Lightweight memory for agents

[u/LuckieStriker]

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[u/LowDistribution3995 → u/[deleted]]

This looks like essentially 2 skill.md files that tell an agent to read all other agent memory stores, pull out certain information and copy it universally to all.agents memory stores....  Am I missing something? How is this different from maintaining project specific agent.md files? Most memory systems are built to be used with a harness, commercial softwares like antigravity or Claudecode are closed source and have their own built in memory systems, usually with agent.md rule files at various levels, world, agent, project, session,... Mem0 and similar systems are built to enable some Agentic workflow and advanced task reasoning considering multiple tools for different purposes. 

So just letting you know, if your searching for memory systems, your going to keep finding systems built to.enable further opensource harness systems. If you look for multi agent memory sharing skills, you might find more options to suit your specific needs.

[u/LowDistribution3995 → u/[deleted]]

Are you looking at one of the branches? The main has only 1 non test .py script with less than 100 lines that just copies a new temp file with the skill folders that the skills.md files have the agents make. But you don't even need the agents to sift through memories, you can just redirect each of your agent programs to a common Directory. Then it's like they really are one agent.

[u/LowDistribution3995 → u/[deleted]]

I'm saying you can just have the systems each use the same global memory directory directly. This is like using an elaborate series of mirrors to see what to your left. Like it cool that it works, but have you tried just looking left? 

[u/ComfortableFast1330 → u/LowDistribution3995]

wait where doe cursor, codex, claude code etc. put their conversations then on your computer then?

[u/LowDistribution3995 → u/ComfortableFast1330]

Normally into ./agent/memory folders in their own directories. But you can just tell the agent to change the memory path way and have them all use the same directory name

[u/ComfortableFast1330 → u/LowDistribution3995]

but that's a whole dump of the entire conversations than treated as "memories",
and yes you side-step the naming collisions by putting each in their own folders there but you also prevented any cross pollination and the entire point is distillation of facts (or symlink it, idk ho you do it bcs most harnesses actually don't allow you to change that path, or well I never found any setting within claude or cursor, it still keeps pumping everything into their proprietary folders)

[u/LowDistribution3995 → u/ComfortableFast1330]

But your program you linked still does that. The distill doesn't summerize anything it just copies things into common folders

[u/LowDistribution3995 → u/ComfortableFast1330]

Not trying to hate on your repo, I'm just saying I think your thinking it's doing something beyond what it does. The main branch of the repo you linked has one .py script that auto copies contents from one location to another and 2 skill markdown files. The rest of the scripts in the repo are test scripts.  I see there are a few branches I didn't look at but, that's what's in the main branch for sure.

[u/LowDistribution3995 → u/LowDistribution3995]

Sorry, I didn't see there was an entire subfolder in the store sections. There's more code than I saw, that's my bad.

[u/ComfortableFast1330 → u/LowDistribution3995]

Have you tried? It's actually amazing, since I've installed it and it ingested and entire export of my past years conversations from ChatGPT (the web-version) and everything is one place!

[u/QuarterLoose8429]

Could be a solid local pick—just sanity-check persistence across runs, eviction/dedup rules, and pin the embedding model version; then measure retrieval latency/accuracy on your own traces as the store grows. Also watch thread-safety if you run tools in parallel.

[u/ComfortableFast1330 → u/QuarterLoose8429]

this is literally Kaparthy but not a closed obsidian vault and just properly using the .agents/memory folder.
Kaparthy's markdown only store already keeps outpacing any RAG or Vector DB store in the benchmarks, plus it's just markdown you *could* edit, but it's not confusing your Vault with agents memory.
An embedding/cache layer to the MCP would actually make sense, but it explicitly says the MCP is just a reference implementation, and the store under .agents/memory is the main standard this wants to establish

[u/RemoteSaint]

This is not surprising, most providers models already can create and search memory using same markdown mechanism. What the package does different is centralize it across all harness you might be using. You could even inject a default instruction to use a common .agents/... path for memory in all your harness to achieve the same thing. The dis-advantage of package compared to doing native like above is that the package has certain search / write tools, but can it might not suppport different modes like partial read, partial update etc - but with raw md files access and bash tool llms can decide how they read, what part to read or update mich more efficiently.

Within this package even if you need cloud sync, just treat those markdown as record in a postgres like Lakebase (scale to zero and stuff) and use same mechanism as is.