Autopilot-LND

Autopilot-LND / Autopilot-for-LND

Public

Autopilot-for-LND – TypeScript toolkit for an AI‑assisted Lightning Node autopilot on lnd. Polls channel balance, peer health, and graph signals; scores actions with linear Q‑learning (tabular RL over handcrafted features); emits structured recommendations for channel open/close/fee adjustments. CLI with mock mode, backtesting, historical replay

autopilot bitcoin channel-management cli lightning-network
17
157
85% credibility
Found May 22, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
TypeScript
AI Summary

Autopilot-for-LND is a decision-support toolkit for Lightning Network node operators. It analyzes your node's channels, peers, and network position, then uses a simple AI model to suggest whether you should open new channels, close existing ones, or adjust fee rates. The tool is designed with safety first: it defaults to sample data, only prints recommendations, and requires you to manually approve any changes. You can train the AI on a built-in simulator, test it against historical data, or connect it to your real node in read-only mode to get ongoing suggestions you can review before taking action.

How It Works

1
⚡ You run a Lightning node and want to optimize

You've been running a Lightning node and want to make smarter decisions about which channels to open, close, or adjust fees on.

2
📦 You install the toolkit

You download and set up the Autopilot tool on your computer so it can help analyze your Lightning node.

3
🎮 You try it out with fake data first

The tool comes with built-in sample data, so you can explore how it works without touching your real node at all.

4
🤖 You train the AI brain on a simulator

You let the tool learn patterns on a simulated Lightning network, teaching it which channel decisions tend to work better.

5
You choose how to use it
👁️
Watch mode

The tool continuously monitors your node and streams suggestions as JSON, one per line

⏪
Backtest mode

You replay historical snapshots from your node to test how the policy would have performed

6
🔒 You connect to your real node safely

You point the tool at your actual Lightning node using a read-only key, so it can only read data—not make changes.

✅ You review suggestions and decide for yourself

The tool prints clear recommendations like 'suggest opening a channel to this peer' or 'consider closing this one'—you always stay in control.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 17 to 17 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is Autopilot-for-LND?

Autopilot-for-LND is a TypeScript toolkit that helps Lightning node operators make smarter channel decisions. It polls your node for channel balances, peer health, and network graph data, then uses a lightweight reinforcement learning loop to score four possible actions: do nothing, close your worst channel, raise fees on your hottest channel, or open a new channel to a graph candidate. The CLI emits structured JSON recommendations you can review before touching funds. It ships with mock data for zero-risk experimentation, a built-in simulator for training, and historical replay so you can backtest strategies against past snapshots.

Why is it gaining traction?

This sits squarely in the 2026 Lightning agent tooling wave from Lightning Labs, but focuses on node economics rather than HTTP payments. The reinforcement learning piece is deliberately lightweight—linear Q-learning over eight handcrafted features—running entirely in TypeScript without PyTorch or TensorFlow. You train weights in the simulator, export them as JSON, then load them for live recommendations. The safety model is refreshing: defaults to mock mode, prints suggestions only, and explicitly warns against auto-execution. Graph truncation and macaroon scope warnings show the authors have thought about production pitfalls.

Who should use this?

Lightning node operators tired of manually balancing liquidity will find the recommendation engine useful. Developers building agent-native Lightning applications can wire the JSON output into approval workflows or hardware signer gates. Node runners wanting to backtest fee or rebalancing strategies before committing capital can replay historical snapshots. It's not for casual users—expect to understand channel economics and read the CLI help.

Verdict

Autopilot-for-LND scores 0.85% on credibility with only 17 stars, signaling early-stage project status. That said, the code is clean, tests cover the core logic, and the safety-first design shows maturity beyond the star count. MIT licensed, CI runs on Node 20 and 22. Worth experimenting with for proof-of-concept, but wait for a larger community and more battle-tested policies before trusting it with significant capital.

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.