evolving-ai-agents
Category: llm-applications · License: MIT · Version: 1.0.0
Tags: Agent Evolution, Self-Improving Agents, Prompt Optimization, LLM, Benchmark Evaluation, Skill Discovery, Agentic AI
When to use it
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.Example requests
Ask your agent in plain language, for example:- “Can I automatically evolve my agent’s prompts and skills against a benchmark?”
- “I have a custom agent in ./my_agent with a BaseAgent subclass and a 200-task internal QA dataset scored 0-1. I ran 3 evolution cycles and it reported converged=True, but the agent doesn’t seem to use the evolved prompts/system.md. How do I fix both problems?”
- “I want my coding assistant to get better at fixing GitHub issues over time without me hand-tuning anything. It should try tasks, look at where it failed, rewrite its own instructions and reusable procedures, and roll back changes that make things worse. How do I set that up?”
Install
/plugin marketplace add KalarisLabs/research-agent-skills and install the whole llm-applications category with /plugin install llm-applications@research-agent-skills.