hermes-agent-self-evolution — Awesome Hermes Agent Ecosystem

Why it matters

Profile

Evolutionary self-improvement using DSPy and GEPA (Genetic Evolution of Prompt Architectures). The research pipeline for optimizing Hermes's own prompts and behaviors.

setup mediumintegration highinterface cli

Provenance

Signals

Listed in the awesome-hermes-agent README

Sources: 2 / Surfaces: 1

Fast skim

What the upstream surface says

Short excerpt only, so you can decide whether to click out.

Evolutionary self-improvement for Hermes Agent.

Hermes Agent Self-Evolution uses DSPy + GEPA (Genetic-Pareto Prompt Evolution) to automatically evolve and optimize Hermes Agent's skills, tool descriptions, system prompts, and code — producing measurably better versions through reflective evolutionary search.

No GPU training required. Everything operates via API calls — mutating text, evaluating results, and selecting the best variants. ~$2-10 per optimization run.

🧬 Hermes Agent Self-EvolutionHow It WorksQuick StartInstallPoint at your hermes-agent repoEvolve a skill (synthetic eval data)Or use real session history from Claude Code, Copilot, and HermesWhat It Optimizes

Full test suite — pytest tests/ -q must pass 100%
Size limits — Skills ≤15KB, tool descriptions ≤500 chars
Caching compatibility — No mid-conversation changes
Semantic preservation — Must not drift from original purpose
PR review — All changes go through human review, never direct commit