visibility

capability

zenn.dev

✓ verified

AI Visibility: ✓ check completed — level L1

AI Capability: ✓ check completed — level L3

L1 Basic Accessibility 5/6

✓ Major AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended) are permitted to access your site. AI crawling allowed

✗ Main content is visible in the HTML source, not only rendered after JavaScript executes. Page content directly readable

✓ The page has a clear title and meta description, helping AI quickly identify the topic. Clear title and description

✓ The page responds quickly enough to avoid AI crawl failures or timeouts. Reasonable response time

✓ The site uses a valid HTTPS certificate. HTTPS secured

✓ Core content isn't blocked by login walls, membership gates, or paywalls. Content is not gated

L2 Content Comprehensibility 3/6

✗ Uses Schema.org / JSON-LD to help AI understand page content more accurately. Has structured data

✓ Open Graph tags provide supplementary title and summary information. Has social sharing info

✓ A canonical URL tells search engines and AI which version of the URL is authoritative. Clear canonical address

✗ The page has a clear H1 and uses H2/H3 headings to organize content logically. Clear heading hierarchy

✓ The HTML lang attribute is set, helping AI identify the page language. Language declared correctly

✗ The page has meaningful text content, not just a few sentences of boilerplate. Substantial content

L3 Discoverability 4/6

✓ An accessible XML sitemap helps AI and search engines discover your pages. Provides a sitemap

✗ The sitemap includes recent pages and isn't neglected over time. Sitemap stays updated

✓ Key content pages are easily reachable from the homepage and main pages. Clear internal linking

✓ Page URLs clearly reflect the content topic, rather than being cryptic parameter strings. Clean, readable URLs

✗ A /llms.txt file proactively tells LLMs which content is most worth paying attention to. Provides llms.txt

✓ The canonical tag points to the current page's standard address, avoiding duplicate page confusion. Consistent canonical setup

L4 Trust & Authority 3/6

✗ Structured data includes basic info like company/organization name, website, and logo. Organization info is clear

✓ Both users and AI can easily find your contact or about page. About and contact info visible

✗ Pages attribute content to an author, team, or organization. Content source is clear

✗ Pages include publish or update dates, helping assess content freshness. Publication dates are clear

✓ The site has essential pages like privacy policy and terms of service. Legal info is complete

✓ Basic security response headers are set, reflecting site maintenance quality. Proper security configuration

L5 AI-Optimized 0/6

✗ Page content is structured for AI to directly extract answers. Has FAQ / HowTo / Q&A structure

✗ Helps AI understand the page's position and hierarchy within the site. Has breadcrumb structure

✗ Products, services, or content include structured Review/Rating data. Has review information

✗ Multilingual pages have clear corresponding relationships, such as hreflang tags. Supports multiple languages

✗ Uses multiple effective Schema.org types, not just one. Richer structured data

✗ Pages contain FAQs, tables, lists, definitions, etc., making it easy for AI to extract and summarize. Clear content block structure

L1 Basic Accessibility 5/6

✓ Uses semantic HTML elements such as header, nav, main, article, section, and footer so agents can better understand page structure. Semantic HTML

✓ Includes essential metadata such as page title, description, and social sharing tags to improve machine interpretation. Metadata

✗ Provides JSON-LD structured data based on Schema.org to make entities and page meaning more explicit. Structured Data

✓ Public content is accessible without CAPTCHA or other anti-bot challenges that block legitimate automated access. No CAPTCHA Barriers

✓ Core content is present in the initial HTML response, rather than relying entirely on client-side JavaScript rendering. Server-Rendered Content

✓ Uses stable, human-readable URLs without excessive query parameters, session tokens, or hash-fragment routing. Clean URLs

L2 Discoverability 4/6

✗ Provides a robots.txt file that permits access for legitimate crawlers and agent systems where appropriate. robots.txt

✓ Publishes a valid XML sitemap to help agents and crawlers discover indexable pages efficiently. XML Sitemap

✗ Exposes a /llms.txt file that gives LLM-based systems guidance on important content and site structure. llms.txt

✓ Publishes an OpenAPI or Swagger specification so agents can understand available API endpoints programmatically. OpenAPI Specification

