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hermes-agent

Integrates AI agent papers into a CLI framework for recursive task decomposition and multi-platform control.

Updated Apr 29, 2026
Search Tags:#task automation#ai agent#multi-platform#autonomous agent#persistent memory#provider-agnostic#extensible
One-click install
npx skills add https://github.com/fikriaf/agentos --skill hermes-agent-fikriaf
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hermes-agent
Source: https://github.com/fikriaf/agentos/tree/main/src/agentos/skills/autonomous-ai-agents/hermes-agent
Command: npx skills add https://github.com/fikriaf/agentos --skill hermes-agent-fikriaf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires openrouter, anthropic, nous, openai-codex, github-copilot, google-gemini, deepseek, xai-grok, hugging-face, zai-glm, minimax, kimi-moonshot, alibaba-dashscope, xiaomi-mimo, kilo-code, ai-gateway, opencode-zen, opencode-go, qwen-oauth, custom-endpoint, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill addresses the need for a comprehensive AI agent framework that can handle complex tasks, maintain persistent memory, and interact with a variety of platforms.

Core Features & Use Cases

  • Recursive Task Decomposition: Break down complex tasks into parallel subtasks for efficient execution.
  • Safety-First Execution: Implement MOSAIC-style Plan→Check→Act/Refuse for secure execution.
  • Budget-Aware Planning: Estimate costs using INTENT-style cost estimation.
  • Long-Horizon Memory: Externalize state for persistent memory across sessions.
  • Multi-Platform Gateway: Run the same agent on multiple platforms like Telegram, Discord, and Slack.
  • Provider-Agnostic: Swap models and providers without workflow changes.
  • Profiles: Run multiple independent instances with isolated configurations.
  • Extensibility: Add plugins, MCP servers, custom tools, and leverage the Python ecosystem.
  • Use Case: For software development, research, system administration, and more, this Skill enables AI agents to assist with a wide range of tasks.

Quick Start

Use the hermes-agent skill to set up your environment with the following command: Use the hermes setup command to configure your environment and select the appropriate model and provider.

Frequently Asked Questions about hermes-agent

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build an autonomous AI agent for complex task automation?▼

Build autonomous AI agents by using a CLI framework that supports recursive task decomposition, breaking complex tasks into parallel subtasks for efficient execution. This approach enables safety-first execution and budget-aware planning for versatile control.

What is recursive task decomposition in AI agent frameworks?▼

Recursive task decomposition is an AI agent mechanism that breaks down complex tasks into parallel subtasks for efficient execution. It allows autonomous agents to handle sophisticated automation by dividing work into manageable, concurrent operations.

Can I use different LLM providers like OpenAI and Anthropic without changing my agent workflow?▼

Yes, you can swap models and providers without workflow changes using a provider-agnostic gateway. The framework supports extensive providers including OpenAI, Anthropic, Google Gemini, DeepSeek, and custom endpoints for seamless model integration.

Does this AI agent framework support multi-platform deployment on Discord and Slack?▼

Yes, the multi-platform gateway supports running the same agent on multiple platforms like Telegram, Discord, and Slack. You can deploy your autonomous agent across different communication channels without altering core logic.

How do I maintain persistent memory across AI agent sessions?▼

Maintain persistent memory across sessions by externalizing agent state. This long-horizon memory capability ensures your autonomous agent retains context and historical data between different execution cycles.

What is the best way to ensure safe execution when automating tasks with AI agents?▼

Ensure safe execution by implementing MOSAIC-style Plan→Check→Act/Refuse protocols. This safety-first approach validates actions before execution, preventing potentially harmful operations during autonomous task automation.

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