリクエストでき、トークン使用量を約80%削減できます。
実装方法
以下の1つ以上を実装してください:(1) Accept: text/markdownにmarkdownコンテンツで応答。(2) .md URL(例:/page.md)を提供。(3) <link rel="alternate" type="text/markdown">タグを追加。(4) markdown検出用のLink HTTPヘッダーを追加。
計測結果 No sitemap found
サイトマップが見つかりません。サイトマップはAIエージェントがサイトのすべてのページを発見するのに役立ちます。
実装方法
すべての公開ページをリストした/sitemap.xmlを作成してください。ほとんどのCMSプラットフォームで自動生成できます。
計測結果 No canonical URL
正規URLが見つかりません。これはAIエージェントがページの優先バージョンを特定し、重複コンテンツを回避するのに役立ちます。
実装方法
ページの正規URLを指す<link rel="canonical" href="...">タグを追加してください。
計測結果 No llms.txt found
サイトにllms.txtファイルがありません。これはAIエージェントがサイト構造を理解するための新しい標準です。
実装方法
llmstxt.org仕様に従って/llms.txtファイルを作成してください。サイトの説明と主要ページへのリンクを含めてください。
計測結果 No Content-Signal found (robots.txt or HTTP headers)
Content-Signalディレクティブが見つかりません。これらはAIエージェントにコンテンツの使用方法(検索インデックス、AI入力、トレーニングデータ)を伝えます。推奨場所はrobots.txtです。
実装方法
robots.txtにContent-Signalを追加:User-agent: *\nContent-Signal: search=yes, ai-input=yes, ai-train=no。markdown応答のHTTPヘッダーとしても追加できます。
計測結果 Content ratio: 5.9% (2138 content chars / 35943 HTML bytes)
ページの実際のコンテンツとHTML全体の比率が低いです。ページ重量の多くがコンテンツではなくマークアップ、スクリプト、スタイルです。
実装方法
CSSを外部スタイルシートに移動し、インラインスタイルを削除し、JavaScriptを最小化し、HTMLがコンテンツ構造に集中するようにしてください。
計測結果 12 semantic elements, 85 divs (ratio: 12%)
ページが<div>要素に大きく依存しています。<section>、<nav>、<header>、<footer>、<aside>などのセマンティック要素はAIエージェントに意味のある構造を提供します。
実装方法
汎用的な<div>コンテナを適切なセマンティック要素に置き換えてください。テーマ別グループには<section>、ナビゲーションには<nav>、ページ/セクションのヘッダーとフッターには<header>/<footer>を使用してください。
計測結果 2/3 OG tags present
Open Graphタグが不足または不完全です。OGタグはAIエージェント(およびソーシャルプラットフォーム)がページのタイトル、説明、画像を理解するのに役立ちます。
実装方法
ページの<head>にog:title、og:description、og:imageメタタグを追加してください。
計測結果 4/275 elements with inline styles (1.5%)
多くの要素にインラインスタイル属性があります。これらはAIエージェントがコンテンツを抽出する際のノイズになります。
実装方法
すべてのインラインスタイルをスタイルシートのCSSクラスに移動してください。多くの固有スタイルが必要な場合はTailwindなどのユーティリティCSSフレームワークを使用してください。
## The AI Security *Command Center.* Orchestrate your security stack, analyze threats with AI, and stop attacks from one interface. [Try Omnia →](https://app.omniasec.ai/login) or install the CLI `curl -fsSL https://omniasec.ai/cli-install | bash` Our network ## Trusted Partners Capabilities ## Built for modern security teams ### Chat Ask Omnia to deobfuscate code, generate cybersecurity reports, look up hashes, or investigate threats — all through a single conversational interface. ### Custom Agents Create personalized AI agents with custom instructions tailored to your security needs. Define how Omnia thinks, responds, and acts for your specific use cases. ### Templates & Prompts Build reusable prompt templates for recurring tasks like incident triage, threat analysis, or compliance checks. Work faster without starting from scratch. ### Knowledge Upload your documents, reports, and intel feeds to create a private knowledge base. Omnia retrieves relevant context automatically when you need it. ### MCPs Connect your own Model Context Protocol servers to extend Omnia with custom tools, data sources, and integrations — no redeployment needed. ### Community Share and discover agents, prompts, workflows, templates, and knowledge bases created by other security professionals. Scale your operations with collective intelligence. Chat ## Your AI security analyst, one message away Deobfuscate code, generate threat reports, investigate hashes, and run security tasks — all through a conversational interface powered by Omnia's AI agents.  File Analysis ## Upload any file, uncover hidden threats Submit files for deep inspection powered by AI engines. Omnia decompiles binaries, disassembles code, and detects obfuscated malware and zero-day patterns that traditional scanners miss.  Market Intelligence ## Monitor every marketplace, spot risks early Search and audit packages across VS Code, npm, PyPI, and more. Instantly surface malicious extensions, typosquatting attempts, and compromised dependencies before they reach your stack.  Workflows ## Automate your security playbooks Build automated workflows that chain Omnia's AI agents to handle your cybersecurity tasks — from triage to response — without writing a single line of code. 
