Product Thumbnail

Epismo Context Pack

Portable memory for agent workflows

Productivity
Developer Tools
Artificial Intelligence

Hunted byHirokiHiroki

Context Pack is portable memory for agent workflows. Turn prompts, plans, decisions, project context, and hard-won know-how into reusable packs you can fetch across agents and threads. Keep them private, share them with your team, or publish them for the community, so others can reuse proven context instead of starting from scratch. Works across MCP and CLI, with support for cloud agents, local setups, Slack, and Discord.

Top comment

We built Context Pack because valuable context keeps getting trapped inside one chat, one tool, or one moment. That leads to a lot of manual work: moving context between agents, re-explaining the same project in new threads, pasting old prompts again, or rewriting good discussions into docs just to share them. Context Pack makes that reusable. A pack is a title + content set. You can use it for prompts, plans, decisions, project context, or hard-won know-how. You can fetch titles first, load full content only when needed, and use your context window more efficiently. One of the most exciting parts is that packs are not limited to private use. You can keep them private, share them with your team, or publish them for the community. That means Context Pack is not just about saving your own memory. It is also a way to reuse proven context from others. AI power users can publish the memory behind their workflows, prompts, research habits, and playbooks, and others can build on that instead of starting from scratch. To get started, you can simply tell your agent: `Set up Epismo access and load the Skills from https://github.com/epismoai/skills` The Skills are designed for both MCP and CLI, so you can use Context Pack with cloud-based agents like ChatGPT or Claude, local setups like Claude Code or Codex, and even Epismo agent on Slack or Discord. For a first example of how to share a Context Pack: `/context-pack @hirokiyn/context-pack` Would love to hear how you’d use it.

Comment highlights

how do you handle context conflicts when multiple agents write to the same memory pack?

The part about reusing context from other people's workflows is interesting. If I load someone's published context pack, does it just give me their prompts or does it actually carry over the decisions and reasoning behind why they built it that way?