✓ Provides comprehensive documentation in a format that is easy for machines and agents to parse and use. Machine-Readable Documentation

✓ Ensures primary content is available as text, rather than being locked inside images, videos, or non-parsable PDFs. Text-Accessible Content

L3 Structured Interaction 4/6

✓ Exposes a well-defined REST or GraphQL API for programmatic access to data and actions. Structured API

✓ Returns JSON payloads with stable and predictable schemas across endpoints. Consistent JSON Responses

✓ Supports query parameters for search, filtering, pagination, and retrieval refinement. Search and Filtering Support

✗ Provides an agent descriptor, such as an A2A agent card at /.well-known/agent.json, to advertise agent capabilities. A2A Agent Card

✓ Clearly documents rate limits and returns proper 429 Too Many Requests responses when limits are exceeded. Documented Rate Limits

✗ Returns machine-readable error responses with clear codes, messages, and actionable context. Structured Error Handling

L4 Agent Integration 1/6

✓ Provides an MCP (Model Context Protocol) server so agents can access tools, resources, and actions through a standardized interface. MCP Server

✗ Supports WebMCP or comparable browser-oriented agent interaction patterns for web-based automation. WebMCP Support

✗ Supports write operations such as POST, PUT, PATCH, and DELETE, enabling agents to create and update resources. Write-Capable API

✗ Supports automation-ready authentication methods such as API keys or OAuth client credentials flows. Agent-Friendly Authentication

✗ Supports webhooks so agents can receive event-driven updates instead of relying only on polling. Webhooks

✗ Write operations support idempotency keys or equivalent safeguards to prevent duplicate execution. Idempotent Writes

L5 Autonomous Operation 0/6

✗ Supports real-time update channels such as SSE or WebSockets for low-latency agent workflows. Event Streaming

✗ Supports agent-to-agent capability discovery or negotiation so systems can adapt to each other dynamically. Capability Negotiation

✗ Provides APIs for subscription, lifecycle management, or registration of agent integrations. Subscription and Management API

✗ Supports multi-step workflows, task coordination, and stateful execution across actions or services. Workflow Orchestration

✗ Can proactively notify agents when relevant content, state, or business events change. Proactive Notifications

✗ Supports handoff between agents or services so tasks can continue across system boundaries. Cross-Service Handoff

AI Readiness Report

download .md

Executive Summary

Zenn.dev is a technically capable platform for AI agents but is poorly optimized for AI discovery and recommendation. Its strength lies in providing structured APIs and documentation for programmatic use, but it lacks the foundational trust signals and content structuring needed for AI systems to confidently find and recommend its content.

AI Visibility — L1

The site is fundamentally accessible to AI crawlers but lacks the structured data, clear authorship, and content freshness signals that build trust and authority. This makes it unlikely for AI assistants like ChatGPT or Perplexity to recommend it as a primary, reliable source of information.

AI Capability — L3

The site is well-prepared for AI agents to interact with its data programmatically, offering a documented API, OpenAPI spec, and MCP server. However, it lacks key integration features like agent authentication and write operations, limiting agents to read-only, non-autonomous tasks.

With low visibility, the site misses out on being surfaced by AI assistants to users. Its moderate capability score means AI agents can fetch data but cannot perform actions like posting content or receiving real-time updates on behalf of users.

Top Issues

CRITICAL Main Content Not Visible in HTML Source visibility · L1 · developer

Why: AI crawlers like GPTBot often parse raw HTML without executing JavaScript. If primary content is rendered only after JS loads, the AI will see an empty or incomplete page.

Impact: Critical failure. AI systems cannot discover or index your articles, leading to zero visibility and traffic from AI-driven platforms like ChatGPT or Perplexity.

Fix: Implement server-side rendering (SSR) or static generation for article pages. Ensure the core article text, title, and author are present in the initial HTML response before any JavaScript executes.

HIGH Missing Structured Data (Schema.org) visibility · L2 · developer

Why: Schema.org markup provides explicit, machine-readable context about page content (e.g., this is an Article, by this Author). Without it, AI must infer meaning from plain text, which is less accurate.