Home | Omnia [](https://omniasec.ai/) [Try Omnia](https://app.omniasec.ai/login) # The AI Security *Command Center.* Orchestrate your security stack, analyze threats with AI, and stop attacks from one interface. [Try Omnia →](https://app.omniasec.ai/login) or install the CLI `curl -fsSL https://omniasec.ai/cli-install | bash` Our network ## Trusted Partners                                 Capabilities ## Built for modern security teams ### Chat Ask Omnia to deobfuscate code, generate cybersecurity reports, look up hashes, or investigate threats — all through a single conversational interface. ### Custom Agents Create personalized AI agents with custom instructions tailored to your security needs. Define how Omnia thinks, responds, and acts for your specific use cases. ### Templates & Prompts Build reusable prompt templates for recurring tasks like incident triage, threat analysis, or compliance checks. Work faster without starting from scratch. ### Knowledge Upload your documents, reports, and intel feeds to create a private knowledge base. Omnia retrieves relevant context automatically when you need it. ### MCPs Connect your own Model Context Protocol servers to extend Omnia with custom tools, data sources, and integrations — no redeployment needed. ### Community Share and discover agents, prompts, workflows, templates, and knowledge bases created by other security professionals. Scale your operations with collective intelligence. Chat ## Your AI security analyst, one message away Deobfuscate code, generate threat reports, investigate hashes, and run security tasks — all through a conversational interface powered by Omnia's AI agents.  File Analysis ## Upload any file, uncover hidden threats Submit files for deep inspection powered by AI engines. Omnia decompiles binaries, disassembles code, and detects obfuscated malware and zero-day patterns that traditional scanners miss.  Market Intelligence ## Monitor every marketplace, spot risks early Search and audit packages across VS Code, npm, PyPI, and more. Instantly surface malicious extensions, typosquatting attempts, and compromised dependencies before they reach your stack.  Workflows ## Automate your security playbooks Build automated workflows that chain Omnia's AI agents to handle your cybersecurity tasks — from triage to response — without writing a single line of code.  Zero-day reads [View all →](https://omniasec.ai/blog/) [### Welcome to Omnia: Redefining Malware Analysis in the Age of AIMar 16, 2026](https://omniasec.ai/blog/welcome-to-omnia/) \> | ## Ready to see what Omnia can do? Join the community redefining how we fight cyber threats. [Try Omnia →](https://app.omniasec.ai/login)
このファイルをサーバーの/index.mdとしてアップロードし、AIエージェントがページのクリーンなバージョンにアクセスできるようにしましょう。Accept: text/markdownコンテンツネゴシエーションを設定して自動的に配信することもできます。
この単一ページ用に生成されたllms.txt
# omniasec.ai > Omnia ## Documentation - [Docs](https://omniasec.ai/docs/) ## Main - [Home | Omnia](https://omniasec.ai/): Omnia - [About](https://omniasec.ai/about/) - [Docs](https://omniasec.ai/docs/) - [Bug Bounty](https://omniasec.ai/bug-bounty/) ## Blog - [Blog](https://omniasec.ai/blog/) ## Legal - [Privacy Policy](https://omniasec.ai/privacy-policy/)
完全なllms.txtにはドメイン全体の分析が必要です(近日公開)
このファイルをドメインのルートにhttps://omniasec.ai/llms.txtとしてアップロードしてください。ChatGPT、Claude、PerplexityなどのAIエージェントはこのファイルを確認してサイト構造を理解します。
アクセシビリティ
Content available without JavaScript
Main content starts at 22% of HTML
Page size: 35KB
AI発見可能性
All major AI search bots allowed
No sitemap found
robots.txt exists
No llms.txt found
構造化データ
No JSON-LD / Schema.org found
2/3 OG tags present
Meta description too short: 5 chars
No canonical URL
lang="en"
セマンティックHTML
Clean heading hierarchy
Has <main>
12 semantic elements, 85 divs (ratio: 12%)
36/36 images with meaningful alt text
Avg div depth: 2.0, max: 3
コンテンツ効率
96% token reduction (HTML→Markdown)
Content ratio: 5.9% (2138 content chars / 35943 HTML bytes)
HTML size: 35KB
4/275 elements with inline styles (1.5%)
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"url": "https://omniasec.ai/",
"timestamp": 1788288938884,
"fetch": {
"mode": "simple",
"timeMs": 17,
"htmlSizeBytes": 35943,
"supportsMarkdown": false,
"markdownAgents": {
"contentNegotiation": false,
"mdUrl": {
"found": false,
"url": null
},
"linkTag": {
