AgileRL logo
AgileRL
★ 959
vs
cap-evolve logo
cap-evolve
★ 66

AgileRL vs cap-evolve

AgileRL: AgileRL is a Deep Reinforcement Learning library that streamlines development by introducing RLOps, or MLOps for reinforcement learning. It significantly reduces training time and hyperparameter optimization using pioneering evolutionary techniques, offering up to 10x faster optimization than state-of-the-art methods.; cap-evolve: cap-evolve is an honesty-guaranteed framework that optimizes AI agent capabilities like prompts, tools, and skills by learning from failed evaluation traces. It automates the loop of evaluation, diagnosis, candidate generation, and validation, ensuring improvements are significant and honest.

01

TL;DR

AgileRL logo
AgileRLLLM Infra · ★ 959

Training single-agent tasks in standard Gymnasium environments.

cap-evolve logo
cap-evolveLLM Infra · ★ 66

Optimizing AI agent capabilities when developing with Claude Code plugin.

02

Side-by-Side Comparison

Field
AgileRL logoAgileRL
cap-evolve logocap-evolve
Category
LLM Infra
LLM Infra
Stars
★ 959
★ 66
License
Apache-2.0
Apache-2.0
Install Command
pip install agilerl
git clone https://github.com/skillberry-ai/cap-evolve.git && cd cap-evolve && python3 -m venv .venv && source .venv/bin/activate && pip install ./core
Updated
1d ago
1d ago
Open Source
Yes
Yes
Tags
Reinforcement Learning, Deep Learning, Hyperparameter Optimization
AI Agent Optimization, Prompt Engineering, Tool Code Optimization
03

Features

AgileRL logoAgileRL
01RLOps integration for streamlined reinforcement learning development.
02Pioneering evolutionary hyperparameter optimization (HPO) techniques.
03Comprehensive suite of evolvable on-policy, off-policy, offline, multi-agent, and contextual multi-armed bandit algorithms.
04Support for distributed training.
05Algorithms for Large Language Model (LLM) finetuning.
cap-evolve logocap-evolve
01Optimizes more than prompts, including executable tool code and entire skill packages.
02Learns from real agent failures and per-task causal feedback to make robust improvements.
03Ensures honest evaluation through a significance gate and a sealed, scored-once test split.
04Provides a dashboard to inspect every change, cost, timing, diff, and pass/fail heatmap.
04

Use Cases

AgileRL logoAgileRL
↳Training single-agent tasks in standard Gymnasium environments.
↳Developing multi-agent reinforcement learning solutions in PettingZoo environments.
↳Fine-tuning Large Language Models (LLMs) with reinforcement learning algorithms.
cap-evolve logocap-evolve
↳Optimizing AI agent capabilities when developing with Claude Code plugin.
↳Integrating and refining agents from various coding-agent hosts like Codex, Gemini, or Droid.
↳Custom integration for developers who want to wire their own agent adapters and drive the CLI directly.
↳Applying pre-built adapter templates for popular benchmarks and data formats (e.g., JSONL, HuggingFace, tau2-bench).
05

Best For

AgileRL logoAgileRL
TrendingHidden Gem
cap-evolve logocap-evolve
—
FAQ

FAQ

What is the difference between AgileRL and cap-evolve?
Both AgileRL and cap-evolve are in the LLM Infra category. AgileRL has 959 stars, while cap-evolve has 66 stars.
Which is better, AgileRL or cap-evolve?
The best choice depends on your use case. Choose AgileRL if Training single-agent tasks in standard Gymnasium environments., and cap-evolve if Optimizing AI agent capabilities when developing with Claude Code plugin..
Is AgileRL free or open source?
Yes, AgileRL is open source on GitHub (Apache-2.0).
Is cap-evolve free or open source?
Yes, cap-evolve is open source on GitHub (Apache-2.0).
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