Summary
Use relay metadata (NIP-11 capabilities, NIP-66 health, paid vs free, estimated retention window) as features to estimate relay quality for new/unseen relays without exploring from scratch.
Why
When a new relay appears in someone's NIP-65 list, the current algorithms have no prior information — they must explore it from zero. Relay metadata provides useful signals: a paid relay with NIP-11 advertising unlimited retention is likely better for archival than a free relay with no retention claim. NIP-66 liveness data can pre-filter dead relays. These contextual features would reduce the cold-start problem.
What to do
- Collect NIP-11 info and NIP-66 health data for all relays in the dataset
- Define features: paid/free, retention policy, NIP-66 online/offline/dead status, supported NIPs
- Use features to initialize MAB priors (contextual bandits) or as multipliers in scoring
- Benchmark against feature-blind algorithms across all 6 time windows
Effort
Higher — requires fetching and parsing NIP-11/NIP-66 data, defining feature encoding, and integrating into the scoring pipeline.
Reference
- IMPLEMENTATION-GUIDE.md: Improvement Opportunities (higher effort)
- IMPLEMENTATION-GUIDE.md §3: Pre-filter relays with NIP-66
Summary
Use relay metadata (NIP-11 capabilities, NIP-66 health, paid vs free, estimated retention window) as features to estimate relay quality for new/unseen relays without exploring from scratch.
Why
When a new relay appears in someone's NIP-65 list, the current algorithms have no prior information — they must explore it from zero. Relay metadata provides useful signals: a paid relay with NIP-11 advertising unlimited retention is likely better for archival than a free relay with no retention claim. NIP-66 liveness data can pre-filter dead relays. These contextual features would reduce the cold-start problem.
What to do
Effort
Higher — requires fetching and parsing NIP-11/NIP-66 data, defining feature encoding, and integrating into the scoring pipeline.
Reference