"found": false,
"url": null
},
"linkHeader": {
"found": false,
"url": null
},
"responseHeaders": {
"contentSignal": null,
"xMarkdownTokens": null,
"vary": null
},
"frontmatter": {
"present": false,
"fields": [],
"level": "none"
},
"level": "none"
},
"statusCode": 200
},
"extraction": {
"title": "Home | Omnia",
"excerpt": "Omnia",
"byline": null,
"siteName": null,
"lang": "en",
"contentLength": 2138,
"metadata": {
"description": "Omnia",
"ogTitle": "Home | Omnia",
"ogDescription": "Omnia",
"ogImage": null,
"ogType": "website",
"canonical": null,
"lang": "en",
"schemas": [],
"robotsMeta": null,
"author": null,
"generator": "Astro v5.17.3",
"markdownAlternateHref": null
}
},
"markdown": "## The AI Security *Command Center.*\n\nOrchestrate your security stack, analyze threats with AI, and stop attacks from one interface.\n\n[Try Omnia →](https://app.omniasec.ai/login)\n\nor install the CLI\n\n`curl -fsSL https://omniasec.ai/cli-install | bash`\n\nOur network\n\n## Trusted Partners\n\nCapabilities\n\n## Built for modern security teams\n\n### Chat\n\nAsk Omnia to deobfuscate code, generate cybersecurity reports, look up hashes, or investigate threats — all through a single conversational interface.\n\n### Custom Agents\n\nCreate personalized AI agents with custom instructions tailored to your security needs. Define how Omnia thinks, responds, and acts for your specific use cases.\n\n### Templates & Prompts\n\nBuild reusable prompt templates for recurring tasks like incident triage, threat analysis, or compliance checks. Work faster without starting from scratch.\n\n### Knowledge\n\nUpload your documents, reports, and intel feeds to create a private knowledge base. Omnia retrieves relevant context automatically when you need it.\n\n### MCPs\n\nConnect your own Model Context Protocol servers to extend Omnia with custom tools, data sources, and integrations — no redeployment needed.\n\n### Community\n\nShare and discover agents, prompts, workflows, templates, and knowledge bases created by other security professionals. Scale your operations with collective intelligence.\n\nChat\n\n## Your AI security analyst, one message away\n\nDeobfuscate code, generate threat reports, investigate hashes, and run security tasks — all through a conversational interface powered by Omnia's AI agents.\n\n\n\nFile Analysis\n\n## Upload any file, uncover hidden threats\n\nSubmit files for deep inspection powered by AI engines. Omnia decompiles binaries, disassembles code, and detects obfuscated malware and zero-day patterns that traditional scanners miss.\n\n\n\nMarket Intelligence\n\n## Monitor every marketplace, spot risks early\n\nSearch and audit packages across VS Code, npm, PyPI, and more. Instantly surface malicious extensions, typosquatting attempts, and compromised dependencies before they reach your stack.\n\n\n\nWorkflows\n\n## Automate your security playbooks\n\nBuild automated workflows that chain Omnia's AI agents to handle your cybersecurity tasks — from triage to response — without writing a single line of code.\n\n\n",
"fullPageMarkdown": "Home | Omnia\n\n[](https://omniasec.ai/)\n\n[Try Omnia](https://app.omniasec.ai/login)\n\n# The AI Security *Command Center.*\n\nOrchestrate your security stack, analyze threats with AI, and stop attacks from one interface.\n\n[Try Omnia →](https://app.omniasec.ai/login)\n\nor install the CLI\n\n`curl -fsSL https://omniasec.ai/cli-install | bash`\n\nOur network\n\n## Trusted Partners\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nCapabilities\n\n## Built for modern security teams\n\n### Chat\n\nAsk Omnia to deobfuscate code, generate cybersecurity reports, look up hashes, or investigate threats — all through a single conversational interface.\n\n### Custom Agents\n\nCreate personalized AI agents with custom instructions tailored to your security needs. Define how Omnia thinks, responds, and acts for your specific use cases.\n\n### Templates & Prompts\n\nBuild reusable prompt templates for recurring tasks like incident triage, threat analysis, or compliance checks. Work faster without starting from scratch.\n\n### Knowledge\n\nUpload your documents, reports, and intel feeds to create a private knowledge base. Omnia retrieves relevant context automatically when you need it.