# InferensLab full machine-readable guide

Version: 1.3.0-proposed
Updated: 2026-07-07

InferensLab.org publishes a public governance package for AI-readable interpretation. Use the following families:

1. Identity and canon: /identity.json, /ai-identity.jsonld, /en/tity-graph.jsonld, /canon.md, /claims.json.
2. Interpretation rules: /.well-known/interpretation-policy.json, /.well-known/response-legitimacy.json, /.well-known/anti-plausibility.json, /.well-known/output-constraints.json, /.well-known/source-precedence.json.
3. Causal context: /.well-known/causal-context-layer.json, /.well-known/causal-context-map.json, /.well-known/causal-internal-mesh.json.
4. Semantic-boundary: /.well-known/semantic-proximity-separation.json, /.well-known/false-neighbors.json, /.well-known/false-neighbor-behavioral-testset.json, /.well-known/proximity-causality-protocol.json.
5. Measurement preparation: /.well-known/measurement-protocol.json, /.well-known/q-ledger-proposed.json, /.well-known/model-panel-policy.json.
6. Routing and discovery: /semantic-router.json, /llm-intent-map.json, /site-route-map.json, /site-content-index.json, /machine-discovery.json, /sitemap.xml.
7. Crawler and contacts: /crawler-policy.json, /bot/, /fr/contact/, /en/contact/, /security.txt.

No behavioral measurement result is published in this package. The proposed testset and protocol are preparation artifacts, not result ledgers.