Rapporto del sito: 1 pagina misurata. Valutazione complessiva: Discreto.
Punteggio del sito · figma.com
Combina l'origine e 1 pagina misurata. Il report qui sotto dettaglia soltanto la pagina di origine.
Porta i risultati a chi può risolverli. Copia un riepilogo pronto per Slack, Teams o la prossima riunione.
Questo rapporto è pubblico. Il team può aprirlo senza un account.
C'è sostanza che un agente possa leggere?
Homepage does not serve Markdown via content negotiation
Serve a Markdown representation of your pages when agents request "Accept: text/markdown". Agents like Claude Code and Cursor ask for it, and Markdown cuts token usage by roughly 80% against HTML. Cloudflare ("Markdown for Agents") and Vercel can enable this without code changes.
No <link rel="alternate" type="text/markdown"> fallback found on the homepage
If you cannot enable content negotiation, advertise a Markdown version with <link rel="alternate" type="text/markdown" href="/index.md"> so agents can discover it.
1 JSON-LD block(s) found
@context references schema.org
No @graph array (single-entity only)
Use an @graph array to define multiple entities in one JSON-LD block: { "@context": "https://schema.org", "@graph": [...] }
Only 1 key type found: Organization
Add more entity types to your @graph. AI agents use these to understand site structure. Common types: Person, Organization, WebSite, WebPage.
No BreadcrumbList found
Add a BreadcrumbList entity to help AI agents understand your site navigation hierarchy.
No author declared in structured data
An assistant deciding whether to cite a page weighs where it came from. Add author as a Person or Organization, not a bare string.
6 sameAs link(s) tie your entity to external identifiers
Organization carries disambiguating detail (registration, legal address or contact point)
No dateModified or datePublished in structured data
Assistants weigh recency when they answer time-sensitive questions, and a page with no date cannot be weighed at all. Add dateModified to anything that changes.
Server-rendered content detected (598 words, 3979 chars of visible text)
Low text-to-markup ratio (0.2%)
A very low text-to-markup ratio is a typical SPA-shell symptom. Inline more content directly into the HTML response.
Semantic landmarks present (main, article, section, header, footer, nav)
Single <h1> heading: "The intelligent canvas for infinite creativity"
Heavy JavaScript with no <noscript> fallback
Provide a <noscript> fallback that explains the site or links to a non-JS variant. This helps agents that disable JS.
92/92 <img> tags have alt attributes
<title> length 56 chars: "Figma: The collaborative canvas for design, code, and AI"
Meta description is long (164 chars)
Trim to 70-160 characters; longer descriptions get truncated.
Canonical URL: https://www.figma.com/
<html lang="en">
UTF-8 charset declared
Viewport meta present: "width=device-width, initial-scale=1"
155/157 interactive elements have an accessible name
Method note: this reads markup, not a rendered accessibility tree
Un agente riesce a recuperarla?
A missing page redirects (301) instead of returning 404
A redirect on a nonexistent path hides the error. Return 404 or 410 so a client can tell the difference.
Homepage answers after 1 redirect
HEAD requests are supported
Content-Type: text/html with charset
Response compressed with Brotli (br)
Cache validator present (ETag)
Conditional request returns 304 Not Modified
Homepage is on the large side (1.6 MB decompressed)
Consider trimming inlined payloads to reduce crawl cost.
Roughly 995 tokens of content in 418,360 tokens of response (100% markup)
An agent pays to receive the markup and then discards it. Serving Markdown on Accept negotiation is the direct fix.
Homepage responded in 95ms
Site is served over HTTPS
HTTP requests redirect to HTTPS
HSTS max-age=31536000
HSTS includes subdomains
HSTS preload-eligible
All 10 core AI crawler user-agents receive the same page as a regular client
Homepage is indexable
Google-Extended is disallowed, but this page is still eligible for AI Overviews
Google-Extended governs Gemini training and grounding in Gemini Apps and Vertex AI. AI Overviews and AI Mode follow Googlebot and the snippet directives instead. If the intent was to stay out of AI Overviews, use nosnippet or max-snippet. If the intent was to opt out of training, this is already correct.
Un agente trova ciò che pubblichi?
/llms.txt not found
Create a /llms.txt file at your site root following the llmstxt.org specification. It should be a Markdown file starting with "# Your Site Name" and include a description, sections, and links.
No AI meta tags (ai:*) found
Add AI meta tags to your HTML <head>: <meta name="ai:summary" content="Brief description">, <meta name="ai:content_type" content="website">, <meta name="ai:author" content="Your Name">.
No rel="alternate" link to llms.txt in HTML
Add to your <head>: <link rel="alternate" type="text/plain" href="/llms.txt" title="LLM-optimized content">
No rel="alternate" link to the Agent Card in HTML
Add to your <head>: <link rel="alternate" type="application/json" href="/.well-known/agent-card.json" title="Agent Card">
No rel="me" identity links found
Add rel="me" links to verify your identity across platforms: <link rel="me" href="https://github.com/yourname">, <link rel="me" href="https://twitter.com/yourname">.
