agent-lightning

Automate AI agent training setup and optimization with the Agent Lightning framework.

264|11|Updated Apr 25, 2026
One-click install
npx skills add https://github.com/rkz91/coco --skill agent-lightning
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-lightning
Source: https://github.com/rkz91/coco/tree/main/skills/agent-lightning
Command: npx skills add https://github.com/rkz91/coco --skill agent-lightning

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Train and optimize AI agents using the Agent Lightning framework to streamline training, tracing, resource management, and reward design across multi-agent pipelines.

Core Features & Use Cases

  • Architecture Flow and central tracing with LightningStore for scalable agent training.
  • Instrumentation of agent code with emit_xxx calls for observability and reward signals.
  • Support for Reinforcement Learning (GRPO/PPO) and Automatic Prompt Optimization (APO) workflows, plus framework adapters.
  • End-to-end trainer configuration and customization with configurable runners, algorithms, and stores.

Quick Start

Install the package, configure a minimal trainer with a simple store, and run a basic training loop.

Frequently Asked Questions about agent-lightning

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I set up multi-agent pipelines for AI training and tracing?▼

To set up multi-agent pipelines for AI training and tracing, configure a trainer with LightningStore as the central tracing hub, then execute a basic training loop to automate scalable agent training and resource management.

What is the best way to instrument agent code for observability and reward signals?▼

The best way to instrument agent code for observability and reward signals is to integrate emit_xxx calls directly into your pipeline, enabling detailed logging and evaluation for reinforcement learning workflows.

Can I use GRPO and PPO algorithms for automatic prompt optimization in multi-agent systems?▼

Yes, you can use GRPO and PPO algorithms for automatic prompt optimization in multi-agent systems by configuring the framework adapters to support both reinforcement learning and APO workflows.

How does LightningStore support scalable agent training and instrumentation?▼

LightningStore supports scalable agent training by acting as a central tracing store for architecture flow, capturing instrumentation data from emit_xxx calls to ensure comprehensive observability and reward signal tracking.

Do I need specific framework adapters to run reinforcement learning and APO workflows?▼

Yes, you need modular framework adapters to run reinforcement learning and APO workflows, as these adapters ensure proper integration with configurable runners, algorithms, and stores for end-to-end trainer customization.