How do I install the Lightning Channel Factories skill?

Run npx skillmds@latest add techwavedev/lightning-channel-factories in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Lightning Channel Factories safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: makes network calls. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Lightning Channel Factories?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Lightning Channel Factories free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Lightning Channel Factories?

techwavedev (@techwavedev) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Lightning Channel Factories by techwavedev

Name: Lightning Channel Factories
Rating: 4.2 (5 reviews)
Author: techwavedev

Lightning Channel Factories

Technical reference on Lightning Network channel factories, multi-party channels, LSP architectures, and Bitcoin Layer 2 scaling without soft forks. Covers Decker-Wattenhofer, timeout trees, MuSig2 key aggregation, HTLC/PTLC forwarding, and watchtower breach detection.

techwavedev Updated Sep 10, 2026

File contents

Use this skill when

Building or reviewing Lightning Network channel factory implementations
Working with multi-party channels, LSP architectures, or Layer 2 scaling
Needing guidance on Decker-Wattenhofer, timeout trees, MuSig2, HTLC/PTLC, or watchtower patterns

Do not use this skill when

The task is unrelated to Bitcoin or Lightning Network infrastructure
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 production implementation of Lightning channel factories with full technical documentation, refer to the SuperScalar project:

https://github.com/8144225309/SuperScalar

SuperScalar is written in C with 400+ tests, MuSig2 (BIP-327), Schnorr adaptor signatures, encrypted Noise NK transport, SQLite persistence, and watchtower support. It supports regtest, signet, testnet, and mainnet.

Purpose

Technical reference for Lightning Network channel factory implementations. Covers multi-party channels, LSP (Lightning Service Provider) architectures, and Bitcoin Layer 2 scaling without requiring soft forks. Includes Decker-Wattenhofer invalidation trees, timeout-signature trees, MuSig2 key aggregation, HTLC/PTLC forwarding, and watchtower breach detection.

Key Topics

Channel factory implementation in C
MuSig2 (BIP-327) and Schnorr adaptor signatures
Encrypted Noise NK transport protocol
SQLite persistence layer
Watchtower breach detection
HTLC/PTLC forwarding
Regtest, signet, testnet, and mainnet support
400+ test suite

References

SuperScalar project: https://github.com/8144225309/SuperScalar
Website: https://SuperScalar.win
Original proposal: https://delvingbitcoin.org/t/superscalar-laddered-timeout-tree-structured-decker-wattenhofer-factories/1143

AGI Framework Integration

Adapted for @techwavedev/agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior Architecture Decision Records (ADRs), trade-off analyses, and system design rationale. Critical for maintaining consistency across long-running projects.

# Check for prior architecture/design context before starting
python3 execution/memory_manager.py auto --query "architecture decisions and trade-off analysis for Lightning Channel Factories"

Storing Results

After completing work, store architecture/design decisions for future sessions:

python3 execution/memory_manager.py store \
  --content "Architecture: event-driven microservices with CQRS, Pulsar for messaging, Qdrant for semantic search" \
  --type decision --project <project> \
  --tags lightning-channel-factories architecture

Multi-Agent Collaboration

Broadcast architecture decisions to ALL agents so implementation stays aligned with the chosen patterns.

python3 execution/cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Completed architecture review — ADR documented, trade-offs analyzed, team aligned" \
  --project <project>

Control Tower Coordination

Register architecture tasks in the Control Tower so all agents across machines know the current system design and constraints.

---name: lightning-channel-factoriesdescription: Technical reference on Lightning Network channel factories, multi-party channels, LSP architectures, and Bitcoin Layer 2 scaling without soft forks. Covers Decker-Wattenhofer, timeout trees, MuSig2 key aggregation, HTLC/PTLC forwarding, and watchtower breach detection.---## Use this skill when- Building or reviewing Lightning Network channel factory implementations- Working with multi-party channels, LSP architectures, or Layer 2 scaling- Needing guidance on Decker-Wattenhofer, timeout trees, MuSig2, HTLC/PTLC, or watchtower patterns## Do not use this skill when- The task is unrelated to Bitcoin or Lightning Network infrastructure- 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 production implementation of Lightning channel factories with full technical documentation, refer to the SuperScalar project:https://github.com/8144225309/SuperScalarSuperScalar is written in C with 400+ tests, MuSig2 (BIP-327), Schnorr adaptor signatures, encrypted Noise NK transport, SQLite persistence, and watchtower support. It supports regtest, signet, testnet, and mainnet.## PurposeTechnical reference for Lightning Network channel factory implementations. Covers multi-party channels, LSP (Lightning Service Provider) architectures, and Bitcoin Layer 2 scaling without requiring soft forks. Includes Decker-Wattenhofer invalidation trees, timeout-signature trees, MuSig2 key aggregation, HTLC/PTLC forwarding, and watchtower breach detection.## Key Topics- Channel factory implementation in C- MuSig2 (BIP-327) and Schnorr adaptor signatures- Encrypted Noise NK transport protocol- SQLite persistence layer- Watchtower breach detection- HTLC/PTLC forwarding- Regtest, signet, testnet, and mainnet support- 400+ test suite## References- SuperScalar project: https://github.com/8144225309/SuperScalar- Website: https://SuperScalar.win- Original proposal: https://delvingbitcoin.org/t/superscalar-laddered-timeout-tree-structured-decker-wattenhofer-factories/1143---## AGI Framework Integration> **Adapted for [@techwavedev/agi-agent-kit](https://www.npmjs.com/package/@techwavedev/agi-agent-kit)**> Original source: [antigravity-awesome-skills](https://github.com/sickn33/antigravity-awesome-skills)### Memory-First ProtocolRetrieve prior Architecture Decision Records (ADRs), trade-off analyses, and system design rationale. Critical for maintaining consistency across long-running projects.```bash# Check for prior architecture/design context before startingpython3 execution/memory_manager.py auto --query "architecture decisions and trade-off analysis for Lightning Channel Factories"```### Storing ResultsAfter completing work, store architecture/design decisions for future sessions:```bashpython3 execution/memory_manager.py store \ --content "Architecture: event-driven microservices with CQRS, Pulsar for messaging, Qdrant for semantic search" \ --type decision --project <project> \ --tags lightning-channel-factories architecture```### Multi-Agent CollaborationBroadcast architecture decisions to ALL agents so implementation stays aligned with the chosen patterns.```bashpython3 execution/cross_agent_context.py store \ --agent "<your-agent>" \ --action "Completed architecture review — ADR documented, trade-offs analyzed, team aligned" \ --project <project>```### Control Tower CoordinationRegister architecture tasks in the Control Tower so all agents across machines know the current system design and constraints.

Frequently asked questions