# Opari (opari.ch): agent-readiness 53/100, grade D

> Rank 630 of 1000 on Qomvia (rubric v2.3.0). Last scanned 2026-09-28T00:50:18.055Z. Page: https://qomvia.com/site/opari-ch  JSON: https://qomvia.com/api/score/opari-ch

## Summary

{
  "known": false,
  "confidence": "low",
  "summary": "I do not have specific information about opari.ch in my knowledge base. Therefore, I cannot provide a detailed summary of what this site is and what it does.",
  "offerings": [],
  "audience": null,
  "geography": null,
  "strengths": [],
  "unknowns": [
    "The specific business model and services offered by Opari.",
    "Its target market and customer base.",
    "Its financial performance and market position.",
    "Its unique selling propositions or competitive advantages.",
    "Its operational scale and geographical reach."
  ],
  "alternatives": [],
  "business": "I do not have specific information about the business model or operations of opari.ch.",
  "competitors": []
}

## Score by group
- Machine access: 21/24
- Content legibility: 15/26
- Discovery surface: 8/20
- Identity & policy: 3/12
- Agent-facing performance: 5/8
- Agent protocols: 1/10
Failing checks:
- [blocker] No llms.txt
- [blocker] No MCP endpoint to call
- [improvement] Title, description and canonical URL
- [improvement] No stated policy for automated access
- [improvement] No machine-readable contact

## FAQ
Q: Is Opari readable by AI agents?
A: Opari (opari.ch) scores 53 out of 100 for agent readiness, grade D, measured 2 days ago, on 28.09.2026. 0 of 3 agent classes we test can use the site, and 2 checks currently block agents outright.

Q: What stops agents from using opari.ch?
A: The heaviest problems are: No llms.txt; No MCP endpoint to call; Title, description and canonical URL; No stated policy for automated access; No machine-readable contact. 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 Opari agent-readiness score calculated?
A: Qomvia fetches public pages of opari.ch 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.

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 2 days ago, on 28.09.2026.

## Related
- Leaderboard: https://qomvia.com/leaderboard
- Score another site: https://qomvia.com/