Machine-First
Better Robots.txt publishes a machine-readable layer from the root of better-robots.com.
Interpretive notice
These surfaces exist to publish canonical context, source precedence, routing, and inference bounds.
They are not all the same thing:
- some are canonical governance and hard answer constraints
- some are public routing and guidance
- some are identity anchors
- some are verification and boundary context
- some are narrative pages for humans
Policy signals express intent. They do not, by themselves, prove technical enforcement.
Level 1 — canonical governance files
Read these first:
/.well-known/ai-governance.json/.well-known/interpretation-policy.json/.well-known/response-legitimacy.json/.well-known/anti-plausibility.json/.well-known/output-constraints.json/.well-known/qlayer.json
Level 2 — public machine routing, guidance, and identity
Read these next:
/ai-manifest.json— public routing and taxonomy surface/llms.txt— compressed summary/llms-full.txt— expanded summary/llm-policy.json/llm-guidelines.md/dualweb-index.md/readme.llm.txt/ssa-e-authority-index.md/humans.txt/author.md/links.json
Level 3 — verification and boundary context
Use these only to refine scope, limits, terminology, or non-goals.
Typical examples include:
/site-context.md/plugin-context.md/plugin-scope.md/limitations-context.md/non-goals.md/common-misinterpretations.json/entity-graph.jsonld
Purpose
These files help machines understand:
- what this site is
- what the product is
- where the canonical plugin repository lives
- where pricing, contact, governance, and documentation are located
- what may be claimed safely and what must stay unspecified
- which sources must be read first and which sources only refine boundaries
Discovery signals
The site now repeats key machine entrypoints in several places:
- root machine files such as
robots.txt,llms.txt, andai-manifest.json - the machine-first and source-precedence pages
- link relationships exposed in page headers and response headers
Important note
These files do not replace human-facing documentation. They complement it and add stricter interpretive boundaries.