# YeQing17-2026/OmniAgent

An agent capable of self-evolving and dynamically hardening security

Repository: https://github.com/YeQing17-2026/OmniAgent
Canonical: https://ross.abutalabs.com/products/omniagent
Homepage: https://yeqing17-2026.github.io/OmniAgent/
Language: Python
License: NOASSERTION
License Family: other
Topics: agent, hermes, open-claw
Last push: 2026-07-27T07:54:11+00:00

## Health v2 (maintenance only)
Score: 56/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 94, release rhythm 35, longevity 9
- inputs: {"age_days": 139, "days_push": 37, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, young, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2549, forks 383 (observed 2026-08-28T04:07:00.424661+00:00)

## What it is
OmniAgent is an open-source Python agent framework that self-evolves across skills, context, memory, and its underlying model during interaction, inspired by OpenClaw. It pairs this evolution with dynamic security hardening via a Hyper-Harness execution scaffold and a dual-layer Deep Reflexion architecture.

## Use cases
- build a self-evolving ai agent that learns from interactions
- run a coding assistant that remembers my project and avoids past mistakes
- safely execute shell commands with sandboxing and human approval
- deploy a chatbot to cli, web, discord, and telegram from one codebase
- research assistant that searches the web and remembers what worked
- agent framework with online reinforcement learning for the brain model

## When to choose
- you want an agent whose skills, memory, and context improve in real time during use
- you need layered safety controls (llm review, policy engine, approval, sandbox) for agent command execution
- you want one agent deployable across cli, web ui, feishu, discord, and telegram
- you're comparing against OpenClaw or Hermes and want faster skill evolution and lower token cost

## When to avoid
- you need a simple, static agent with predictable, unchanging behavior
- you require a permissively licensed dependency (GPL-3.0)
- you need a mature, long-proven framework - the project is new and docs are still in progress
- you don't want a self-modifying agent touching your model or context

## Facets
- artifact type: framework
- maturity: active
- function: agent-framework, llm-inference, security, chatbot, machine-learning, cli, webhook
- domain: artificial-intelligence, large-language-models, security, developer-tools
- platform: python, cli, cross-platform, self-hosted
- tags: self-evolving-agent, omni-evolve, proactive-memory, skill-evolution, context-evolution, online-reinforcement-learning, hyper-harness, deep-reflexion, sandboxing, multi-channel-deployment, openclaw-inspired, ai-agents, automation, discord, telegram

## Member repositories
- YeQing17-2026/OmniAgent (main) score 56

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:07:00.424661+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:23:59.968554+00:00, confidence not recorded.
  - readme: https://github.com/YeQing17-2026/OmniAgent (fetched 2026-08-28T04:07:00.424661+00:00, sha a835d6efd122)
  - homepage: https://yeqing17-2026.github.io/OmniAgent/ (fetched 2026-08-29T10:06:36.434356+00:00, sha a7a4c58b4084)
- Data as of 2026-08-30T08:39:29.467469+00:00.