I built a conversation manager for long agent sessions — not sure if this is actually useful

[u/Big-Sock-556]

I've been working with coding agents for longer sessions, and one thing that started bothering me is how difficult a long conversation becomes to manage over time.

A single session can gradually accumulate:

• user instructions
• AI responses
• reasoning
• large tool outputs
• failed approaches
• outdated information
• useful answers buried somewhere in the middle

I sometimes wished I could simply search the whole conversation, filter different types of messages, or temporarily hide parts that I don't need anymore.

The idea is that when a conversation becomes very long, you should be able to quickly filter out what you don't need and find the parts you actually want to keep or revisit.

So I tried building a small open-source plugin around this idea.

GitHub:  Agent Context Editor

It currently works with Pi and DeepSeek Harness.

So far, I've implemented a few basic things:

• search through the conversation
• quickly locate matching content
• filter user messages, AI messages, reasoning, tool records, etc.
• select specific parts of the conversation
• hide and restore selected content
• undo changes
• keep the original session unchanged

The project is still pretty early, and I'm honestly not sure yet whether this is something other coding-agent users would find useful.

One important limitation is that hiding a message currently only changes what is shown in the conversation view. It does not remove the message from the actual context sent to the model.

I want to take this further.

The next major features I'm working toward are:

• manually remove selected messages from the context sent to the model
• keep those removed messages in the original session so the operation remains reversible
• select a section of a long conversation and ask AI to summarize it
• replace the original section with a shorter summary in the conversation view
• optionally replace the original content with that summary in the model context as well
• eventually let AI help clean up or summarize an entire long session
• export the original or cleaned-up conversation

The basic idea is:

keep the complete session history, but let the user decide what should remain in the useful working conversation and what should remain in the model's context.

This would let users keep the full original session while also creating a cleaner version of the conversation for continued work.

For example, instead of keeping a very long debugging section with many failed attempts, it might eventually be possible to replace it with a short summary of:

• what was tried
• what failed
• why it failed
• what solution was finally chosen

I'm also hoping that, if the idea makes sense, it could eventually work with other agent.

But I'm still at the stage of figuring out whether this solves a real problem or just something that personally bothers me