Impact: High. AI summaries and citations will be less precise, reducing the likelihood of your content being correctly recommended and trusted as a source.

Fix: Add JSON-LD script blocks to article pages. Use types like Article (with headline, author, datePublished) and WebSite. Place the script in the <head> or <body> of the page.

MEDIUM Poor Semantic Heading Structure visibility · L2 · content

Why: Clear heading hierarchy (H1, H2, H3) helps AI understand the logical flow and key sections of an article, improving content parsing and summarization.

Impact: Medium. AI may struggle to correctly extract and organize key points from articles, leading to lower-quality citations or summaries that miss important sections.

Fix: Audit article templates. Ensure each page has a single, descriptive H1 (the article title). Use H2 for major sections and H3 for subsections. Avoid using headings for purely stylistic purposes.

MEDIUM Insufficient Meaningful Text Content visibility · L2 · content

Why: AI systems prioritize content-rich pages. Pages with only a few sentences or boilerplate are seen as low-value and are less likely to be indexed or cited.

Impact: Medium. Thin content pages will be deprioritized by AI, reducing the site's overall authority and the number of pages that can drive AI-referred traffic.

Fix: Review pages with low word counts. For article listings or user profiles, ensure there is descriptive introductory text. Encourage authors to write substantive articles with detailed explanations.

MEDIUM Missing Clear Author Attribution visibility · L4 · developer

Why: AI and users trust content more when it's clearly attributed to a credible author or organization. This builds authority and helps AI correctly associate content with experts.

Impact: Medium. Lack of clear attribution reduces the perceived trustworthiness of content, making AI less likely to cite it as a definitive source, especially for expert topics.

Fix: On article pages, explicitly display the author's name and link to their profile. In the HTML, use the `author` property in Article Schema.org markup and consider using rel="author" links.

Quick Wins

⚡

Missing LLMs.txt File — Create a plain text file at /llms.txt. Format it in Markdown: start with '# Zenn', a tagline in a blockquote '>', then sections like '## Articles' with bulleted links to important pages or categories. See llmstxt.org for spec. (developer)

⚡

Missing Organization Schema — Add a JSON-LD block for the Organization type to the site's homepage or global footer. Include required properties: '@type': 'Organization', 'name': 'Zenn', 'url': 'https://zenn.dev', and 'logo'. (developer)

⚡

Missing Publication Dates on Pages — Ensure the article template displays the publication date prominently. Include the `datePublished` property in the Article Schema.org markup. For updated articles, also add `dateModified`. (developer)

⚡

Missing or Restrictive Robots.txt — Ensure /robots.txt exists and is accessible. Add explicit 'Allow' rules for AI crawlers like GPTBot, ClaudeBot, and PerplexityBot. Example: 'User-agent: GPTBot\nDisallow: /private/\nAllow: /'. (devops)

30-Day Roadmap

Week 1: Quick Wins

— Create and deploy /llms.txt file formatted per llmstxt.org spec with site introduction and key content links.

— Add JSON-LD Organization Schema block to homepage or global footer with name, url, and logo.

— Update /robots.txt to include explicit 'Allow' rules for AI crawlers (GPTBot, ClaudeBot, PerplexityBot).

— Ensure article template displays publication date and add datePublished (and dateModified if applicable) to Article Schema markup.

Visibility L1 → L2

Week 2: Foundation

— Implement missing Article and WebSite JSON-LD structured data blocks on article pages, including headline, author, and datePublished properties.

— Explicitly display author name and link on article pages and add the 'author' property to the Article Schema markup.

Visibility L2 → L3

Weeks 3-4: Advanced

— Implement server-side rendering (SSR) or static generation for article pages to ensure core content (title, text, author) is present in the initial HTML.

— Audit and fix article template heading structure to ensure a single H1, proper H2/H3 hierarchy, and remove stylistic heading misuse.

— Review low-word-count pages (listings, profiles) and add descriptive introductory text; encourage authors to write substantive content.

Visibility L3 → L4, Capability L3 → L4

The site's AI Visibility Level should improve from L1 to L4 by addressing foundational markup and critical rendering. AI Capability Level should improve from L3 to L4 through enhanced content structure and depth.

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