Hermes Agent Self Evolution
Description
⚒ Evolutionary self-improvement for Hermes Agent — optimize skills, prompts, and code using DSPy + GEPA
Installation
This entry records only its repository, not the path inside it, so there is no
exact command to give. Open the source below and copy the folder into
~/.claude/skills/, or the file into ~/.claude/agents/.
README
🧬 Hermes Agent Self-Evolution
**Evolutionary self-improvement for [Hermes Agent](https://github.com/NousResearch/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.
How It Works
Read current skill/prompt/tool ──► Generate eval dataset
│
▼
GEPA Optimizer ◄── Execution traces
│ ▲
▼ │
Candidate variants ──► Evaluate
│
Constraint gates (tests, size limits, benchmarks)
│
▼
Best variant ──► PR against hermes-agent
GEPA reads execution traces to understand *why* things fail (not just that they failed), then proposes targeted improvements. ICLR 2026 Oral, MIT licensed.
Quick Start
# Install
git clone https://github.com/NousResearch/hermes-agent-self-evolution.git
cd hermes-agent-self-evolution
pip install -e ".[dev]"
# Point at your hermes-agent repo
export HERMES_AGENT_REPO=~/.hermes/hermes-agent
# Evolve a skill (synthetic eval data)
python -m evolution.skills.evolve_skill \
--skill github-code-review \
--iterations 10 \
--eval-source synthetic
# Or use real session history from Claude Code, Copilot, and Hermes
python -m evolution.skills.evolve_skill \
--skill github-code-review \
--it
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