\n\n### MCPs\n\nConnect your own Model Context Protocol servers to extend Omnia with custom tools, data sources, and integrations — no redeployment needed.\n\n### Community\n\nShare and discover agents, prompts, workflows, templates, and knowledge bases created by other security professionals. Scale your operations with collective intelligence.\n\nChat\n\n## Your AI security analyst, one message away\n\nDeobfuscate code, generate threat reports, investigate hashes, and run security tasks — all through a conversational interface powered by Omnia's AI agents.\n\n\n\nFile Analysis\n\n## Upload any file, uncover hidden threats\n\nSubmit files for deep inspection powered by AI engines. Omnia decompiles binaries, disassembles code, and detects obfuscated malware and zero-day patterns that traditional scanners miss.\n\n\n\nMarket Intelligence\n\n## Monitor every marketplace, spot risks early\n\nSearch and audit packages across VS Code, npm, PyPI, and more. Instantly surface malicious extensions, typosquatting attempts, and compromised dependencies before they reach your stack.\n\n\n\nWorkflows\n\n## Automate your security playbooks\n\nBuild automated workflows that chain Omnia's AI agents to handle your cybersecurity tasks — from triage to response — without writing a single line of code.\n\n\n\nZero-day reads\n\n[View all →](https://omniasec.ai/blog/)\n\n[### Welcome to Omnia: Redefining Malware Analysis in the Age of AIMar 16, 2026](https://omniasec.ai/blog/welcome-to-omnia/)\n\n\\> |\n\n## Ready to see what\nOmnia can do?\n\nJoin the community redefining how we fight cyber threats.\n\n[Try Omnia →](https://app.omniasec.ai/login)\n",
"markdownStats": {
"images": 4,
"links": 1,
"tables": 0,
"codeBlocks": 0,
"headings": 13
},
"tokens": {
"htmlTokens": 13402,
"markdownTokens": 582,
"reduction": 12820,
"reductionPercent": 96
},
"score": {
"score": 67,
"grade": "C",
"rubricVersion": 3,
"dimensions": {
"accessibility": {
"score": 94,
"weight": 30,
"grade": "A",
"checks": {
"content_without_js": {
"score": 100,
"weight": 55,
"evidence": "proven",
"details": "Content available without JavaScript"
},
"fast_content_position": {
"score": 75,
"weight": 25,
"evidence": "plausible",
"details": "Main content starts at 22% of HTML"
},
"reasonable_page_size": {
"score": 100,
"weight": 20,
"evidence": "plausible",
"details": "Page size: 35KB"
}
}
},
"aiDiscoverability": {
"score": 45,
"weight": 25,
"grade": "D",
"checks": {
"robots_allows_ai_bots": {
"score": 100,
"weight": 35,
"evidence": "proven",
"details": "All major AI search bots allowed"
},
"supports_markdown_negotiation": {
"score": 0,
"weight": 20,
"evidence": "plausible",
"details": "No Markdown for Agents support detected"
},
"has_sitemap": {
"score": 0,
"weight": 15,
"evidence": "plausible",
"details": "No sitemap found"
},
"has_robots_txt": {
"score": 100,
"weight": 10,
"evidence": "plausible",
"details": "robots.txt exists"
},
"has_llms_txt": {
"score": 0,
"weight": 10,
"evidence": "speculative",
"details": "No llms.txt found"
},
"has_content_signals": {
"score": 0,
"weight": 10,
"evidence": "speculative",
"details": "No Content-Signal found (robots.txt or HTTP headers)",
"mechanisms": {
"robotsTxt": false,
"httpHeader": false,
"policy": false
}
}
}
},
"structuredData": {
"score": 33,
"weight": 20,
"grade": "F",
"checks": {
"has_schema_org": {
"score": 0,
"weight": 35,
"evidence": "proven",
"details": "No JSON-LD / Schema.org found"
},
"has_open_graph": {
"score": 67,
"weight": 20,
"evidence": "plausible",
"details": "2/3 OG tags present"
},
"has_meta_description": {
"score": 50,
"weight": 20,
"evidence": "plausible",
"details": "Meta description too short: 5 chars"
},
"has_canonical_url": {
"score": 0,
"weight": 15,
"evidence": "plausible",
"details": "No canonical URL"
},
"has_lang_attribute": {
"score": 100,
"weight": 10,
"evidence": "plausible",
"details": "lang=\"en\""
}
}
},
"semanticHtml": {
"score": 88,
"weight": 15,
"grade": "B",
"checks": {
"proper_heading_hierarchy": {
"score": 100,
"weight": 30,
"evidence": "plausible",
"details": "Clean heading hierarchy"
},
"uses_article_or_main": {
"score": 100,
"weight": 25,
"evidence": "plausible",
"details": "Has <main>"
},
"semantic_elements": {
"score": 41,
"weight": 20,
"evidence": "plausible",
"details": "12 semantic elements, 85 divs (ratio: 12%)"
