wazoo.dev
Finalizing the report
Preparing the stored Is Agentic score
Essential—
Recommended—
Bonus signals—
wazoo.dev
Preparing the stored Is Agentic score
wazoo.dev
These checks describe whether an ordinary agent can enter, read, and operate the public site.
Agents can reach the site
Crawler access and bot defenses.
Core content is available
Useful content remains accessible without a fragile browser-only path.
Navigation fails safely
Redirects and missing pages give agents a recoverable path.
Controls are understandable
Forms and interactive controls expose usable names and structure.
The public website is always evaluated. Optional surfaces appear when the scan finds positive evidence that they apply.
Needs work
Weighted across 16 applicable checks
Ready with gaps
Weighted across 12 applicable checks
Needs work
Weighted across 3 applicable checks
Critical access gaps come first, followed by other applicable readiness gaps.
Server-side render your homepage so AI crawlers see meaningful content without JavaScript. Ensure an H1 and 500+ chars of text in raw HTML.
Return a real HTTP 404 (or 410) status for nonexistent paths - never a 200 with your app shell, which makes agents believe every path exists. For full credit, give the 404 response a short markdown body pointing agents at your sitemap, llms.txt, or docs index. Verify with curl -s -o /dev/null -w "%{http_code}" https://yourdomain.com/some-path-that-does-not-exist - it must print 404.
On the responses that serve text/markdown via Accept negotiation, add Accept to the Vary header (Vary: Accept, Accept-Encoding). Without it, CDNs can serve the cached HTML variant to an agent asking for markdown (or vice versa), depending on which variant landed in cache first.
Build an MCP (Model Context Protocol) server exposing your API as tools. Use Streamable HTTP transport for full score. This lets Claude, ChatGPT, and other AI agents call your product natively.
Tell agents when to reach for you: add a 'when to use this' section to your llms.txt (or a dedicated agent-instructions file) that names your best-fit use cases and how an agent should call you. Be specific about the jobs you are right for - generic marketing copy does not read as guidance.
Checks are grouped by relevance for Docs & content sites.
Only 805 chars of text content, no H1 tag - agents see limited content
How to pass
Server-side render your homepage so AI crawlers see meaningful content without JavaScript. Ensure an H1 and 500+ chars of text in raw HTML.
Site accessible to 6 AI agent user-agents
No meta-refresh stubs, JavaScript-redirect stubs, or cross-domain hops across 3 checked pages
All 2 sampled pages are publicly readable (2 with substantive content)
OpenAPI spec found at https://api.wazoo.dev/openapi.json (version: 3.0.0)
Not acceptmarkdown.com compliant: Accept: text/markdown returned text/html; charset=utf-8; Vary header missing Accept (got "accept-encoding")
How to pass
On the responses that serve text/markdown via Accept negotiation, add Accept to the Vary header (Vary: Accept, Accept-Encoding). Without it, CDNs can serve the cached HTML variant to an agent asking for markdown (or vice versa), depending on which variant landed in cache first.
API returns JSON error responses (404 at https://api.wazoo.dev (from OpenAPI servers))
MCP server exposes 1 resource(s) via resources/list
Nonexistent paths return a real HTTP 404. For full credit, include a short markdown body (site map links, where to look next) so agents can recover.
How to pass
Return a real HTTP 404 (or 410) status for nonexistent paths - never a 200 with your app shell, which makes agents believe every path exists. For full credit, give the 404 response a short markdown body pointing agents at your sitemap, llms.txt, or docs index. Verify with curl -s -o /dev/null -w "%{http_code}" https://yourdomain.com/some-path-that-does-not-exist - it must print 404.
Name search surfaced no pages on wazoo.dev, although developer resources exist on the site (API docs, OpenAPI spec, developer portal, auth docs, MCP server) - weak search indexing or transient search noise
How to pass
Make your developer resources (API docs, OpenAPI spec, auth docs, developer portal, MCP server) discoverable by name. Publish them at predictable URLs, list them in llms.txt, and include your product name in page titles and headings so search engines surface them for name-based queries.
wazoo.dev appears once in brand-name search results for "Wazoo Technologies" (position #5 out of 9)
How to pass
Make sure a clean search for your brand name returns your own domain in the top results. If it does not, your brand may be too generic, conflict with a more established term, or not yet indexed. Strengthen brand-name search by claiming consistent NAP across listings, earning press mentions that link to the canonical domain, and avoiding redirect chains that mask the apex domain in search results.
No sitemap found
How to pass
Add a valid XML sitemap at /sitemap.xml listing all indexable URLs. Include lastmod dates and keep it under 50MB.
