honcho

Manage cross-session user modeling for conversational agents with Python libraries and Honcho AI services.

4|Updated Apr 19, 2026
One-click install
npx skills add https://github.com/ragnarokhaa/hermes --skill honcho-ragnarokhaa
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: honcho
Source: https://github.com/ragnarokhaa/hermes/tree/main/hermes-cerul-tech-news-package/hermes-cerul-tech-news-package/hermes-agent/optional-skills/autonomous-ai-agents/honcho
Command: npx skills add https://github.com/ragnarokhaa/hermes --skill honcho-ragnarokhaa

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires honcho-ai, and includes scripts (resource) components.

What problem does it solve?

Honcho AI provides advanced cross-session user modeling for Hermes, solving the issue of maintaining context across different conversations, enabling personalized agent profiles, and isolating multi-profile sessions effectively.

Core Features & Use Cases

  • User Modeling: Builds user profiles based on conversations and messages to enable a coherent conversation across different sessions.
  • Multi-profile Management: Each Hermes profile gets a dedicated Honcho peer while maintaining a unified user representation.
  • Observation Config: Fine-grained control over what Honcho learns from users and other peers for building comprehensive profiles.
  • Dialectic Reasoning: Leverages advanced memory tools for context injection and reasoning capabilities, enhancing the conversational AI's decision-making.

Quick Start

To configure Honcho with Hermes, use: hermes honcho setup

Frequently Asked Questions about honcho

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

FAQPage Schema
How do I maintain conversational context across different AI sessions?

Cross-session context is maintained by building user profiles from past conversations. Honcho integrates with Hermes to store user-centric observations and shared memories, enabling coherent, personalized interactions across multiple sessions.

Can I isolate memory and profiles for multiple users in the same conversational agent?

Yes, multi-profile management is supported. Each Hermes profile is assigned a dedicated Honcho peer while maintaining a unified user representation, effectively isolating sessions while building comprehensive individual profiles.

How do I set up cross-session user modeling for Hermes?

To set up cross-session user modeling, use the command `hermes honcho setup`. This configures the Honcho AI integration, requiring the `honcho-ai` Python library to implement memory-intensive interaction flows.

What is dialectic reasoning in AI memory tools?

Dialectic reasoning leverages advanced memory tools for context injection into conversations. It enhances the conversational AI's decision-making capabilities by utilizing stored user observations and shared memories for deeper reasoning.

Does Hermes user modeling require external Python libraries?

Yes, implementing complex memory-intensive interaction flows requires the `honcho-ai` Python library. The Skill depends on these external libraries and Honcho AI services to manage cross-session user modeling effectively.

How can I control what the AI learns from user conversations?

Observation configuration provides fine-grained control over what the system learns from users and other peers. This allows you to specify exactly which data builds the comprehensive user profiles.