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honcho

Configure Honcho memory integration for Titan with peer-isolated profiles.

1|Updated May 16, 2026
Search Tags:#memory#profiles#context budget#honcho#user modeling#recall mode#dialectic reasoning
One-click install
npx skills add https://github.com/devMoez/titan --skill honcho-devmoez
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: honcho
Source: https://github.com/devMoez/titan/tree/main/optional-skills/autonomous-ai-agents/honcho
Command: npx skills add https://github.com/devMoez/titan --skill honcho-devmoez

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Honcho Skill setup streamlines cross-session AI memory and peer-based user modeling in Titan, so your agent can consistently remember you, respect profile isolation, and keep context budgets under control.

Core Features & Use Cases

  • Configure Honcho integration: Set up cloud or self-hosted Honcho, verify connection, and enable the memory provider flow for Titan profiles.
  • Manage multi-profile user modeling: Create separate AI peers per Titan profile while sharing a unified user representation across peers.
  • Tune recall, observation, and dialectic behavior: Adjust recall modes, per-peer observeMe/observeOthers, and dialectic knobs (cadence, depth, reasoning level) for cost/quality tradeoffs.
  • Control context injection safely: Enforce context token budgets and apply memory-context sanitization to reduce prompt corruption risks from stored content.
  • Operational use cases: Fix memory not persisting, troubleshoot syncing/peers, and tune session summaries and context injection when sessions grow long.

Quick Start

Use the honcho Skill by running Titan honcho setup and selecting cloud or local, then pasting your Honcho API key or base URL.

Frequently Asked Questions about honcho

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

FAQPage Schema
How do I set up cross-session AI memory for user modeling?▼

Configure cross-session AI memory by running the Honcho setup command, selecting cloud or local, and pasting your API key or base URL to enable persistent user modeling across sessions.

What is peer-isolated profile management in AI memory systems?▼

Peer-isolated profile management creates separate AI peers per profile while sharing a unified user representation across peers, ensuring context remains isolated yet user data stays consistent.

How do I keep context token budgets under control during long AI sessions?▼

Control context token budgets during long AI sessions by enforcing context limits, applying session summaries, and using sanitized memory-context injection to reduce prompt corruption risks from stored content.

Can I tune dialectic reasoning and recall modes for cost and quality tradeoffs?▼

Yes, you can tune dialectic reasoning and recall modes by adjusting cadence, depth, reasoning level, and per-peer observation toggles to balance cost and quality tradeoffs in memory injection behavior.

Why is my AI memory not persisting across sessions after setup?▼

AI memory not persisting across sessions typically indicates a failed setup verification or peer synchronization issue, requiring troubleshooting of the Honcho connection and memory provider flow configuration.

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