hermes-self-evolution

Name: hermes-self-evolution
Rating: 5 (1 reviews)
Author: Lu1sDV

Replicates the Hermes Agent's self-evolving loop, enabling agents to learn from experience through persistent declarative memory, session recall, agent-managed procedural skills, and post-task review for skill creation/patching. Ideal for designing, evaluating, or operating AI agent workflows that need to save durable user/project facts and recall prior conversations.

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Updated 27 days ago

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Hermes Self Evolution

Implement the Hermes-style learning loop: keep user-facing work on the critical path, then persist only the durable knowledge that will reduce future steering. Treat the system as four cooperating surfaces:

Memory: compact, always-on facts about the user, environment, project conventions, and stable tool quirks.
Session search: on-demand recall of past conversations and completed task history.
Skills: procedural memory for reusable workflows, pitfal

[Description truncada. Veja o README completo no GitHub.]

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