agent-browser.dev
Ready with a few material gaps
Task
What does agent-browser.dev do and who is it for? Explain it back to me.
Critical access needs attention
These checks describe whether an ordinary agent can enter, read, and operate the public site.
- 2 / 2 passed
Agents can reach the site
Crawler access and bot defenses.
- 2 / 2 passed
Core content is available
Useful content remains accessible without a fragile browser-only path.
- 1 / 2 passed
Navigation fails safely
Redirects and missing pages give agents a recoverable path.
- 2 / 2 passed
Controls are understandable
Forms and interactive controls expose usable names and structure.
Evaluated surfaces have material gaps
The public website is always evaluated. Optional surfaces appear when the scan finds positive evidence that they apply.
Public website
Blocked
7 of 17 mature checks passed
Fix these gaps first
Critical access gaps come first, followed by other applicable readiness gaps.
- 01Critical access
Agent-friendly 404s
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. - 02Other readiness checks
Markdown content negotiation (acceptmarkdown.com)
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.
- 03Other readiness checks
Developer resource discoverability
Make your developer resources (API docs, OpenAPI spec, auth docs, webhooks, 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.
- 04Other readiness checks
JSON-LD structured data
Add JSON-LD structured data to your homepage using the identity type that matches your site - SoftwareApplication for products, Organization or LocalBusiness for companies, Person for personal sites, Article for blogs - with name, description, url, and type-appropriate fields (offers, sameAs, author) so AI can parse your identity programmatically.
- 05Other readiness checks
Agent instruction / when-to-use
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.
Audit the checks behind the score
Applicable evidence is grouped by how it contributes to this preview model. Bonus checks appear only when they add points.
Essential5 of 7 passed · 62.9 / 80 points
- Content without JavaScriptPassed
2860 chars, semantic headings (H1 + 6 H2s), 5.4% content ratio
Recommendation
Server-side render your homepage so AI crawlers see meaningful content without JavaScript. Ensure an H1 and 500+ chars of text in raw HTML.
- Not blocked by bot detectionPassed
Site accessible to 6 AI agent user-agents
Recommendation
Allowlist known AI agent User-Agents (ChatGPT-User, ClaudeBot, Google-Extended, DeepSeekBot) in your WAF or bot-detection rules.
- Redirect hygienePassed
No meta-refresh stubs, JavaScript-redirect stubs, or cross-domain hops across 6 checked pages
Recommendation
Replace meta-refresh and JavaScript-only redirects with real HTTP 301/302 redirects. Non-JS agents never execute
location.hrefor wait for a meta refresh - they see only the stub page. Verify withcurl -sI <url>- you should see a Location header, not a 200 with a near-empty body. - Content behind authPassed
All 5 sampled pages are publicly readable (5 with substantive content)
Recommendation
Serve your content pages without a login wall. Agents cannot complete auth flows while browsing - a 401/403 or a login-form page is invisible content. Keep public documentation public; if some content must stay gated, publish an ungated summary so agents can still represent it.
- Markdown content negotiation (acceptmarkdown.com)Failed
Not acceptmarkdown.com compliant: Accept: text/markdown returned text/html; charset=utf-8; Vary header missing Accept (got "rsc, next-router-state-tree, next-router-prefetch, next-router-segment-prefetch")
Recommendation
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.
- Agent crawler reachabilityPassed
Reachable to all major AI crawlers - ChatGPT-User: reachable, ClaudeBot: reachable, Google-Extended: reachable, ora-agent: reachable, DeepSeekBot: reachable
Recommendation
Verify that major agent User-Agents can reach the homepage. If your WAF or bot rules block them, remove or narrow the blocking rule. Add an allow rule only when your security setup denies them by default.
- Agent-friendly 404sPartial (50%)
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.
Recommendation
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.