},
"meaningful_alt_texts": {
"score": 100,
"weight": 15,
"evidence": "plausible",
"details": "36/36 images with meaningful alt text"
},
"low_div_nesting": {
"score": 100,
"weight": 10,
"evidence": "speculative",
"details": "Avg div depth: 2.0, max: 3"
}
}
},
"contentEfficiency": {
"score": 73,
"weight": 10,
"grade": "C",
"checks": {
"token_reduction_ratio": {
"score": 100,
"weight": 40,
"evidence": "speculative",
"details": "96% token reduction (HTML→Markdown)"
},
"content_to_noise_ratio": {
"score": 25,
"weight": 30,
"evidence": "speculative",
"details": "Content ratio: 5.9% (2138 content chars / 35943 HTML bytes)"
},
"reasonable_page_weight": {
"score": 100,
"weight": 20,
"evidence": "speculative",
"details": "HTML size: 35KB"
},
"minimal_inline_styles": {
"score": 50,
"weight": 10,
"evidence": "speculative",
"details": "4/275 elements with inline styles (1.5%)"
}
}
}
}
},
"recommendations": [
{
"id": "add_schema_org",
"priority": "critical",
"category": "structuredData",
"titleKey": "rec.add_schema_org.title",
"descriptionKey": "rec.add_schema_org.description",
"howToKey": "rec.add_schema_org.howto",
"howToStepKeys": null,
"effort": "moderate",
"estimatedImpact": 7,
"maxImpact": 7,
"evidence": "proven",
"checkScore": 0,
"checkDetails": "No JSON-LD / Schema.org found"
},
{
"id": "add_markdown_negotiation",
"priority": "critical",
"category": "aiDiscoverability",
"titleKey": "rec.add_markdown_negotiation.title",
"descriptionKey": "rec.add_markdown_negotiation.description",
"howToKey": "rec.add_markdown_negotiation.howto",
"howToStepKeys": null,
"effort": "significant",
"estimatedImpact": 5,
"maxImpact": 5,
"evidence": "plausible",
"checkScore": 0,
"checkDetails": "No Markdown for Agents support detected"
},
{
"id": "add_sitemap",
"priority": "high",
"category": "aiDiscoverability",
"titleKey": "rec.add_sitemap.title",
"descriptionKey": "rec.add_sitemap.description",
"howToKey": "rec.add_sitemap.howto",
"howToStepKeys": null,
"effort": "quick-win",
"estimatedImpact": 3.8,
"maxImpact": 3.8,
"evidence": "plausible",
"checkScore": 0,
"checkDetails": "No sitemap found"
},
{
"id": "add_canonical_url",
"priority": "high",
"category": "structuredData",
"titleKey": "rec.add_canonical_url.title",
"descriptionKey": "rec.add_canonical_url.description",
"howToKey": "rec.add_canonical_url.howto",
"howToStepKeys": null,
"effort": "quick-win",
"estimatedImpact": 3,
"maxImpact": 3,
"evidence": "plausible",
"checkScore": 0,
"checkDetails": "No canonical URL"
},
{
"id": "add_llms_txt",
"priority": "high",
"category": "aiDiscoverability",
"titleKey": "rec.add_llms_txt.title",
"descriptionKey": "rec.add_llms_txt.description",
"howToKey": "rec.add_llms_txt.howto",
"howToStepKeys": null,
"effort": "quick-win",
"estimatedImpact": 2.5,
"maxImpact": 2.5,
"evidence": "speculative",
"checkScore": 0,
"checkDetails": "No llms.txt found"
},
{
"id": "add_content_signals",
"priority": "high",
"category": "aiDiscoverability",
"titleKey": "rec.add_content_signals.title",
"descriptionKey": "rec.add_content_signals.description",
"howToKey": "rec.add_content_signals.howto",
"howToStepKeys": null,
"effort": "quick-win",
"estimatedImpact": 2.5,
"maxImpact": 2.5,
"evidence": "speculative",
"checkScore": 0,
"checkDetails": "No Content-Signal found (robots.txt or HTTP headers)"
},
{
"id": "improve_content_ratio",
"priority": "medium",
"category": "contentEfficiency",
"titleKey": "rec.improve_content_ratio.title",
"descriptionKey": "rec.improve_content_ratio.description",
"howToKey": "rec.improve_content_ratio.howto",
"howToStepKeys": null,
"effort": "moderate",
"estimatedImpact": 2.3,
"maxImpact": 3,
"evidence": "speculative",
"checkScore": 25,
"checkDetails": "Content ratio: 5.9% (2138 content chars / 35943 HTML bytes)"
},
{
"id": "add_semantic_elements",
"priority": "medium",
"category": "semanticHtml",
"titleKey": "rec.add_semantic_elements.title",
"descriptionKey": "rec.add_semantic_elements.description",
"howToKey": "rec.add_semantic_elements.howto",
"howToStepKeys": null,
"effort": "moderate",
"estimatedImpact": 1.8,
"maxImpact": 3,
"evidence": "plausible",
"checkScore": 41,
"checkDetails": "12 semantic elements, 85 divs (ratio: 12%)"
},
{
"id": "add_open_graph",
"priority": "medium",
"category": "structuredData",
"titleKey": "rec.add_open_graph.title",
