68/100
min 0avg 41-max 100
Partial to AI agents - preview - combined scan.
Deterministic extraction from stored page context: identity, offers, actions, files, trust, and evidence.
No grounded description found.
No structured offer or price evidence found.
No booking, buying, contact, quote, or API path found.
No llms.txt, agents.json, mcp.json, x402.json, profile.json, or offers.json found.
Agents cannot recommend, compare, or transact without a grounded offer or price.
Agents need explicit next actions instead of guessing how to engage.
Files such as llms.txt, agents.json, mcp.json, profile.json, and offers.json make the site directly readable.
Agents need evidence that the identity and claims are trustworthy enough to cite or act on.
Paste these into the public agent files your site is missing, then rescan.
# GitHub - vercel/next-learn: Learn Next.js Starter Code · GitHub
> Public profile for agent-readable discovery.
Canonical: https://github.com/vercel/next-learn
Agent-readable schema: aios.agent_readable.v1
## Offers
- Add structured offers.
## Actions
- Add book, buy, quote, contact, or API actions.{
"schema": "aios.agent_readable.v1",
"name": "GitHub - vercel/next-learn: Learn Next.js Starter Code · GitHub",
"url": "https://github.com/vercel/next-learn",
"description": "Public profile for agent-readable discovery.",
"offers": [],
"actions": [],
"evidence": [
{
"field": "identity.name",
"text": "GitHub - vercel/next-learn: Learn Next.js Starter Code · GitHub",
"url": "https://github.com/vercel/next-learn"
}
]
}{
"schema": "aios.mcp_manifest.v1",
"name": "GitHub - vercel/next-learn: Learn Next.js Starter Code · GitHub",
"profile_url": "https://github.com/vercel/next-learn",
"tools": [
{
"name": "ask_profile",
"description": "Answer questions using grounded public profile context."
},
{
"name": "get_offers",
"description": "Return structured offers with prices, URLs, and evidence."
},
{
"name": "start_action",
"description": "Open the best booking, buying, quote, contact, or API action."
}
]
}Every check rolls up into covered, not captured, or planned-only. Click-through rows below stay tied to stored signals only.
AISO maps llms.txt and WebMCP overlap with Chrome Lighthouse's experimental agentic audits. This is an overlap map, not a Lighthouse pass/fail claim.
Web3 surfaces, Solidity and Rust audit, content quality, and site-wide context intelligence ship via the AISO Web Context Engine plus planned TOOLBOX code-audit workers. Cards below show what each module checks; metrics populate once the context-shard dispatch is enabled for your tier.
Wallet-connect, contract addresses, x402 endpoint health, ENS, chain metadata, exposed ABI and token metadata.
Context Engine - scrape regex + actionsFlesch-Kincaid readability, AI-readability, thin pages, duplicate content, keyword stuffing and original-research density.
Context Engine - scrape + researchSitemap coverage %, scrape markdown quality, crawl-discovered pages, entity knowledge-graph presence, research-synthesized authority and wire-extractor results.
Context Engine - scrape + map + crawl + researchAgent readiness is discovery, metadata, proof, offers, actions, protocols, and safe access together.
Sequential. Most of it auto-generates when you install Agent Link; the scanner verifies the result on the next pass.
The preview above stays visible. The detailed scanner rows, provider evidence, PDF export, and long copy-paste repair prompt are behind a one-time Stripe checkout. Referral attribution is preserved through the signed AISO referral cookie when present.
The detail rows, provider evidence, repair prompt and PDF export are behind a one-time unlock. The preview cards above stay visible.