exo:context

Configure agent context limits, overflow strategies, and caching for long-running conversations.

1|Updated Feb 16, 2026
One-click install
npx skills add https://github.com/midsphere-ai/exo --skill exo-context
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: exo:context
Source: https://github.com/midsphere-ai/exo/tree/main/skills/context
Command: npx skills add https://github.com/midsphere-ai/exo --skill exo-context

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Exo Context provides configurable, robust management of conversation context for agents, including context limits, overflow strategies, caching, and modular prompt composition via neurons, enabling scalable long-running interactions while controlling token usage and data retention.

Core Features & Use Cases

  • Context control with limit, overflow (summarize, truncate, none, hook)
  • ContextConfig and cache to persist processed context between runs
  • Neurons for modular prompt fragments and hierarchical task decomposition with fork/merge
  • Budget awareness and token counting to optimize costs
  • Safe, memory-backed history without mutating raw stores, with access to raw history when needed

Quick Start

Configure an Agent with a ContextConfig, enable overflow summarize, and optionally set cache to persist context across runs.

Frequently Asked Questions about exo:context

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

FAQPage Schema
How do I manage agent context limits and overflow for long-running conversations?

You can manage agent context limits and overflow by configuring ContextConfig to define a context_limit and selecting an overflow strategy like summarize, truncate, or none to control long-running conversation data retention.

What is the best way to persist agent memory and context across multiple sessions?

To persist agent memory and context across multiple sessions, enable caching by setting cache to True in your ContextConfig, ensuring processed context history is safely retained without mutating raw stores.

How do I optimize token usage and costs when configuring agent context?

You optimize token usage and costs by applying budget awareness and token counting within your ContextConfig, ensuring the agent remains aware of its token limits during long-running interactions.

Can I decompose hierarchical agent tasks using modular prompt composition?

Yes, you can decompose hierarchical agent tasks by utilizing Neurons for modular prompt fragments and applying fork/merge strategies to manage complex hierarchical task workflows efficiently.

When should I disable context management for an agent?

You should disable context management by setting context to None when an agent does not require conversation history retention or when operating in stateless execution modes where context tracking is unnecessary.

Does setting cache to True alter the raw conversation history stores?

No, setting cache to True maintains memory-backed history without mutating raw stores, ensuring you retain safe access to the original raw conversation history whenever needed.