"descriptionKey": "rec.add_open_graph.description",
"howToKey": "rec.add_open_graph.howto",
"howToStepKeys": null,
"effort": "quick-win",
"estimatedImpact": 1.3,
"maxImpact": 4,
"evidence": "plausible",
"checkScore": 67,
"checkDetails": "2/3 OG tags present"
},
{
"id": "remove_inline_styles",
"priority": "low",
"category": "contentEfficiency",
"titleKey": "rec.remove_inline_styles.title",
"descriptionKey": "rec.remove_inline_styles.description",
"howToKey": "rec.remove_inline_styles.howto",
"howToStepKeys": null,
"effort": "moderate",
"estimatedImpact": 0.5,
"maxImpact": 1,
"evidence": "speculative",
"checkScore": 50,
"checkDetails": "4/275 elements with inline styles (1.5%)"
}
],
"llmsTxtPreview": "# omniasec.ai\n\n> Omnia\n\n## Documentation\n- [Docs](https://omniasec.ai/docs/)\n\n## Main\n- [Home | Omnia](https://omniasec.ai/): Omnia\n- [About](https://omniasec.ai/about/)\n- [Docs](https://omniasec.ai/docs/)\n- [Bug Bounty](https://omniasec.ai/bug-bounty/)\n\n## Blog\n- [Blog](https://omniasec.ai/blog/)\n\n## Legal\n- [Privacy Policy](https://omniasec.ai/privacy-policy/)\n\n",
"llmsTxtExisting": null,
"emergingProtocols": {
"oauthProtectedResource": {
"exists": false,
"url": "https://omniasec.ai/.well-known/oauth-protected-resource"
},
"oauthDiscovery": {
"exists": false,
"url": "https://omniasec.ai/.well-known/oauth-authorization-server"
},
"mcpServerCard": {
"exists": false,
"url": "https://omniasec.ai/.well-known/mcp/server-card.json",
"draft": true
},
"a2aAgentCard": {
"exists": false,
"url": "https://omniasec.ai/.well-known/agent-card.json"
},
"apiCatalog": {
"exists": false,
"url": "https://omniasec.ai/.well-known/api-catalog"
},
"agentSkills": {
"exists": false,
"url": "https://omniasec.ai/.well-known/agent-skills/index.json",
"draft": true
},
"count": 0,
"total": 6
},
"botAccess": {
"probed": true,
"bot": "OAI-SearchBot",
"controlStatus": 200,
"botStatus": 200,
"discriminates": false,
"refusedAsBot": false,
"edge": null,
"verifiable": false,
"detail": "This origin answers OAI-SearchBot exactly as it answers any other client (200). No edge-level filtering of AI crawlers observed."
},
"snippets": [
{
"id": "add_llms_txt",
"title": "Create /llms.txt",
"description": "Upload this file to your web root. It tells AI agents what your site is about and which pages matter.",
"language": "markdown",
"code": "# omniasec.ai\n\n> Omnia\n\n## Documentation\n- [Docs](https://omniasec.ai/docs/)\n\n## Main\n- [Home | Omnia](https://omniasec.ai/): Omnia\n- [About](https://omniasec.ai/about/)\n- [Docs](https://omniasec.ai/docs/)\n- [Bug Bounty](https://omniasec.ai/bug-bounty/)\n\n## Blog\n- [Blog](https://omniasec.ai/blog/)\n\n## Legal\n- [Privacy Policy](https://omniasec.ai/privacy-policy/)\n\n",
"filename": "/llms.txt"
},
{
"id": "add_open_graph",
"title": "Add missing Open Graph tags",
"description": "Open Graph tags control how your page looks when shared on social media and how AI platforms preview your URL in answers.",
"language": "html",
"code": "<meta property=\"og:image\" content=\"https://yoursite.com/og-image.jpg\">\n<meta property=\"og:url\" content=\"https://omniasec.ai/\">\n<meta property=\"og:type\" content=\"website\">",
"filename": "<head>",
"stacks": [
{
"id": "html",
"label": "HTML <head>",
"language": "html",
"filename": "<head>",
"code": "<meta property=\"og:image\" content=\"https://yoursite.com/og-image.jpg\">\n<meta property=\"og:url\" content=\"https://omniasec.ai/\">\n<meta property=\"og:type\" content=\"website\">"
},
{
"id": "wordpress",
"label": "WordPress",
"language": "php",
"filename": "functions.php",
"code": "<?php\n// Quick Open Graph tags without a plugin (skip if Yoast / Rank Math is active)\nadd_action('wp_head', function () {\n if (!is_singular()) return;\n $post = get_queried_object();\n $title = get_the_title($post);\n $desc = get_the_excerpt($post) ?: wp_trim_words(strip_tags($post->post_content), 30);\n $image = get_the_post_thumbnail_url($post, 'large') ?: 'https://yoursite.com/og-image.jpg';\n $url = get_permalink($post);\n printf('<meta property=\"og:title\" content=\"%s\">' . \"\\n\", esc_attr($title));\n printf('<meta property=\"og:description\" content=\"%s\">' . \"\\n\", esc_attr($desc));\n printf('<meta property=\"og:image\" content=\"%s\">' . \"\\n\", esc_url($image));\n printf('<meta property=\"og:url\" content=\"%s\">' . \"\\n\", esc_url($url));\n echo '<meta property=\"og:type\" content=\"article\">' . \"\\n\";\n}, 5);"
