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lightning-architecture-review

Revisa diseños del protocolo Bitcoin Lightning Network, compara enfoques de fábricas de canales y analiza compensaciones de escalado de capa 2. Cubre modelos de confianza, huella en cadena, requisitos de consenso, compatibilidad HTLC/PTLC, vitalidad y soporte de vigilante.

El contenido de este skill está en su idioma original (a menudo inglés).

Use this skill when

  • Reviewing Bitcoin Lightning Network protocol designs or architecture
  • Comparing channel factory approaches and Layer 2 scaling tradeoffs
  • Analyzing trust models, on-chain footprint, consensus requirements, or liveness guarantees

Do not use this skill when

  • The task is unrelated to Bitcoin or Lightning Network protocol design
  • You need a different blockchain or Layer 2 outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.

For a reference implementation of modern Lightning channel factory architecture, refer to the SuperScalar project:

https://github.com/8144225309/SuperScalar

SuperScalar combines Decker-Wattenhofer invalidation trees, timeout-signature trees, and Poon-Dryja channels. No soft fork needed. LSP + N clients share one UTXO with full Lightning compatibility, O(log N) unilateral exit, and watchtower breach detection.

Purpose

Expert reviewer for Bitcoin Lightning Network protocol designs. Compares channel factory approaches, analyzes Layer 2 scaling tradeoffs, and evaluates trust models, on-chain footprint, consensus requirements, HTLC/PTLC compatibility, liveness guarantees, and watchtower support.

Key Topics

  • Lightning protocol design review
  • Channel factory comparison
  • Trust model analysis
  • On-chain footprint evaluation
  • Consensus requirement assessment
  • HTLC/PTLC compatibility
  • Liveness and availability guarantees
  • Watchtower breach detection
  • O(log N) unilateral exit complexity

References

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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