hermes-agent-self-evolution
⚒ Evolutionary self-improvement for Hermes Agent — optimize skills, prompts, and code using DSPy + GEPA
Hermes Agent Self-Evolution is an evolutionary optimization system that automatically improves Hermes Agent's skills, prompts, tool descriptions, and code through reflective search algorithms. Built on DSPy and GEPA (Genetic-Pareto Prompt Evolution), it analyzes execution traces to understand failure modes and generates targeted improvements without requiring GPU training. The system operates entirely via API calls, costs approximately $2-10 per optimization run, and enforces strict guardrails including full test suite validation and human code review before merging changes.
Key Features
Use Cases
- 01Automatically refining GitHub code review skills based on real developer session traces
- 02Optimizing tool descriptions to improve agent understanding and task execution accuracy
- 03Evolving system prompt sections to reduce errors and improve response quality
- 04Running iterative improvement cycles on custom skills added to Hermes Agent
- 05Analyzing failure patterns in agent execution logs to identify systematic weaknesses
- 06Creating measurably better agent variants through constraint-gated evolutionary search
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hermes-agent-self-evolution — FAQ
What is Hermes Agent Self-Evolution?+
Hermes Agent Self-Evolution is an automated optimization system for Hermes Agent that uses evolutionary algorithms (DSPy + GEPA) to improve skills, prompts, and code by analyzing execution traces and generating progressively better variants. It was presented as an oral paper at ICLR 2026 and is MIT licensed.
How do I install Hermes Agent Self-Evolution?+
Clone the repository from GitHub, install it with pip install -e ".[dev]", and set the HERMES_AGENT_REPO environment variable to point at your local Hermes Agent installation. You can then run evolution scripts targeting specific skills with configurable iterations and evaluation data sources.
Which AI agents does this work with?+
This system is specifically designed for Hermes Agent by Nous Research. It can use evaluation data from sessions in Claude Code, GitHub Copilot, and Hermes Agent itself, but the optimization outputs target Hermes Agent components exclusively.
Do I need API keys to run this?+
Yes, you need API access for the language models that power DSPy and GEPA optimization. The system operates entirely via API calls rather than local GPU training, with typical costs of $2-10 per optimization run.
Is Hermes Agent Self-Evolution free?+
The software itself is MIT licensed and free to use. However, running optimizations incurs API costs (approximately $2-10 per run) for the language model calls that power the evolutionary search process.
What can this optimize in Hermes Agent?+
Currently it optimizes skill files (SKILL.md). Planned phases include tool descriptions, system prompt sections, tool implementation code, and eventually a continuous improvement loop. All changes go through automated testing and human code review before being merged.
How do I install hermes-agent-self-evolution?+
Open the source repository on GitHub and follow its README. hermes-agent-self-evolution is a agent — MCP Agents Market links you directly to the official repo.
Is hermes-agent-self-evolution free?+
hermes-agent-self-evolution is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.