Agent-readiness report, Software and SaaS
Agents can read and quote it, but cannot call it as a tool or extract its content.
llmpulse.ai, last scanned 3 days ago, on 27.09.2026
Agent classes working
1/3
Score history
±03 scans since 21.09.2026
1 of 3 agent classes work
Retrieval chunks the page badly, so the passage a model quotes lacks its context.
BlockerTool-calling assistants have no function to call, so they can only scrape.
BlockerCautious platforms will not act on the site without an explicit permission signal.
ImprovementOversized HTML fills the model's context before it reaches the content.
ImprovementAn agent has to parse HTML to find your API catalog, llms.txt or MCP server.
PolishFree dashboard
Weekly re-scans, the fix for every gap above, and the rank moves of your rivals.
Your dashboard
We email you a sign-in link and add llmpulse.ai to your dashboard.
5 domains free, unlimited with a plan.
Llmpulse exposes 7 of 8 interfaces agents look for: AI crawler access, Bot user-agent handling, Server-rendered content, llms.txt, API or feed, Organisation markup, Machine-readable contact.
Locked
All 8 interfaces and 26 checks for llmpulse.ai
See which interface is missing, what each check looked for, and what to change to pass it. Free account, no card.
View detailed signalsThe seal
Agents can complete the site's main task without a human. Paste this line where you want the seal: it is drawn at runtime, so it upgrades itself when you improve and removes itself if a deploy closes the site to agents.
<script src="https://qomvia.com/badge.js" data-slug="llmpulse-ai" async></script>There is no image URL and no static version. The seal exists only as markup we serve per request, which is what makes it worth displaying.
Llmpulse (llmpulse.ai) scores 82 out of 100 for agent readiness, grade B, measured 3 days ago, on 27.09.2026. 1 of 3 agent classes we test can use the site, and 2 checks currently block agents outright.
The heaviest problems are: No heading hierarchy; No MCP endpoint to call; No stated policy for automated access; HTML payload size; No Link headers for agents. Each one is scored from a public HTTP response, and the fix for each is listed in the signed-in report.
Qomvia fetches public pages of llmpulse.ai as an AI agent would and runs the core checks every site gets across 6 groups: Machine access, Content legibility, Discovery surface, Identity & policy, Agent-facing performance, Agent protocols. Checks are weighted by how much an agent loses when they fail, and the score is expressed out of 100.
Public scores are re-checked when the site is re-scanned; tracked domains are re-scanned weekly and their owners are alerted when a check regresses. This page shows the scan from 3 days ago, on 27.09.2026.
Scores are computed from public HTTP responses only. We never submit forms, never attempt a purchase and never bypass a bot challenge. Disagree with a result? Request a correction or opt this domain out.