Recommended2 of 10 passed · 5.7 / 20 points
- Developer resource discoverabilityFailed
Agent searched for "agent-browser" developer resources but found nothing relevant
Recommendation
Make your developer resources (API docs, OpenAPI spec, auth docs, webhooks, 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.
- Brand name discoverabilityPartial (33%)
agent-browser.dev appears once in brand-name search results for "agent-browser" (position #4 out of 9)
Recommendation
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.
- Sitemap existsFailed
No sitemap found
Recommendation
Add a valid XML sitemap at /sitemap.xml listing all indexable URLs. Include lastmod dates and keep it under 50MB.
- Content efficiencyPassed
Content efficiency: 6.26% (3304 text chars / 52KB HTML)
Recommendation
Reduce markup overhead so readable text is at least 5% of your HTML. Strip unused inline scripts/styles, server-render content instead of shipping large JSON hydration blobs, and keep wrapper nesting shallow.
- JSON-LD structured dataFailed
No JSON-LD structured data found on homepage
Recommendation
Add JSON-LD structured data to your homepage using the identity type that matches your site - SoftwareApplication for products, Organization or LocalBusiness for companies, Person for personal sites, Article for blogs - with name, description, url, and type-appropriate fields (offers, sameAs, author) so AI can parse your identity programmatically.
- Agent instruction / when-to-useFailed
No agent instruction file with when-to-use guidance found
Recommendation
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.
- Metadata completenessPartial (50%)
3/4 metadata signals present - missing: canonical URL
Recommendation
Add all four signals to your homepage: , , , and . Agents use these for entity resolution and attribution.
- Organization schema completenessFailed
No JSON-LD found - Organization schema missing
Recommendation
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.
- Trust anchor pagesFailed
No trust anchor pages found with sufficient content (About, Contact, Privacy)
Recommendation
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.
- Page token budgetPassed
All 6 measured pages fit an agent context budget (largest ~1K tokens)
Recommendation
Keep each page's extracted text under ~100K characters (~25K tokens) so it fits an agent's context window without truncation. Split oversized reference pages into focused per-topic documents and link them from an index. Check a page with
curl -s <url> | wc -cand remember agents read the extracted text, not the raw HTML.
Bonus signals6 positive · +1.3 points
- NPM/PyPI SDK packagePassed
NPM package found: agent-browser - "Browser automation CLI for AI agents"
Recommendation
Publish a JavaScript/TypeScript SDK package on npm so developers can integrate your API programmatically. In package.json set
repositoryto your source repo andhomepageto your product domain - these links are how agents confirm the package is your official SDK rather than a third-party tool with a similar name. - Agent platform configsPassed
Agent config found: github.com/vercel-labs/agent-browser/blob/main/AGENTS.md
Recommendation
Add an AGENTS.md or .cursorrules file to your public GitHub repo with instructions for how AI coding agents should interact with your codebase. Then make sure the repo is documented in the entry-point pages agents read - homepage, docs, and llms.txt - so it can be discovered without guessing.
- Multi-language SDK packagesPartial (33%)
SDK package found only in npm
Recommendation
Publish official SDK packages across multiple language ecosystems (npm, PyPI, Go modules, RubyGems). Auto-generate them from your OpenAPI spec using tools like openapi-generator. For each package set the project URL or homepage to your product domain (package.json
repository/homepage, PyPIHome-Pageorproject_urls, RubyGemshomepage_uri) - this is how agents verify the package is your official SDK. - Native interactive controlsPassed
74 native controls, 0 non-native div-soup affordances (100% native).
- Accessible names on controlsPassed
73/74 interactive elements have a computable accessible name (99%).
- Accessibility-tree injection safety (bonus)Passed
No hidden instruction text detected in accessibility-tree attributes or off-screen content.
Inspect the underlying audit
The complete Ora audit uses evidence from the scan on . After applying changes, run another scan from the homepage to refresh these recommendations.
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Source: Ora API
Snapshot 2026-08-21T23-05-05-713Z