#24 · Primary category： Prompt Engineering Tools
hermes-agent-self-evolution
⚒ Evolutionary self-improvement for Hermes Agent — optimize skills, prompts, and code using DSPy + GEPA
Project last updated：06/17/26
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Why we included this project
Building an agent that mostly works but keeps tripping over the same edge cases is a familiar frustration. Hermes Agent Self-Evolution automates the part people usually tune by hand: it reads execution traces to see why a skill or prompt fails, mutates candidate variants, evaluates them, and keeps whichever versions actually score better. Because it runs entirely through API calls rather than GPU training, an optimization run costs roughly two to ten dollars, which puts it in reach for small teams. The implemented path currently covers skill files like SKILL.md, while tool descriptions, system prompt sections, and code evolution are still planned. Every candidate has to pass the test suite, size limits, and a human PR review before it lands, so changes stay auditable. If you maintain a long-lived agent and hand-tuning has stalled, this offers a repeatable way to keep improving it.
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