OpenGraph required tags present (og:title, og:description, og:url, og:type)
Twitter Card required tags present (twitter:card, twitter:title, twitter:description)
/robots.txt exists
8/12 core AI crawlers configured
Add explicit User-agent entries for the missing crawlers with Allow: / for each one.
12 AI crawler(s) explicitly blocked
These crawlers have "Disallow: /" rules. If you want AI agents to access your site, change to "Allow: /" for each blocked crawler.
3 assistant search crawler(s) blocked — your site cannot be cited by those assistants
Search crawlers build the index an assistant cites from; they are separate from the training crawlers. If the intent was to opt out of training only, allow these and block the training tokens instead.
7 training crawler(s) blocked — recorded as a deliberate policy choice
1 user-triggered fetcher(s) blocked in robots.txt that may ignore it
These clients fetch a page because a person asked for that URL, and their vendors document that robots.txt may not apply. Enforce at the edge if the block must hold.
1 robots.txt rule(s) target a retired or non-existent crawler token
These rules have no effect. Remove them so the file reflects your actual policy.
Sitemap directive present
No Content-Signal directive found (optional)
Declare how crawlers may use your content after access with the Content Signals Policy, e.g.: Content-Signal: search=yes, ai-train=no. Known signals: search, ai-input, ai-train, plus the optional use=immediate|reference|full. Generate yours at contentsignals.org.
12/57 known AI crawlers have explicit rules
4/7 security headers present
No Link header for AI discovery (llms.txt, Agent Card)
Add a Link response header pointing to your AI discovery files: Link: </llms.txt>; rel="alternate"; type="text/plain", </.well-known/agent-card.json>; rel="alternate"; type="application/json"
No machine-readable discovery relations beyond llms.txt and the Agent Card
Advertise what you publish with Link relations so agents stop guessing paths. Add the ones that apply, for example: Link: </llms.txt>; rel="describedby", </.well-known/api-catalog>; rel="api-catalog". Informational in 3.x: this does not affect your score.
Sitemap located: https://www.figma.com/sitemap.xml
Content-Type is XML (application/xml)
Sitemap-index references 11 child sitemap(s)
3/3 sample child sitemap(s) reachable
Sample yielded 6237 URL(s) across 3 child(ren)
Newest <lastmod> is recent (1 day(s) ago)
Che cosa può chiamare un agente?
/.well-known/agent-card.json not found
This site offers something an agent could call, but nothing tells an agent what. Publish an A2A Agent Card at /.well-known/agent-card.json. A minimal 1.0 card needs name, description, version, capabilities, supportedInterfaces, defaultInputModes, defaultOutputModes and skills. Spec: https://a2a-protocol.org/latest/specification/
API surface present but no machine-readable description found
The API exists; nothing describes it in a form an agent can read, so using it requires a human to read your documentation first. Serve an OpenAPI description at /openapi.json and advertise it with Link: </openapi.json>; rel="service-desc". For several APIs, publish an RFC 9727 catalog.
No agent resource catalog found
A catalog is one document listing everything an agent can call here — agent cards, MCP servers, APIs, skills — so a client stops probing four conventions to find out. Worth publishing once you have more than one of those. Informational: both ai-catalog.json and ard.json are still drafts, so this never affects your score.
No Agent Skills published
This site has documentation, so it has procedures worth teaching. A skill is a SKILL.md an agent installs and follows: setup steps, argument shapes, the mistakes to avoid. Publish one per task at /.well-known/agent-skills/{name}/SKILL.md and list them in /.well-known/agent-skills/index.json.
No MCP server — MCP discovery does not apply to this site
No forms and no WebMCP code — nothing here for an agent to invoke as a tool
No commerce surface — agentic-commerce discovery does not apply to this site
Nothing on this site requires authorization — auth discovery does not apply
Quali diritti d'uso sono dichiarati?
No RSL license discovery found
Declare machine-readable licensing terms for your content with Really Simple Licensing. Add to robots.txt: License: https://your-site.com/license.xml — then publish the RSL document. See https://rslstandard.org.
No machine-readable usage policy declared
State your terms where they can be read without a lawyer. The lowest-effort option is a Content-Signal line in robots.txt: Content-Signal: search=yes, ai-input=yes, ai-train=no. Absence is neutral, not permission — but it also gives you nothing to point at.
/.well-known/security.txt exists
Required field "Contact" present
Required field "Expires" present
Expires date is in the future (2026-10-21)
2/5 optional fields present
Dai al team rapporti completi, correzioni prioritarie e monitoraggio per mantenere i miglioramenti dopo ogni rilascio.