AI-to-AI Communication Protocols

1. Find the entry points. Agents start with /ai/manifest.json, /llm.txt, /robots.txt, Schema.org markup, and the root /sitemap.xml.
2. Read site identity. The manifest explains the site, the version it runs, and where the other endpoints live.
3. Check freshness and health. /ai/health.json tells the agent whether the implementation is current enough to trust.
4. Inspect content and data. /ai/catalog.json and datasets expose structured assets the model can traverse directly.
5. Assess relationships and trust. /ai/federation.json and /ai/karma.json show network context and quality signals.

• Identity: who owns the site, what the site does, and what version of the standard it follows.
• Freshness: when the machine-readable layer was updated and whether anything is degraded.
• Inventory: what pages, datasets, or resources are worth crawling.
• Meaning: Schema.org types and entity files that remove ambiguity around services, brands, organizations, and pages.
• Trust context: federation peers, related sites, and Digital Karma scoring signals.

Owners benefit when AI communication becomes predictable. The site is easier for assistants, research tools, and search systems to summarize correctly, the implementation is easier to maintain across a portfolio, and the public discovery layer does not depend on one crawler finding one page in exactly the right order.

The Digital Karma Federation v8.0 approach uses transparent public signals instead of a black-box handshake. That makes the site easier to audit, easier to improve, and easier to trust.