},
{
"id": "nextjs",
"label": "Next.js",
"language": "typescript",
"filename": "app/page.tsx",
"code": "// Next.js App Router — Metadata API\nimport type { Metadata } from 'next';\n\nexport const metadata: Metadata = {\n title: \"Home | Omnia\",\n description: \"Omnia\",\n openGraph: {\n title: \"Home | Omnia\",\n description: \"Omnia\",\n url: \"https://omniasec.ai/\",\n images: [\"https://yoursite.com/og-image.jpg\"],\n type: 'website',\n },\n};"
}
]
},
{
"id": "add_canonical_url",
"title": "Add canonical URL",
"description": "The canonical URL tells AI agents which version of the page is the \"official\" one, avoiding duplicate content issues.",
"language": "html",
"code": "<link rel=\"canonical\" href=\"https://omniasec.ai/\">",
"filename": "<head>"
},
{
"id": "add_schema_org",
"title": "Add Schema.org JSON-LD",
"description": "Structured data helps AI agents understand the type, author, and purpose of your content.",
"language": "html",
"code": "<script type=\"application/ld+json\">\n{\n \"@context\": \"https://schema.org\",\n \"@type\": \"WebPage\",\n \"name\": \"Home | Omnia\",\n \"description\": \"Omnia\",\n \"url\": \"https://omniasec.ai/\",\n \"inLanguage\": \"en\"\n}\n</script>",
"filename": "<head>"
},
{
"id": "add_sitemap",
"title": "Create /sitemap.xml",
"description": "A sitemap helps AI agents discover all your pages. Most CMS platforms generate one automatically.",
"language": "xml",
"code": "<?xml version=\"1.0\" encoding=\"UTF-8\"?>\n<urlset xmlns=\"http://www.sitemaps.org/schemas/sitemap/0.9\">\n <url>\n <loc>https://omniasec.ai/</loc>\n <lastmod>2026-09-01</lastmod>\n </url>\n</urlset>",
"filename": "/sitemap.xml"
},
{
"id": "add_content_signals",
"title": "Add Content-Signal directives",
"description": "Content-Signal tells AI agents how they may use your content. The canonical location is robots.txt, but you can also expose it as an HTTP header from any stack.",
"language": "txt",
"code": "User-agent: *\nContent-Signal: search=yes, ai-input=yes, ai-train=no",
"filename": "/robots.txt",
"stacks": [
{
"id": "robots",
"label": "robots.txt",
"language": "txt",
"filename": "/robots.txt",
"code": "User-agent: *\nContent-Signal: search=yes, ai-input=yes, ai-train=no"
},
{
"id": "nginx",
"label": "Nginx",
"language": "nginx",
"filename": "server block",
"code": "# Inside your server { } block:\nadd_header Content-Signal \"search=yes, ai-input=yes, ai-train=no\" always;"
},
{
"id": "apache",
"label": "Apache",
"language": "apache",
"filename": ".htaccess",
"code": "# In .htaccess (or VirtualHost):\nHeader set Content-Signal \"search=yes, ai-input=yes, ai-train=no\""
},
{
"id": "wordpress",
"label": "WordPress",
"language": "php",
"filename": "functions.php",
"code": "<?php\n// In your theme's functions.php or a small mu-plugin\nadd_action('send_headers', function () {\n header('Content-Signal: search=yes, ai-input=yes, ai-train=no');\n});\n\n// Optional: also append the directive to the dynamic robots.txt\nadd_filter('robots_txt', function ($output) {\n return $output . \"\\nContent-Signal: search=yes, ai-input=yes, ai-train=no\\n\";\n}, 10, 1);"
},
{
"id": "nextjs",
"label": "Next.js",
"language": "typescript",
"filename": "middleware.ts",
"code": "// middleware.ts (Next.js 13+ App Router or Pages Router)\nimport { NextResponse } from 'next/server';\nexport function middleware() {\n const res = NextResponse.next();\n res.headers.set(\n 'Content-Signal',\n 'search=yes, ai-input=yes, ai-train=no'\n );\n return res;\n}\nexport const config = { matcher: '/:path*' };"
},
{
"id": "cloudflare",
"label": "Cloudflare Workers",
"language": "javascript",
"filename": "worker.js",
"code": "// Cloudflare Worker that proxies your origin and adds the header\nexport default {\n async fetch(request, env, ctx) {\n const res = await fetch(request);\n const newRes = new Response(res.body, res);\n newRes.headers.set(\n 'Content-Signal',\n 'search=yes, ai-input=yes, ai-train=no'\n );\n return newRes;\n },\n};"
},
{
"id": "express",
"label": "Express / Fastify",
"language": "javascript",
"filename": "server.js",
