Write the site thesis.
Define the audience, problem, useful outcome, IN/ADJACENT/OUT boundary and the page job before adding another route.
Open Site FocusA PRACTICAL FIELD GUIDE TO SEARCH & AI DISCOVERY
Start with the problem your site should own. Then improve only the content, evidence and technical surfaces that help people — and machines — solve it.
SITE FOCUS / BEFORE OPTIMIZATION
A useful resource gets weaker when every adjacent topic becomes a first-class section. Scope is part of the product: say what belongs, what stays subordinate and what does not belong here.
THREE PROBLEMS, NOT THIRTY FEATURES
The homepage routes work by problem. Protocols, schemas, tools and research stay available one level deeper instead of competing as separate product identities.
Fix crawlability, discoverable routes, internal structure and the specific technical surfaces that make sense for the site.
Find an applicable pattern → 02 / BE USEDStrengthen original evidence, direct answers, comparisons, data, tools and page structure instead of adding filler.
Improve the useful surface → 03 / BE PROVENSeparate implementation checks from real search, citation, recommendation and useful-action outcomes. Keep neutral results too.
Run the Growth Loop →House heuristic, not a ranking rule: one core problem, up to three first-order lanes, up to five primary navigation destinations and one dominant action per page. Change the architecture when the site's real audience gives you a better reason.
FROM FOCUS TO EVIDENCE
Do less, but make each change explainable: why this page exists, why this pattern applies and what signal will tell you whether it worked.
Define the audience, problem, useful outcome, IN/ADJACENT/OUT boundary and the page job before adding another route.
Open Site FocusSelect a small number of applicable patterns. Keep sources, versions, implementation checks and limitations attached.
Explore the pattern libraryConnect technical checks with actual search, citation and useful-action results. Preserve null and negative outcomes.
Start an improvement loopEVIDENCE MODEL
Goose keeps source support, implementation verification and outcome evidence separate. A technically correct change is not automatically a ranking or recommendation win.
Primary guidance, reviewed research or explicitly labeled project hypothesis.
Generated output, links, semantics, accessibility and repository checks.
Search, citations, recommendations and product actions remain separate observed outcomes.
Unknown, unmeasured and neutral results stay visible rather than being converted into success language.
THE INTEROPERABILITY FOUNDATION
Without a resolver
With ARWP Resolver
node bin/arwp.mjs resolve https://example.com
node bin/arwp.mjs explain https://example.com
node bin/arwp.mjs plan https://example.com --intent=search
node bin/arwp.mjs scan https://example.comnode bin/arwp.mjs init https://example.com
The resolver treats ARWP as one publisher source, not a mandatory universal manifest. Native standards keep their own semantics.
WORKING REFERENCES
Owner-controlled examples are implementation fixtures, not independent adoption evidence.
Loading the public directory…
Publisher profile example
The profile is one explicit source the resolver can consume.
/ai/site-profile.jsonARWP Directory
The directory records current reference sites that publish ARWP.
Search across resolved heterogeneous sites while preserving interface evidence.
View router →The interoperability foundation should earn additions through observed failures and independent evidence, not new AI vocabulary.
Benchmark methodology →RFC, A2A, Agent Skills, MCP, OAuth and API metadata keep their own semantics and authority.
Resolver contract →