# Airadar (airadar.run): agent-readiness 56/100, grade D

> Rank 628 of 1000 on Qomvia (rubric v2.3.0). Last scanned 2026-10-04T20:40:43.470Z. Page: https://qomvia.com/site/airadar-run  JSON: https://qomvia.com/api/score/airadar-run

## Summary
Category: Software and SaaS
{
  "known": false,
  "confidence": "high",
  "summary": "I do not recognize this website and have no information about airadar.run from my training data. Therefore, I cannot provide details on its offerings, audience, or operations.",
  "offerings": [],
  "audience": null,
  "geography": null,
  "strengths": [],
  "unknowns": [
    "Specific services and features offered by airadar.run",
    "Its target customer segments and geographical focus",
    "Its pricing models and business structure",
    "Key differentiators and competitive advantages",
    "Company history, funding, and team leadership"
  ],
  "alternatives": [],
  "business": null,
  "competitors": []
}

## Score by group
- Machine access: 24/24
- Content legibility: 19/26
- Discovery surface: 5/20
- Identity & policy: 0/12
- Agent-facing performance: 8/8
- Agent protocols: 0/10
Failing checks:
- [blocker] No llms.txt
- [blocker] The site does not say who it is
- [blocker] No API or feed to read
- [blocker] No MCP endpoint to call
- [improvement] Title, description and canonical URL

## Add-on packs
- E-commerce & product feeds: 15/100 (not part of the public score)

## AI mentions and rivals
Named in 4 AI assistant answers.


## Named for
- Which platforms help e-commerce businesses become visible and actionable for AI shopping agents? https://qomvia.com/answers/which-platforms-help-e-commerce-businesses-become-visible-and-actionable-for-ai

## FAQ
Q: Is Airadar readable by AI agents?
A: Airadar (airadar.run) scores 56 out of 100 for agent readiness, grade D, measured 6 days ago, on 04.10.2026. 0 of 3 agent classes we test can use the site, and 4 checks currently block agents outright.

Q: What stops agents from using airadar.run?
A: The heaviest problems are: No llms.txt; The site does not say who it is; No API or feed to read; No MCP endpoint to call; Title, description and canonical URL. Each one is scored from a public HTTP response, and the fix for each is listed in the signed-in report.

Q: How is the Airadar agent-readiness score calculated?
A: Qomvia fetches public pages of airadar.run 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. E-commerce & product feeds checks are scored separately (15/100) and do not affect the public score or rank.

Q: How often is this score updated?
A: 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 6 days ago, on 04.10.2026.

## Related
- Leaderboard: https://qomvia.com/leaderboard — category ranking: https://qomvia.com/leaderboard/saas-software
- Score another site: https://qomvia.com/