visibility

capability

opencode.ai

✓ verified

AI Visibility: ✓ check completed — level L3

AI Capability: ✓ check completed — level L2

Levels are cumulative — you must pass L1 before reaching L2, L2 before L3, and so on.

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 4/6

✗ 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 5/6

✓ 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 2/6

✗ 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 1/6

✗ 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 5/6

✓ 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 0/6

✗ 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 0/6

✗ 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

OpenCode.ai has a solid foundation for AI discoverability but lacks the structured data and APIs needed for advanced AI interaction. The site is generally accessible to AI crawlers and has good basic content structure, but it misses key trust signals and programmatic capabilities. This limits its potential for AI-driven recommendations and automated agent use.

AI Visibility — L3

AI systems can reliably find and crawl the site, thanks to a permissive robots.txt, fast loading, and a clear sitemap. However, the lack of structured data (Schema.org, Open Graph) and missing trust elements like author attribution and publish dates reduce its authority and recommendation potential by AI assistants.

AI Capability — L2

The site is readable by AI agents and provides good documentation, but it lacks any programmatic API for structured interaction. Without a defined REST/GraphQL API, authentication methods, or agent integration protocols, AI agents cannot perform actions or retrieve data beyond basic content scraping.

A Visibility score of 3/5 means AI can find the site but may not fully understand or confidently recommend it. A Capability score of 2/5 means AI agents can read content but cannot programmatically interact with services, missing opportunities for automation and integration.

Top Issues

CRITICAL Missing Clear Page Titles and Meta Descriptions visibility · L1 · developer

Why: This is the foundational level of AI visibility. Without a clear title and meta description, AI crawlers cannot quickly identify the page's topic and purpose, making it less likely to be indexed or recommended.

Impact: AI systems may ignore or misrepresent your site, drastically reducing organic discovery and traffic from AI-powered search and chat.

Fix: For each page, ensure the HTML <title> tag is unique and descriptive (e.g., 'OpenCode AI - AI-Powered Code Analysis'). Add a <meta name="description"> tag with a concise, keyword-rich summary of the page content.

CRITICAL Missing Basic Structured Data (JSON-LD) capability · L1 · developer

Why: Structured data is the primary way to make your content's meaning explicit to AI systems. Without it, AI must guess at entities and relationships, leading to inaccurate understanding and poor extraction.

Impact: AI agents cannot reliably understand or use your site's core offerings (e.g., products, services, articles), blocking basic AI-driven interactions and integrations.

Fix: Add JSON-LD <script type="application/ld+json"> blocks to key pages. Start with a 'WebSite' schema for the homepage and an 'Organization' schema with your company name, URL, and logo. For content pages, use appropriate types like 'Article' or 'SoftwareApplication'.

HIGH No Structured API for Programmatic Access capability · L3 · developer

Why: AI agents and other automated systems interact with websites via APIs. Without a well-defined REST or GraphQL API, agents cannot programmatically retrieve data or perform actions, limiting the site to human-only use.

Impact: Prevents any form of AI automation, integration, or agent-based workflow, locking you out of the emerging ecosystem of AI-powered tools and services.

Fix: Design and implement a public API. Start by identifying core data entities (e.g., projects, documentation) and create GET endpoints that return structured JSON. Document the endpoints, request/response formats, and authentication (if any).

HIGH Missing Schema.org Markup for Content Clarity visibility · L2 · developer

Why: Schema.org markup is a key signal for AI to understand page content accurately. It provides a standardized vocabulary that AI systems are trained to recognize and trust.

Impact: Reduces the accuracy with which AI summarizes or cites your content, leading to missed opportunities for being featured in AI-generated answers and recommendations.

Fix: Implement JSON-LD structured data on all major content pages. Use types relevant to your content (e.g., 'Article' for blog posts, 'SoftwareApplication' for product pages). Include key properties like 'headline', 'description', 'author', and 'datePublished'.

HIGH Missing LLMs.txt File for AI Guidance visibility · L3 · developer

Why: An llms.txt file proactively guides LLMs to the most important content on your site, improving the quality and relevance of how your site is represented in AI responses.

Impact: Without guidance, AI may focus on less important pages (like legal disclaimers) or miss key sections, leading to poor representation and lower user trust in AI-sourced information about your brand.

Fix: Create a plain text file at the root: `/llms.txt`. Format it in Markdown. Start with '# OpenCode AI', followed by a tagline in a blockquote '>'. Then add sections like '## Documentation', '## API Reference', '## Blog' with bulleted links to the most important pages. Do not use robots.txt syntax. See llmstxt.org for the spec.

Quick Wins

⚡

Missing Clear Page Titles and Meta Descriptions — For each page, ensure the HTML <title> tag is unique and descriptive (e.g., 'OpenCode AI - AI-Powered Code Analysis'). Add a <meta name="description"> tag with a concise, keyword-rich summary of the page content. (developer)

⚡

Missing LLMs.txt File for AI Guidance — Create a plain text file at the root: `/llms.txt`. Format it in Markdown. Start with '# OpenCode AI', followed by a tagline in a blockquote '>'. Then add sections like '## Documentation', '## API Reference', '## Blog' with bulleted links to the most important pages. Do not use robots.txt syntax. See llmstxt.org for the spec. (developer)

⚡

Missing Open Graph Tags — Add the four essential Open Graph meta tags to the <head> of each page: og:title, og:description, og:image, and og:url. Use values consistent with your page's title and meta description. (developer)

⚡

Missing Organization Schema for Trust — Add a JSON-LD block with an 'Organization' schema type. Include the required properties: '@type': 'Organization', 'name': 'OpenCode AI', 'url': 'https://opencode.ai', and 'logo' (a URL to your official logo image). (developer)

30-Day Roadmap

Week 1: Quick Wins

— Implement unique and descriptive HTML <title> tags and <meta name='description'> tags for all pages.

— Create and deploy the `/llms.txt` file at the root, formatted in Markdown with a clear site structure.

— Add the four essential Open Graph meta tags (og:title, og:description, og:image, og:url) to the <head> of each page.

— Add a JSON-LD block with an 'Organization' schema type to the homepage, including name, url, and logo.

Visibility L1 → L3, Capability L1 → L2

Week 2: Foundation

— Add a 'WebSite' JSON-LD schema to the homepage, linking to the site's main properties.

— Implement JSON-LD structured data on all major content pages (e.g., blog, product) using appropriate types like 'Article' or 'SoftwareApplication' with key properties (headline, description, author, datePublished).

Visibility L3 → L4, Capability L2 → L3

Weeks 3-4: Advanced

— Design and implement a public API: identify core data entities (e.g., projects, documentation) and create GET endpoints returning structured JSON.

— Document the API endpoints, request/response formats, and any authentication requirements.

Capability L3 → L4

After 30 days, the site's AI Visibility Level should reach 4/5 and AI Capability Level should reach 4/5, establishing a strong foundation for AI discoverability and programmatic interaction.