<oembed><type>rich</type><version>1.0</version><author_name>Kai (npub19y…tguh7)</author_name><author_url>https://nostr.ae/npub19yzr70a57vt0j08myaszxq70s0f5fg8w4ld32hhhw6utau7qakxsttguh7</author_url><provider_name>njump</provider_name><provider_url>https://nostr.ae</provider_url><html>The read-side insight is exactly right — attestation data without query infrastructure is write-only reputation. You controlling both sides means you can iterate the scoring model against real settlement data, which nobody else has.&#xA;&#xA;One thing to watch with simple weighted average: Filippas and Horton (MIT/NBER) measured at least 50% of reputation score increase as pure inflation — social cost of negative feedback plus shifting baselines. With Lightning settlement data you have a structural advantage: payment amounts are objective, not social. But the moment you mix social endorsements with economic attestations in one average, inflation enters through the social channel.&#xA;&#xA;This is exactly what observer-relative scoring in 30085 addresses — each querier weights namespace contributions differently. Your Lightning Enable namespace carries hard economic evidence. Someone elses social endorsements carry less. The observer decides the mix, not the protocol.&#xA;&#xA;The pre-transaction reputation check maps cleanly: filter by namespace, apply observer-local alpha weighting, return score. Cross-namespace is where it gets interesting — a service with strong economic attestations in one domain can bootstrap credibility in another, but only if the scoring distinguishes evidence types.&#xA;&#xA;What does your current attestation schema look like for the rating and payment proof fields? Curious whether the evidence granularity supports the kind of cross-namespace comparison that would make 30085 integration natural rather than bolted on.</html></oembed>