Rich JSON-LD identity: Organization with name, description, url, and sameAs/logo/address (1 block)
Documentation site found at https://docs.wazoo.dev
No agent instruction file with when-to-use guidance found
How to pass
Tell agents when to reach for you: add a 'when to use this' section to your llms.txt (or a dedicated agent-instructions file) that names your best-fit use cases and how an agent should call you. Be specific about the jobs you are right for - generic marketing copy does not read as guidance.
Only 1/4 metadata signals present - missing: canonical URL, og:image, og:type
How to pass
Add all four signals to your homepage: <link rel="canonical">, <html lang="...">, <meta property="og:image">, and <meta property="og:type">. Agents use these for entity resolution and attribution.
Organization schema found but missing: contactPoint, address
How to pass
Add Organization JSON-LD that includes both contactPoint (with email/phone and contactType) and address (PostalAddress). This lets AI verify your business legitimacy and answer contact queries.
Only Privacy page verified - missing: About, Contact
How to pass
Publish real /about, /contact, and /privacy pages with at least 500 characters of content each. These are the pages AI agents check to verify your business is legitimate before recommending you.
All 3 measured pages fit an agent context budget (largest ~1K tokens)
Code fences balanced across 1 markdown document
Developer documentation portal found at https://docs.wazoo.dev
REST API documentation found at https://docs.wazoo.dev/introduction.md. Best-of-protocols score: 7/7.
No MCP server or manifest found
How to pass
Build an MCP (Model Context Protocol) server exposing your API as tools. Use Streamable HTTP transport for full score. This lets Claude, ChatGPT, and other AI agents call your product natively.
No REST rate-limit headers found on probed endpoints
How to pass
Return standard rate-limit headers on your API responses (the RFC RateLimit headers, plus Retry-After on a 429) so agents can self-throttle in real time, and document the conventions alongside your API.
No typed error model found in OpenAPI spec
How to pass
Document your error responses in your OpenAPI spec: give 4xx and 5xx responses a typed error schema (or use RFC 9457 application/problem+json). A consistent error object with a machine-readable code and a human-readable message lets agents handle failures without guessing.
API versioning found (URL versioning (servers or paths)) but no deprecation or sunset policy detected - add Sunset/Deprecation headers or a deprecation policy page
How to pass
Declare a versioning policy agents can rely on: version your API (in the URL path or a version header) and publish how you signal deprecation (a Sunset/Deprecation header or a documented timeline). Agents avoid integrating against a surface that can change without warning.
CLI tool mentioned in llms.txt
How to pass
Publish an official CLI tool on npm, PyPI, or Homebrew. A CLI lets agents and developers script interactions with your product without building API integrations from scratch.
91% of operations define typed response schemas, 91% use application/json
REST: agent-friendly schema (23 operations, 100% with operationIds, 100% documented by description or summary)
Compatible: 23/23 ops with IDs, 19/23 with typed schemas
1/1 resources read with valid mimeType and non-empty content
Agent config found: github.com/wazootech/worlds/blob/main/AGENTS.md
MCP server discoverable via server-card.json at /.well-known/mcp/
Found the llms.txt at https://docs.wazoo.dev/llms.txt.
The llms.txt is well-formatted: 138 lines with markdown links, 18,298 characters in total.
Strong entity linking via sameAs: linkedin.com, github.com
All 5 probed llms.txt links resolve to real content
All 3 tools on docs MCP have detailed descriptions (>= 30 chars)
3/3 tools on docs MCP have parameter schemas
docs MCP identifies as "Wazoo Docs" v1.0.0 with instructions
docs MCP exposes 3 tool(s) - focused docs surface
All 3 tool names follow consistent convention, descriptive, and non-generic
docs MCP is public - correct posture for documentation surface
docs MCP returns structured JSON-RPC errors with code and message
docs MCP uses modern Streamable HTTP transport
docs MCP: 3/3 tools have behavioral annotations
MCP server card found at https://docs.wazoo.dev/.well-known/mcp/server-card.json (2 tools advertised)
Server HTML is a well-structured document (main=true, landmarks=3/4, h1=1, maxHeadingSkip=1).
16 native controls, 0 non-native div-soup affordances (100% native).
16/16 interactive elements have a computable accessible name (100%).
No hidden instruction text detected in accessibility-tree attributes or off-screen content.
What does wazoo.dev do and who is it for? Explain it back to me.
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Source: Ora API
What does wazoo.dev do and who is it for? Explain it back to me.
28 steps3 reasoning steps14 searches
The agent successfully assembled a comprehensive explanation of Wazoo by combining sparse official content with inferred prior knowledge. The main website ([1]) and documentation ([2]) provided minimal marketing copy and technical detail; the GitHub README ([14]) supplied the core pitch ("persistent, edge-native knowledge graph storage for agents"), and structured metadata embedded in the homepage ([25], referenced in final response) yielded the neuro-symbolic positioning. However, the site failed to surface pricing, business model, or competitive positioning—gaps the agent explicitly flagged rather than glossed over.