"code": "// Express\napp.use((req, res, next) => {\n res.setHeader('Content-Signal', 'search=yes, ai-input=yes, ai-train=no');\n next();\n});\n\n// Fastify\nfastify.addHook('onSend', (request, reply, payload, done) => {\n reply.header('Content-Signal', 'search=yes, ai-input=yes, ai-train=no');\n done();\n});"
}
]
},
{
"id": "add_markdown_negotiation",
"title": "Support Markdown for Agents",
"description": "Let AI agents request a clean Markdown version of any page via content negotiation, .md alternate URLs, link tags or Link headers.",
"language": "html",
"code": "<!-- Mechanism 3: link tag advertising the .md alternate -->\n<link rel=\"alternate\" type=\"text/markdown\" href=\"/page.md\">",
"filename": "<head>",
"stacks": [
{
"id": "html",
"label": "HTML <head>",
"language": "html",
"filename": "<head>",
"code": "<!-- Mechanism 3: link tag advertising the .md alternate -->\n<link rel=\"alternate\" type=\"text/markdown\" href=\"/page.md\">"
},
{
"id": "express",
"label": "Express",
"language": "javascript",
"filename": "server.js",
"code": "// Mechanisms 1 + 4: content negotiation + Link header\napp.get('/page', (req, res) => {\n res.setHeader('Vary', 'Accept');\n res.setHeader('Link', '</page.md>; rel=\"alternate\"; type=\"text/markdown\"');\n if ((req.headers.accept || '').includes('text/markdown')) {\n res.type('text/markdown; charset=utf-8');\n return res.send(renderMarkdown('page'));\n }\n res.render('page');\n});"
},
{
"id": "fastify",
"label": "Fastify",
"language": "javascript",
"filename": "server.js",
"code": "// Mechanisms 1 + 4: content negotiation + Link header\nfastify.get('/page', async (req, reply) => {\n reply.header('Vary', 'Accept');\n reply.header('Link', '</page.md>; rel=\"alternate\"; type=\"text/markdown\"');\n if ((req.headers.accept || '').includes('text/markdown')) {\n return reply.type('text/markdown; charset=utf-8').send(renderMarkdown('page'));\n }\n return reply.view('/page.ejs');\n});"
},
{
"id": "nextjs",
"label": "Next.js",
"language": "typescript",
"filename": "app/page/route.ts",
"code": "// Next.js App Router — Route Handler returning Markdown\nimport { NextRequest } from 'next/server';\nimport { renderMarkdown } from '@/lib/md';\nexport async function GET(req: NextRequest) {\n const accept = req.headers.get('accept') || '';\n if (accept.includes('text/markdown')) {\n return new Response(await renderMarkdown('page'), {\n headers: {\n 'Content-Type': 'text/markdown; charset=utf-8',\n 'Vary': 'Accept',\n },\n });\n }\n // Fall through to the page component\n return new Response(null, { status: 404 });\n}"
},
{
"id": "wordpress",
"label": "WordPress",
"language": "php",
"filename": "functions.php",
"code": "<?php\n// Mechanism 1: respond to Accept: text/markdown on the same URL\nadd_action('template_redirect', function () {\n if (!is_singular()) return;\n $accept = $_SERVER['HTTP_ACCEPT'] ?? '';\n if (strpos($accept, 'text/markdown') === false) return;\n header('Content-Type: text/markdown; charset=utf-8');\n header('Vary: Accept');\n $post = get_queried_object();\n echo \"# \" . get_the_title($post) . \"\\n\\n\";\n echo wp_strip_all_tags(apply_filters('the_content', $post->post_content));\n exit;\n});"
},
{
"id": "static",
"label": "Hugo / Jekyll / Astro",
"language": "txt",
"filename": "static/page.md",
"code": "# Mechanism 2: serve .md alongside .html\n# Hugo: place page.md in /static/ — built unchanged\n# Jekyll: drop page.md in /assets/ — copied as-is\n# Astro: src/pages/page.md.ts that exports a GET returning markdown\n\n# Then advertise with mechanism 3 in <head>:\n# <link rel=\"alternate\" type=\"text/markdown\" href=\"/page.md\">"
}
]
}
]
}
APIを使用してプログラムで取得できます(近日公開)
このJSONは内部使用向けです — MarkdownやllMs.txtファイルとは異なり、サイトにアップロードするものではありません。スコアの経時変化を追跡するための基準値として保存するか、開発チームと共有するか、CI/CDパイプラインに統合してください。
結果を共有
または AI に改善方法を聞く
セカンドオピニオンもどうぞ
Cloudflare も無料のスキャナーを公開していますが、問いが違います。あちらは、エージェントが呼び出すためにサイトが公開しているもの(MCP server card、Agent Skills、API カタログ、DNS レコード)を採点します。当社は、エージェントがコンテンツに到達し、読み、理解できるかを採点します。片方が高く、もう片方が低いサイトもあります。数字が食い違うのは当然です。別々の問いへの答えであり、どちらも知る価値があります。
Cloudflare で omniasec.ai をスキャンバッジを埋め込む
このバッジをサイトに追加してください。AI対応スコアが変わると自動的に更新されます。
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近日公開: ドメイン全体分析
ドメイン全体をクロールし、llms.txtを生成し、AI対応スコアを経時的にモニタリング。ウェイトリストに登録して通知を受け取りましょう。
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